• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.422-424
• /
• 2018

Recently there has been growing interest in big data analysis and methods for collecting data have been developed diversely but researchers are still not easy to collect and use these large scale data. In this paper, researchers try to compare and analyze the method of collecting big data by using several methods and present it. I hope that you can provide the results of your research if you select and use methods that match your research objectives.

• Journal of Korean Association for Spatial Structures
• /
• v.10 no.2
• /
• pp.135-145
• /
• 2010

The objective of this study is to draw basic data for the application of the fire protection planning for the future plan large enclosure buildings in Korea through an analysis of its characteristics by case studies of the domestic and foreign large scale gymnasiums. In this study, domestic building codes for the fire protection are investigated and fire detection systems, fire extinguishing systems, smoke control systems and evacuation systems of three large scale gymnasiums located at Korea and eight foreign countries are compared and analyzed. The results of this study show that infrared light fire detection system and flame detector for spacial characteristics are potentially used in fire protection systems of large scale gymnasiums: dry type sprinkler and sprinkler water gun are adopted in fire detection system; and smoke accumulation system is widely utilized in smoke control system.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.4
• /
• pp.273-286
• /
• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.5
• /
• pp.502-515
• /
• 2020

To identify the dynamic characteristics of the Auto-leveling system applied to the Tractor-Trailer type Transporter for mounting a large scale precision equipment, Dynamics Modeling & Simulation were performed using general Dynamics Analysis Program - RecurDyn(V9R2). The axial load data, transverse load data and pad trace data of leveling actuators were obtained from M&S. And they were analyzed and compared with each other by parameters, i.e. friction coefficients on the ground, landing ram speed of actuators, and direction & quantity of ground slope. It was observed that ground contact friction coefficients affected to transverse load and pad trace; the landing ram speed of actuators to both amplitude of axial & transverse load, and this phenomena was able to explain from the frequency analysis of the axial load data; the direction of ground slope to driving sequence of landing ram of actuators. But the dynamic behaviors on the two-directional slope were very different from them on the one-directional slope and more complex.

• Journal of Distribution Science
• /
• v.21 no.5
• /
• pp.101-111
• /
• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.2-5
• /
• 2021

With the recent development of the Internet of Things (IoT) technology, various terminals are being connected to the Internet. As a result, the amount of IoT data is also increasing, and an index key that can efficient analyze the large-scale IoT data is proposed. Existing index keys have only time and space information, so if data stored in index tables and instance tables were queried using repetition or join operation, IoT data was embedded in the index key of the proposal to create OLAP-based big tables to minimize the number of repetitions or join times.

• Korean Management Science Review
• /
• v.32 no.2
• /
• pp.69-78
• /
• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• International Journal of Contents
• /
• v.16 no.3
• /
• pp.18-32
• /
• 2020

The aim of this study was to perform a meta-analysis of the learning outcomes of immersive learning technologies in English language teaching (ELT). This study examined 12 articles, yielding a total of 20 effect sizes. The Comprehensive Meta-Analysis (CMA) program was employed for data analysis. The findings revealed that the overall effect size was 0.84, implying a large effect size. Additionally, the mean effect sizes of the dependent variables revealed a large effect size for both the cognitive and affective domains. Furthermore, the study analyzed the impact of moderator variables such as sample scale, technology type, tool type, work type, program type, duration (sessions), the degree of immersion, instructional technique, and augmented reality (AR) type. Among the moderators, the degree of immersion was found to be statistically significant. In conclusion, the study results suggested that immersive learning technologies had a positive impact on learning in ELT.

• Journal of the Korean Institute of Rural Architecture
• /
• v.23 no.4
• /
• pp.1-12
• /
• 2021

Recently, the use of unmanned aerial vehicles (UAVs) is increasing in the field of land information acquisition and terrain exploration through high-altitude aerial photography. High-altitude aerial photography is suitable for large-scale geographic information collection, but has the disadvantage that it is difficult to accurately collect small-scale geographic information. Therefore, this study used low-altitude UAV to monitor changes in small rural spaces around rural resources, and the results are as follows. First, the low-altitude aerial imagery had a very high spatial resolution, so it was effective in reading and analyzing topographic features. Second, an area with a large number of aerial images and a complex topography had a large amount of point clouds to be extracted, and the number of point clouds affects the three-dimensional quality of rural space. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. In this study, the possibility of rural space analysis of low-altitude UAV was verified through aerial photography and analysis, and the effect of 3D mapping on rural space monitoring was visually analyzed. If data acquired by low-altitude UAV are used in various forms such as GIS analysis and topographic map production it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• 한국전산유체공학회:학술대회논문집
• /
• 2000.10a
• /
• pp.149-154
• /
• 2000

The flows through a turbomachinery tend to be extremely complex due to its inherent unsteady and viscous phenomena. A good analysis of the flows associated with rotor/stator interactions in turbomachinery will be great help in design stage. In this investigation, unsteady viscous flow structurts through one and half stage of UTRC large scale rotating axial turbine are analysed. The numerical data was compared with experimental data and showed good agreement.