• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.9-17
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• 2021

With the advancement of big data analysis, artificial intelligence, machine learning, etc., data analytics technology has developed to help with optimal decision-making. However, in certain areas, the lack of data restricts the use of these techniques. For example, real estate related data often have a long release cycle because of its recent release or being a non-liquid asset. In order to overcome these limitations, we studied the scalability of the existing time series through the TimeGAN model. A total of 45 time series related to weekly real estate data were collected within the period of 2012 to 2021, and a total of 15 final time series were selected by considering the correlation between the time series. As a result of data expansion through the TimeGAN model for the 15 time series, it was found that the statistical distribution between the real data and the extended data was similar through the PCA and t-SNE visualization algorithms.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.261-270
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• 2010

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional side bands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.217-223
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• 2012

By using the network, the robot can provide the anytime and anywhere various services. There is the advantage that it can provide the real time service by using the network description but the network robot has the network security vulnerability. Therefore, in the network robot environment, the authentication framework which can be satisfied the security function has to be established. In this paper, the security vulnerability which it can be generated in the network robot environment is analyze and the plan for reaction is prepared. And the authentication framework controlling the network robot safely was proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2166-2172
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• 2006

This paper presents a quality-of-service-enabled next generation local area network architecture which can provide efficiently convergence services over the Internet protocol. The basic concept of the architecture is to combine such three principle technologies as programmable switched network quality-of-service resource management and Internet protocol based network convergence. We discuss system entities and technologies development, which constitute the proposed network. The architecture of the network is then described. Implementation of systems verifies the proposed technologies. The network as a next generation local area network can provide quality-of-service-enabled real-time communication services as well as existing data traffic, and the open programmable interface can facilitates to adopt cost-effectively emerging new services or functionalities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2272-2281
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• 1997

This paepr proposes a shared medium access control protocol for hgih-speed multimedia services of distributed subscriber home and small-sized business ATM networks. This protocol offers not only global fairness for the whole network at the same time, but also local fairness for different prioritytraffics on each node. Considering that the future B-ISDN service si a mixture of real and non-real time traffic data, this protocol is designed to accommodate the real time service, by controlling the priority of the real and non-real time data. The simulation results show that the proposed protocol has better performance than the other protocols.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.147-152
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• 2016

This paper proposes a new TPC (Transmission Priority Change) algorithm which is used to diagnose failures of a CAN (Controller Area Network) based network system for the oil tank monitoring. The TPC algorithm is aimed to increase the total amount of data transmission and to minimize the latency for an urgent message by changing transmission priority. The urgency of the data transmission has been determined by the conditions of sensors. There are multiple sensors inside of the oil tank, such as temperature, valve, pressure and level sensors. When the sensors operate normally, the sensory data can be collected through the CAN network by the monitoring system. However when there is a dangerous situation or failure situation happened at a sensor, the data need to be handled quickly by the monitoring system, which is implemented by using the TPC algorithm. The effectiveness of the TPC algorithm has been verified by the real experiments. In addition, this paper introduces a method that people can figure out the condition of oil tanks and also can perform the fault diagnosis in real-time by using transmitted packet data. By applying this TPC algorithm to various industries, the convenience and reliability of multiple sensors network system can be improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2593-2600
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• 2010

A growth of mobile and wireless networking technologies have enabled mobile ad hoc networks applicable to a wide range of areas. This paper analyzes dynamics of network transport performance with respect to dynamics of network states especially for the mobile ad hoc networks called MANET. The edge cost based modeling methodology is adopted for the analysis, which can express well the characteristics of MANET. In this methodology the network state at arbitrary time can be specified as one of four edge states. We extracts ten target network scenarios for the simulation analysis by employing not only the Real Edge/Infinity Edge concept but also interworking functionality between different transport protocols. Then we could acquire from simulation of them with the DEVSim++ engine that the more sorts of transport protocols and the more number of interworking nodes are included in the network, the more contribution is for improving network transport performance.

• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.433-442
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• 2005

An increase In traffic has a large Influence on the performance of a total network. Therefore, traffic management has become an important issue of network management. In this paper, we propose a new routing algorithm that attempts to analyze network conditions using time series prediction models and to propose predictive optimal routing decisions. Traffic congestion is assumed when the predicting result is bigger than the permitted bandwidth. By collecting traffic in real network, the predictable model is obtained when it minimizes statistical errors. In order to predict network traffic based on time series models, we assume that models satisfy a stationary assumption. The stationary assumption can be evaluated by using ACF(Auto Correlation Function) and PACF(Partial Auto Correlation Function). We can obtain the result of these two functions when it satisfies the stationary assumption. We modify routing oaths by predicting traffic in order to avoid traffic congestion through experiments. As a result, Predicting traffic and balancing load by modifying paths allows us to avoid path congestion and increase network performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Smart Structures and Systems
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• v.16 no.5
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• pp.873-889
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• 2015

In civil engineering, probabilistic seismic risk assessment is used to predict the economic damage to a lifeline system of possible future earthquakes. The results are used to plan mitigation measures and to strengthen the structures where necessary. Instead, after an earthquake public authorities need mathematical models that compute: the damage caused by the earthquake to the individual vulnerable components and links, and the global behavior of the lifeline system. In this study, a framework that was developed and used for prediction purpose is modified to assess the consequences of an earthquake in quasi real-time after such earthquake happened. This is possible because nowadays entire seismic regions are instrumented with tight networks of strong motion stations, which provide and broadcast accurate intensity measure maps of the event to the public within minutes. The framework uses the broadcasted map and calculates the damage to the lifeline system and its component in quasi real-time. The results give the authorities the most likely status of the system. This helps emergency personnel to deal with the damage and to prioritize visual inspections and repairs. A highway transportation network is used as a test bed but any lifeline system can be analyzed.