• Coupled systems mechanics
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• v.11 no.1
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• pp.33-41
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• 2022

Quite often we have a lot of measurement data and would like to find some relation between them. One common task is to see whether some measured data or a curve of known shape fit into the cumulative measured data. The problem can be visualized since data could generally be presented as curves or planes in Cartesian coordinates where each curve could be represented as a vector. In most cases we have measured the cumulative 'curve', we know shapes of other 'curves' and would like to determine unknown coefficients that multiply the known shapes in order to match the measured cumulative 'curve'. This problem could be presented in more complex variants, e.g., a constant could be added, some missing (unknown) data vector could be added to the measured summary vector, and instead of constant factors we could have polynomials, etc. All of them could be solved with slightly extended version of the procedure presented in the sequel. Solution procedure could be devised by reformulating the problem as a measurement problem and applying the generalized inverse of the measurement matrix. Measurement problem often has some errors involved in the measurement data but the least squares method that is comprised in the formulation quite successfully addresses the problem. Numerical examples illustrate the solution procedure.

• Journal of Information Science Theory and Practice
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• v.10 no.1
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• pp.73-88
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• 2022

This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ² analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.66-71
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• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.41-46
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• 2022

The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.77-82
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• 2015

This paper proposed an accident prediction model in order to prevent accidents in mountain areas using a big data analysis. Data of accidents in mountain areas are shown as graphs. We have analyzed cases: the number of accidents per year, day of week, time of day to find patterns of the negligent accident in mountain areas. The proposed prediction model consists of weighted variables of the accident in mountain through visualized big data analysis. The model of danger index performance is demonstrated by showing accident-prone areas with weighted variables.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Korean Journal of Computational Design and Engineering
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• v.17 no.5
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• pp.353-363
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• 2012

As the distributed simulation system has been developed in the defense modeling and simulation, interoperability among heterogeneous simulators is essential to achieve the objectives of the distributed simulation system. However, the interoperability has been a problem to synchronize synthetic environment among many heterogeneous simulators that utilize different environmental data formats. SEDRIS (Synthetic Environmental Data Representation and Interchange Specification) was initiated to solve the problem of the interoperability. SEDRIS provides a standard mechanism to promote data interchange and reusability, and it represents all environmental things from ocean, land and atmosphere to the universe. Although SEDRIS provides various advantages as a standard environmental data format, applying of SEDRIS has been hindered by its broadness and complexity. The main objective of this paper is to explain application development process to improve SEDRIS usability for the atmosphere and ocean. The developed application of this paper provides auto-generation of SEDRIS data with minimum user's input, and the auto-generated SEDRIS data is also visualized and verified by the application.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.37-43
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• 2022

In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.463-466
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• 2007

In this study, 3D building reconstruction and road design were performed using LiDAR data, digital map and airborne digital image. Information for tourism was extracted from digital maps (scale: 1/5,000) of Jeju Island, and then route of the road was determined for road design. Reconstructed buildings, aerial image and designed road were overlayed with tourism information for 3D simulation. In addition, landscape analysis was performed and result of the road design was visualized.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.427-428
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• 2009

Optical imaging offers excellent spatio-temporal sensitivity that is unparalleled by any other perfusion based imaging techniques. We used in vivo optical recording of intrinsic signals (ORIS) to map neurovascular hemodynamics of perfusion, oximetry and membrane potential during epileptic events in rat and mouse neocortex. Studies of hemodynamic changes with ORIS alone were also performed in human. Laboratory studies in rodent epilepsy models have demonstrated a persistent increase in deoxygenated hemoglobin (Hbr) and a decrease in tissue oxygenation during interictal spikes and ictal events. This "epileptic dip", like the "initial dip" recorded during normal sensory processing, implies that the enormous rise in cerebral blood flow (CBF) is inadequate to meet the increased metabolic demands associated with synchronized epileptic activity. These findings are critically important to the interpretation of the perfusion-based imaging studies, such as fMRI. In addition, we visualized the effect of direct cortical electrical stimulation, an alterative epilepsy treatment. The optical data following direct cortical electrical stimulation showed that hemodynamic signals are sensitive to different electrical stimulation parameters. Furthermore, our recent data demonstrated that the application of unilateral electrical stimulation is able to elicit bilateral hemodynamic responses in rat neocortex.