• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.21-30
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• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.691-695
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• 2023

Currently, the utilization of measurement results of the automated measurement system is very low and is at the level of providing only fragmentary measurement results. In this study, we are going to study a structure behavior analysis 3D display system with high precision and reliability for automated measurement data obtained by constructing big data by transmitting massive data values measured in real time to the cloud and using a Python-based algorithm. As a result of the study, as a system that can evaluate the behavior of a structure to a manager in real time, it provides analysis data in real time without significant restrictions regardless of the type of measurement data and sensor, and derived it as a 3D display. In addition, it was analyzed that the manager could grasp the behavior graph of the structure in real time and more easily judge the derivation of the weak part of the structure through data analysis. In the future, by analyzing the behavior of structures in three dimensions using past and present data, it is expected that more effective measurement results can be obtained in terms of repair, reinforcement, and maintenance of realistic structures.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.443-450
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• 2011

The Internet has become an essential part in our modern life by providing useful information. So, the volume of Internet traffic has been increasing rapidly, which emphasizes the importance of network traffic analysis for effective network operation and management. Signature based analysis have been commonly used, but it is shown that the increase of signatures due to the increase of applications causes the performance degradation of real-time traffic analysis on high-speed network links. In this paper, we propose OS fingerprinting method for real-time traffic analysis. The previous problems can be solved by utilizing the OS information. The OS fingerprinting method for real-time traffic analysis, proposed in this paper, conducts under passive mode, and improves the limitation of a previous method such as low completeness and accuracy. In this paper, we enlarged an input data to improve completeness, and used the User-Agent field in HTTP packet to extract various OS signatures. Also, we changed an input data from packet to flow to improve accuracy.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.77-89
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• 2023

This study aims to establish the correlations between variables related to a slope during rainfall and factor of safety (FOS) and displacement using a coupling analysis method that is designed to consider both in rainfall conditions. With the recent development of measurement technologies, the approach of using the measurement data in the field has become easier. Particularly, they have been obtained in tests to determine the real-time safety and movement of a slope; however, a specific method has not been finalized. In addition, collected measurement data for recognizing the FOS and displacement in real-time with a specific relevance is difficult, and risks of uncertainty, such as in soil parameters and time, exist. In this study, the correlations between various slope-related variables (i.e., rainfall intensity, rainfall duration, angle of the slope, and mechanical properties including strength parameters of selected three types of soil; loamy sand, silt loam, sand) and the FOS and displacement are analyzed in order of seepage analysis, slope stability analysis and slope displacement analysis. Moreover, the methodology of coupling analysis is verified and a fundamental understanding of the factors that need to be considered in real-time observations is gained. The results show that the contributions of the abovementioned variables vary according to the soil type. Thus, the tendency of the displacement also differs by the soil type and variables but not same tendency with FOS. The friction angle and cohesion are negative while the rainfall duration and rainfall intensity are positive with the displacement. This suggests that understanding their correlations is necessary to determine the safety of a slope in real-time using displacement data. Additionally, databases considering rainfall conditions and a wide range of soil characteristics, including hydraulic and mechanical parameters, should be accumulated.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1197-1220
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• 2014

Accurate actuator tracking is critical to achieve reliable real-time hybrid simulation results for earthquake engineering research. The frequency-domain evaluation approach provides an innovative way for more quantitative post-simulation evaluation of actuator tracking errors compared with existing time domain based techniques. Utilizing the Fast Fourier Transform the approach analyzes the actuator error in terms of amplitude and phrase errors. Existing application of the approach requires using the complete length of the experimental data. To improve the computational efficiency, two techniques including data decimation and frequency decimation are analyzed to reduce the amount of data involved in the frequency-domain evaluation. The presented study aims to enhance the computational efficiency of the approach in order to utilize it for future on-line actuator tracking evaluation. Both computational simulation and laboratory experimental results are analyzed and recommendations on the two decimation factors are provided based on the findings from this study.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.371-381
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• 2017

There has never been research on Chaos analysis using real estate auction sale price rate in Korea. In this study, three Chaos analysis methodologies - Hurst exponent, correlation dimension, and maximum Lyapunov exponent - in order to capture the nonlinear deterministic dynamic system characteristics. High level of Hurst exponent and the extremely low maximum Lyapunov exponent provide the tendency and the persistence of the data. The empirical results give two meaningful facts. First, monthly time lags of the correlation dimension are coincident with the time period from the approval auction start day to the sale price fixing day. Second, its weekly time lags correspond to the time period from the last day of request for sale price allocation to the sale price fixing day. Then, this study potentially examines the predictability of the real estate auction price rate time series.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.292-298
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• 2012

It is a real-time system that the system correctness depends not only on the correctness of the logical result of the computation but also on the result delivery time. Real-time Operating System (RTOS) is a software that manages the time of a microprocessor to ensure that the most important code runs first so that it is a good building block to design the real-time system. The real-time performance is achieved by using real-time mechanisms through data communication and synchronization of inter-task communication (ITC) between tasks. Therefore, test on the response time of real-time mechanisms is a good measure to predict the performance of real-time systems. This paper aims to analysis the response characteristics of real-time mechanisms in kernel space for real-time embedded Linux: RTAI and Xenomai. The performance evaluations of real-time mechanism depending on the changes of task periods are conducted. Test metrics are jitter of periodic tasks and response time of real-time mechanisms including semaphore, real-time FIFO, Mailbox and Message queue. The periodicity of tasks is relatively consistent for Xenomai but RTAI reveals smaller jitter as an average result. As for real-time mechanisms, semaphore and message transfer mechanism of Xenomai has a superior response to estimate deterministic real-time task execution. But real-time FIFO in RTAI shows faster response. The results are promising to estimate deterministic real-time task execution in implementing real-time systems using real-time embedded Linux.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.2-129
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• 2001

Visual effects are important cues for providing occupant s with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant´s posture, therefore, the total body motion must be considered in a graphic simulator. A real time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and acceleration. A multibody system analysis software, MADYMO, was used in the motion analysis of an adult male dummy in the seated position. Position data of the head were collected as inputs to the viewpoint movement. Based on these data, a back- propagation neural network was ...

• The Journal of Information Systems
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• v.22 no.3
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• pp.25-42
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• 2013

Recently various kinds of Information Technology services are created and the quantities of the data flow are increase rapidly. Not only that, but the data patterns that we deal with also slowly becoming diversity. As a result, the demand of discover the meaningful knowledge/information through the various mining analysis such as linkage analysis, sequencing analysis, classification and prediction, has been steadily increasing. However, solving the business problems using data mining analysis does not always concerning, one of the major causes of these limitations is there are some analyzed data can't accurately reflect the real world phenomenon. For example, although the time gap of purchasing the two products is very short, by using the traditional sequencing analysis, the precedence relationship of the two products is clearly reflected. But in the real world, with the very short time interval, the precedence relationship of the two purchases might not be defined. What was worse, the sequence of the purchase intention and the sequence of the purchase realization of the two products might be mutually be reversed. Therefore, in this study, an expanded sequencing analysis methodology has been proposed in order to reflect this situation. In this proposed methodology, the purchases that being made in a very short time interval among the purchase order which might not important will be notice, and the analysis which included the original sequence and reversed sequence will be used to extend the analysis of the data. Also, to some extent a very short time interval can be defined as the time interval, so an experiment were carried out to determine the varying based on the time interval for the actual data.

• Journal of Electrochemical Science and Technology
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• v.3 no.4
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• pp.154-158
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• 2012

It is generally known that electrochemical impedance spectroscopy is a powerful technique and its real-time application has been demanded for prompt observations on instantaneous electrochemical changes. Nevertheless, long measurement time and laborious analysis procedures have hindered development of it. Solving the problems, here I report of a new algorithm design for development of a real-time electrochemical impedance monitoring system, which potentially provides a guideline in developing monitoring systems of electric vehicles batteries and other electrochemical power plants. The significant progress in this report is employment of the parallel processing protocol which connects independent sub functions to successfully operate with avoiding mutual interruptions. Therefore, all the processes required to monitor electrochemical impedance changes in realtime are properly operated. To realize the conceptual scheme, a Labview program was coded with sub functions units which conduct their processes individually and only data are transferred between them through the parallel pipelines. Finally, measured impedance spectra and analysis results are displayed, which are synchronized according to the time of change.