Proceedings of the Korea Contents Association Conference
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2010.05a
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pp.277-280
/
2010
The prevention of disasters is important to prepare in advance through analysis and an estimate. But for all the efforts of the government to stave off disasters, the damage out of a guerilla localized heavy rain caused the global warming, a landslide and inundation is growing. To prevent these damages, the basic data and system through systematic research and analysis should be set up. But it is true that collecting of the basic data and the system for preventing disasters are either constructing or insufficient so far. In this research, by using topography spatial data including LiDAR data including the aerial photo and digital maps, and etc. the factor of a disaster, the disaster risk element was extracted. Moreover, the disaster region about the disaster generation available region was evaluated in advance using the easy disaster analysis of current situation photo map which made with the grid analysis method and weighted value estimate technique.
Kim, Min Seok;Lee, Mi Ran;Choi, Woo Jung;Lee, Jong Kook
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.30
no.6_1
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pp.567-574
/
2012
For the past few years, the video surveillance market has shown a rapid growth due to the increasing demand for Closed Circuit Television(CCTV) by the public sector and the private security industry. While the overall utilization of CCTV in the public and private sectors is expanding, its usage in the field of disaster management is less than sufficient. Therefore, the authors of this study, in an effort to revisit the role of CCTV in disaster situations, have carried out a case analysis in the vicinity of the Gangnam Station which has been designated as a natural disaster-prone area. First, the CCTV images around the target location are collected and the time and depth of inundation are measured through field surveys and image analyses. Next, a rainfall analysis was conducted using the Automatic Weather Station(AWS) data and the past inundation records. Lastly, the authors provide an estimate of rainfall for the areas around the station and suggest viable warning systems and countermeasures. The results from this study are expected to make positive contributions towards a significant reduction of the damages caused by the floods around the Gangnam Station.
The purpose of this study was to analyze the factors affecting the awareness of temporomandibular disorders in high school students and to provide basic data for the development of easy-to-access program to help the management of temporomandibular disorders. For data collection, convenience sampling was performed among academic high school students in Daejeon and North Jeolla Province to complete a self-administered questionnaire from December 1 to 30, 2019. The statistical analysis was conducted by t-test, one-way ANOVA, and Pearson correlation. Stepwise multiple regression analysis was conducted. Oral parafunctional habits were positively correlated with trait anxiety and both of them were positively correlated with the perceived symptoms of temporomandibular disorders. The most influential factors on the awareness symptoms of temporomandibular disorders in high school students were oral parafunctional habits, health habits, and trait anxiety. It is necessary to make positive communication and intervention, which meets high school age, in coping well with anxiety and managing oral parafunctional habits and apply an oral health promotion program that involves socio-psychological efforts to prevent them.
UML class diagrams are used to visualize the static aspects of a software system and are involved from analysis and design to documentation and testing. Software modeling using class diagrams is essential for software development, but it may be not an easy activity for inexperienced modelers. The modeling productivity could be improved with a dataset of class diagrams which are classified by domain categories. To this end, this paper provides a classification method for a dataset of class diagram images. First, real class diagrams are selected from collected images. Then, class names are extracted from the real class diagram images and the class diagram images are classified according to domain categories. The proposed classification model has achieved 100.00%, 95.59%, 97.74%, and 97.77% in precision, recall, F1-score, and accuracy, respectively. The accuracy scores for the domain categorization are distributed between 81.1% and 95.2%. Although the number of class diagram images in the experiment is not large enough, the experimental results indicate that it is worth considering the proposed approach to class diagram image classification.
Journal of the Korean Association of Geographic Information Studies
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v.17
no.1
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pp.91-106
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2014
This study tries to cluster the 795 standard watersheds of Korea Water Resources Unit Map using multivariate statistical analysis technique. The 30 factors of watershed characteristics related to topography, stream, meteorology, soil, land cover and hydrology were selected for comprehensive analysis. From the factor analysis, 16 representative factors were selected. The significant factors in order were the pedological feature, scale and geological location and meteorological and hydrological features of the watershed. As a next step, the 73 gauged watersheds were selected for cluster analysis. They are scattered properly to the whole country and the discharge data were within a confidential level. Based on the 73 watersheds, the other ungaged watersheds were clustered by applying the 16 factors and calculating Euclidian distances. The clustering results showed that the similarity between standard watersheds within the same river basin were 87%, 69%, 41%, 52%, and 27% for Han, Nakdong, Geum, Seomjin, and Yeongsan river basins respectively.
Journal of the Korean Society for Library and Information Science
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v.50
no.4
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pp.97-120
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2016
This study is to objectively deduce components of a public library culture and define a library culture. Thus, the study gathers the opinions and the experiences of the expertise in this specific area of a library culture. Furthermore, the study takes gathered informations and dates into consideration, to derive a measurement of final components, delphi technique. Through usage of Delphi technique, it allowed selected final components to operate a comparative analysis of the elements, which then it helps to measure each element's critical importance, identify priorities of each element by using a hierarchical decision making method. The major conclusions of this study are as follows. First, the study used a two-step delphi survey which was conducted on a panel of experts (Faculty of Library and Information Science (LIS) and the librarians), deduced the components of a library culture. In the primary survey, the study found 29 components (material culture 6, non-material culture 23). In the secondary survey, it deduced 21 components (material culture 3, non-material culture 18). Second, through comparative analysis, the prioritization of the public library culture components presented in following orders, , , and . The Most weighted values of each components were, of 'data usage and its method.'; of 'core values of librarianship'; of 'library ethical consciousness.' appeared as such.
Korea, which has undergone a rapid urbanization, faces various problems such as the management of facilities, safety, environment and transportation. To solve civil complaints, local governments receive electronic complaints, but complaints are increasing. Therefore, this study conducted the spatial distribution pattern analysis and the trend analysis by presenting location data on spatial information through Geo-coding by collecting electronic civil petition data over the last 10 years targeting Jinju city. Using the ARIMA model, this study predicted the occurrence of complaints over the next two years (2016~2017) through a time series forecast analysis. As a result, the complaints related to illegal parking were the highest, the complaint related to noise was the second highest, and the complaints related to illegal garbage dumping was the third highest. In addition, the analysis of the spatial distribution pattern shows that the largest hot spot was formed in the central commercial district every year. As a result of the time series forecasting analysis for the crackdown of the illegal parking, complaints increased slightly. To compare the predicted value and the actual data showed a similar pattern. It is judged that this study will be utilized to establish effective countermeasures against civil complaints.
Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.
News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.
Journal of The Korean Association For Science Education
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v.18
no.1
/
pp.43-60
/
1998
The purpose of this study is to compare and analyse the elementary school science curriculum and textbooks of South and North Korea, then gather the fundamental sources for the establishment of elementary school science curriculum after Unification of Korea by clarifying the difference and the likeness in educational objectives, contents, teaching methods of both Korean elementary school sciences. Based on this comparison and analysis, this study tried to give the concrete suggestions for the elementary school science curriculum and textbook development after Unification. For this, analyses were carried out for the curriculum managing systems, subject organization, education goal, emphasis on each field, teaching-learning and evaluation method. Besides, this study compared and analysed the elementary school science textbook development and distribution system, apparent format, content organization, ratio of content categories, content scope and level and the related terms appeared in both Korean elementary school science textbooks. The result of this study showed a lot of differences in the educational objectives, contents, and educational method of the elementary school science between South and North Korea. The grasping of these differences and the exact understanding about what causes these differences and how the differences are made must be the necessary work for the science curriculum establishment, especially for elementary school science curriculum and textbook development, after Unification.
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