• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.16-20
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• 2010

Recently, the smart grid has become a hot issue and interest in related power sources have increased accordingly. The implementation of a smart grid can enable many generation resources to be linked to the power system, including small-scale reactors for the purpose of co-generation. Research on small-scale reactors is being carried out all over the world. Similarly, Korea is also conducting research on multi-purpose regional energy systems using nuclear energy. This paper proposes a real-time data acquisition and analysis system for small-scale reactors, and is known as the REX-10 (Regional Energy rX 10 MVA). This analysis requires real-time simulations for the power system since it needs data communication with a remote REX-10. A RTDS (Real Time Digital Simulator) has been used for the simulation, and a SCADA/HMI system interfaced with the RTDS is proposed for the purpose of monitoring and control of the regional energy system.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.86-94
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• 2018

This study focuses on presenting the IT program module provided by real - time forecasting and database of the voluntary disclosure quality measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. This study suggests a model of the algorithm that the quality of real - time voluntary disclosure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.251-257
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• 2012

Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1682-1692
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• 2021

Digital Twin, one of the core technologies of the Fourth Industrial Revolution, is attracting attention as a very suitable technology for disaster monitoring such as fires and earthquakes. In this paper, we implement a system equipped with UWB RTLS(Ultra-Wideband Real Time Location System), real-time remote control, and video streaming, which are element technologies for disaster monitoring digital twin. Since the proposed system structure is based on a cloud server, the actual location of the UWB indoor positioning-based client is transmitted to the user device in real time and stored on the cloud server for statistical and data analysis. In addition, we demonstrate through experiments that outliers occurs when the value of RSSI(Received Signal Strength Indicator) decreases due to communication collisions between UWB Tags, and propose an RSSI outlier correction algorithm to solve this problem.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.61.2-61
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• 2001

The purpose of the initial alignment of a SDINS is to get a coordinate transformation matrix from the body frame to the navigation frame. The initial alignment is one of the most important processes in the navigation system since its error has a large influence on the navigation solution. In this paper, a real-time initial alignment algorithm for the SDINS is developed using the Kalman filter. The steady state error analysis is performed for the developed Kalman filter technique and the gyrocompass loop method. The performance of the developed alignment method is compared with the gyrocompass loop method through the real-time alignment experiments.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.215-217
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• 2005

There are two types of packet loss probabilities used in both the network layer and the physical layer within the wireless transmitter such as a queueing discard probability and transmission loss probability. We analyze these loss performances in order to guarantee Quality of Service (QoS) which is the basic of the future network. The queuing loss probability is caused by a maximum allowable delay time and the transmission loss probability is caused by a wireless channel error. These two types of packet loss probabilities are not easily analyzed due to recursive feedback which, originates as a result at a queueing delay and a number of retransmission attempts. We consider a wireless transmitter to a M/D/1 queueing model. We configurate the model to have a finite-size FIFO buffer in order to analyze the real-time traffic streams. Then we present the approaches used for evaluating the loss probabilities of this M/D/1/K queueing model. To analyze the two types of probabilities which have mutual feedbacks with each other, we drive the solutions recursively. The validity and accuracy of the analysis are confirmed by the computer simulation. From the following solutions, we suggest a minimum of 'a Maximum Allowable Delay Time' for real-time traffic in order to initially guarantee the QoS. Finally, we analyze the required service rate for each type utilizing real-time traffic and we apply our valuable analysis to a N-user's wireless network in order to get the fundamental information (types of supportable real-type traffics, types of supportable QoS, supportable maximum number of users) for network design.

• Fourth Industrial Review
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• v.3 no.1
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• pp.13-20
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• 2023

Purpose - By designing a PEF(Personalized Education Feedback) system for real-time prediction of learning achievement and motivation through real-time EEG analysis of learners, this system provides some modules of a personalized adaptive learning system. By applying these modules to e-learning and offline learning, they motivate learners and improve the quality of learning progress and effective learning outcomes can be achieved for immersive self-directed learning Research design, data, and methodology - EEG data were collected simultaneously as the English test was given to the experimenters, and the correlation between the correct answer result and the EEG data was learned with a machine learning algorithm and the predictive model was evaluated.. Result - In model performance evaluation, both artificial neural networks(ANNs) and support vector machines(SVMs) showed high accuracy of more than 91%. Conclusion - This research provides some modules of personalized adaptive learning systems that can more efficiently complete by designing a PEF system for real-time learning achievement prediction and learning motivation through an adaptive learning system based on real-time EEG analysis of learners. The implication of this initial research is to verify hypothetical situations for the development of an adaptive learning system through EEG analysis-based learning achievement prediction.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.32-32
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• 2011

Plasma etching is used in microelectronic processing for patterning of micro- and nano-scale devices. Commonly, optical emission spectroscopy (OES) is widely used for real-time endpoint detection for plasma etching. However, if the viewport for optical-emission monitoring becomes blurred by polymer film due to prolonged use of the etching system, optical-emission monitoring becomes impossible. In addition, when the exposed area ratio on the wafer is small, changes in the optical emission are so slight that it is almost impossible to detect the endpoint of etching. For this reason, as a simple method of detecting variations in plasma without contamination of the reaction chamber at low cost, a method of measuring plasma impedance is being examined. The object in this research is to investigate the suitability of using plasma impedance monitoring (PIM) with statistical approach for real-time endpoint detection of $SiO_2$ etching. The endpoint was determined by impedance signal variation from I-V monitor (VI probe). However, the signal variation at the endpoint is too weak to determine endpoint when $SiO_2$ film on Si wafer is etched by fluorocarbon plasma on inductive coupled plasma (ICP) etcher. Therefore, modified principal component analysis (mPCA) is applied to them for increasing sensitivity. For verifying this method, detected endpoint from impedance analysis is compared with optical emission spectroscopy (OES). From impedance data, we tried to analyze physical properties of plasma, and real-time endpoint detection can be achieved.

• Structural Engineering and Mechanics
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• v.6 no.3
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• pp.275-289
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• 1998

The objective of the paper is to present a method whereby the time required for a steel structure to sustain the effects of a prescribed temperature rise according to real fire curves can be calculated. The method is divided into two parts. The first part deals with the post-yield behaviour of steel structures at elevated temperatures. It takes into account the variation of the properties of steel material with temperature in an incremental elastoplastic analysis so that the safety factor of the structure under certain fire conditions can be assessed. The second part deals with the heat transfer problem of bare steel members in real fire. Factors affecting the heat transfer process are examined and a model for predicting the temperature variation with time under real fire conditions is proposed. This model results in more accurate temperature predictions for steel members than those obtained from previously adopted model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.123-129
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• 2013

The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.