• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.651-660
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• 2015

This study was conducted to consider application methods of infographic that corresponds to the educational goals of English subject, which is applied with different teaching and learning standards than other subjects. The aim of this study is to analyze the types and the characteristics of 'infographic completed by know-how learning', in other words, 'User behaviors involved infographic', which is frequently used in English textbook. Based on an analysis according to the teaching and learning standards, infographic used in English textbook were suggested in three types, which are 'General Concept', 'Significance' and 'Signification' centered infographic. In addition, according to the level of diagram composition, the main visualization attributes were derived as 'Overview', 'Structure', 'Relationships', 'Sequence', 'Transition between states' and 'Messages'. The major findings of this study are as follows: First, it is necessary to conduct a study on diverse display methods for 'Signification-centered infographic' that need to be displayed on the basis of two or more visual attributes. Second, as the purpose of application for applying infographic in English textbook collides with that in information design fields, it is found that verification is required on the educational effects in relation to this aspect.

• Smart Media Journal
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• v.10 no.1
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• pp.47-54
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• 2021

Web accessibility is presented as a legal obligation to ensure users can access and use information and functions equally in the domestic public website sector. This study introduces the researcher network based on social network analysis (SNA) in order to show the citation relationship by identifying the network among researches in the field of web accessibility. Based on the analysis of the relationship and citation of academic researchers in the domestic web accessibility field, confirm the process of creating a research network. It is a visualization element that shows the citation relationship as well as the relationship and citation form between the studies as a network. Through the process of creating the network, and it can be confirmed and can be usefully used for future academic research network analysis. It is meaningful in terms of analysis for about 17 years from January 2000 to March 2017, a total of 50 papers published in journals registered by the National Research Foundation of Korea and candidate journals. By combining the evaluation metrics for each researcher, evaluation target, evaluation method, and evaluation result for web accessibility, and applying weights, identify the research direction and evaluation research trends in Korea's web accessibility field related to the relevant field and web accessibility evaluation research trends, and related to the researcher trend network.

• Communications of Mathematical Education
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• v.25 no.1
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• pp.245-259
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• 2011

In this study, the instrument of mathematical creative problem solving ability test were considered the differences between Korean and American sixth grade students in mathematical creativity ability and mathematical thinking ability. The instrument consists of 9 items. The participants for the study were 212 Korean and 148 American students. SPSS were carried out to verify the validities and reliability. Reliabilities(Cronbach ${\alpha}$) in mathematical creativity ability is 0.9047 and in mathematical thinking ability is 0.9299 which were satisfied internal validity evaluation on the test items. Internal validity were analyzed by BIGSTEPS based on Rasch's 1-parameter item response model. The results of this study can serve as a foundation for understanding the Korean and American students differences in mathematical creativity ability and mathematical thinking ability. Especially we get the some informations on mathematical creativity ability for American's fifth grade to seventh grade students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.330-336
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• 2020

An anti-collision system between equipment is essential on a drill floor where multiple moving machines are operated simultaneously. This is to prevent accidents by halting the machines when required, by inspecting possibility of a collision based on the relative position data sent by the equipment. In this paper, we propose a framework for an Anti-Collision System (ACS) by considering expandability of the number of machines and computational speed, to promote development of drilling machines and corresponding ACS software. Each drilling equipment is represented as an object in the software with its own message format, and the message is constructed with serialization/deserialization to manage any additional equipment or data. The data handling process receives the current status of machines from the drilling control network, and relays a collision related message (including bypass signal) back to the machines. A commercial visualization software shows the bounding boxes moving with the equipment and indicates probable collision. It has been determined that the proposed system maintains total execution time below 5ms to process data from the network and relay the information hence, the system has no effect on the machine control systems having 100ms control cycle.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.73-83
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• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.372-390
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• 2021

The objective of this study is to understand the current status of damage to Korean musical caused by the COVID-19, and also to seek for the coping measures and development direction in the post-Corona era. Thus, to understand the current status of damage, this study mainly researched the contents of NAVER TV musical performance transmitted for three years from March 2018 to February 2021 for analyzing the online performance and performance statistical data of Performing Arts Box Office Information System. As a result, this study could find a hypothesis and grounds to simultaneously verify and draw the positive and negative sides, pessimistic implications, and optimistic possibility. First, the performing arts would be multilaterally expanded after being divided into offline performance and online performance. Second, the utilization of online performance could narrow the gap(polarization) between capital area and non-capital area. Third, it is urgently needed to develop a win-win model for the establishment of a new musical market. Fourth, the performers' copyrights should be fairly protected. Fifth, the visualization requires the Korean-style support foundation and talent equipped with convergent thinking and knowledge. In such temporal changes from offline performance to online performance, there should be more sophisticated qualitative and quantitative growth in musical market.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.343-350
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• 2022

High-resolution data are needed to understand water body mixing patterns at river junctions. In particular, in river analysis, hydrological and water quality characteristics are used as basic data for aquatic ecological health, so observation through continuous monitoring is necessary. In addition, since measurement is carried out through a one-dimensional and fixed measurement method in existing monitoring systems, a hydrological and water quality characteristics investigation of an entire river, except for in the immediate vicinity of the measurement point, is not undertaken. In order to obtain high-resolution measurement data, a measurer has to consider multiple factors, and the area or time that can be measured is limited. Although the resolution might be lowered, an appropriate interpolation method must be selected in order to acquire a wide range of data. Therefore, in this study, a high-elevation measurement method at a river junction was introduced, and the interpolation method according to the measurement results was compared. The overall hydraulic and water quality information of the river was indicated through the visualization of the prediction and interpolation method in the low-resolution measurement result. By comparing each interpolation method, Inverse Distance Weighting, Natural Neighbor, and Kriging techniques were applied in river mapping to improve the precision of river mapping through visualized data and quantitative evaluation. It is thought that this study will offer a new method for measuring rivers through spatial interpolation.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.