• Journal of Navigation and Port Research
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• v.32 no.8
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• pp.611-619
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• 2008

The Ministry of Land, Transport and Maritime Affairs is working on the construction of Nationwide DGPS(NDGPS) with connection to Maritime DGPS Reference Stations and if Chun-cheon Reference Station is to be completed in 2008, DGPS positioning information is available in the whole area of Republic of Korea. Therefore to promote the usage of DGPS surveying information, we measured and panalyzed the accuracy of DGPS. In real-time DGPS positioning accuracy were 0.42m of planar Root Mean Square(RMS) error in static survey and 0.48m of planar RMS error in dynamic survey. We went abreast with RTK comparison measurement. According to these results. DGPS positioning information cannot be applied directly to the GIS construction field, but GIS application fields, requiring the real-time positioning information. can take advantage of it in variable cases.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.33-47
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• 2018

City gas pipelines are buried underground. Because of this, pipeline is hard to manage, and can be easily damaged. This research proposes a real time prediction system that helps experts can make decision about pressure anomalies. The gas pipline pressure data of Jungbu City Gas Company, which is one of the domestic city gas suppliers, time variables and environment variables are analysed. In this research, regression models that predicts pipeline pressure in minutes are proposed. Random forest, support vector regression (SVR), long-short term memory (LSTM) algorithms are used to build pressure prediction models. A comparison of pressure prediction models' preformances shows that the LSTM model was the best. LSTM model for Asan-si have root mean square error (RMSE) 0.011, mean absolute percentage error (MAPE) 0.494. LSTM model for Cheonan-si have RMSE 0.015, MAPE 0.668.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.285-289
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• 2004

Recently, due to the high development of the internet, needs for multimedia streams such as digital audio and video is increasing much more. In case of transmitting multimedia streams using the User Datagram Protocol (UDP), it may cause starvation of TCP traffic on the same transmission path, thus resulting in congestion collapse and enormous delay because UDP does not perform TCP-like congestion control. Because of this problem, diverse researches are being conducted on new transmission schemes and protocols intended to efficiently reduce the transmission delay of real-time multimedia streams and perform congestion control. The TCP-friendly congestion control schemes can be classified into the window-based congestion control, which uses the general congestion window management function, and the rate-based congestion control, which dynamically adjusts transmission rate by using TCP modeling equations and the like. In this paper, we suggest the square-root congestion avoidance algorithm with the hybrid TCP-friendly congestion control scheme which the window-based and rate-based congestion controls are dealt with in a combined way. We apply the proposed algorithm to the existing TEAR. We simulate the performance of the proposed TEAR by using NS, and the result shows that it gives better improvement in the stability needed for providing congestion control than the existing TEAR.

• Earthquakes and Structures
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• v.15 no.6
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• pp.595-603
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• 2018

Shake table testing has been regarded as one of the most effective experimental approaches to evaluate seismic response of structural systems subjected to earthquakes. However, reproducing a prescribed acceleration time history precisely over the frequency of interest is challenging because shake table test systems are eventually nonlinear by nature. In addition, interaction between the table and specimen could affect the control accuracy of shake table testing significantly. Various novel control algorithms have been proposed to improve the control accuracy of shake table testing; however, reference values for control performance assessment remain rare. In this study, reference values for control performance assessment of shake table testing are specified based on the statistical analyses of 1,209 experimental data provided by the Seismic Simulator Laboratory of National Center for Research on Earthquake Engineering in Taiwan. Three individual reference values are considered for the assessment including the root-mean-square error of the achieved acceleration time history; the percentage of the spectral acceleration that exceeds the determined tolerance range over the frequency of interest; and the error-ratio of the achieved peak ground acceleration. Quartiles of the real experimental data in terms of the three objective variables are obtained, providing users with solid and simple references to evaluate the control performance of shake table testing. Finally, a set of experimental data of a newly developed control framework implementation for uni-axial shake tables are used as an application example to demonstrate the significant improvement of control accuracy according to the reference values provided in this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.494-500
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• 2020

This paper proposes a new distance estimation technique for indoor localization in ultra wideband (UWB) systems. The proposed technique is based on recurrent neural network (RNN), one of the deep learning methods. The RNN is known to be useful to deal with time series data, and since UWB signals can be seen as a time series data, RNN is employed in this paper. Specifically, the transmitted UWB signal passes through IEEE802.15.4a indoor channel model, and from the received signal, the RNN regressor is trained to estimate the distance from the transmitter to the receiver. To verify the performance of the trained RNN regressor, new received UWB signals are used and the conventional threshold based technique is also compared. For the performance measure, root mean square error (RMSE) is assessed. According to the computer simulation results, the proposed distance estimator is always much better than the conventional technique in all signal-to-noise ratios and distances between the transmitter and the receiver.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.383-390
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• 2024

When measuring the radiated noise of an underwater vehicle, the range information between the vehicle and the receiver is an important factor, but since Global Positioning System (GPS) is not available in underwater, an alternative method is needed. As an alternative, the range is measured by estimating the arrival time, arrival time difference, and arrival frequency difference using a separate acoustic signal. However, errors occur due to the channel environment, and these outliers become obstacles in continuously measuring range. In this paper, we propose a method to reduce errors by curve fitting with a function in the form of a V-curve as a post-processing to remove outliers that occurred in the process of measuring range information. Simulation, lake and sea trials were conducted to verify the performance of the proposed method. In the results of the lake trial, the range estimation error was reduced by about 85 % from the Root Mean Square Error (RMSE) point of view.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.182-187
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• 2017

Synchronous generators have been significantly applied in large-scale power plants and its monitoring systems are additionally established to sequentially observe states and outputs. We develop a computer based monitoring device for three-phase synchronous power generators in this paper. First, a test-bed of such generator system is created and then a interface board is constructed to transfer electric signals including the output voltage and the current from generators into a computer system via a data acquisition device. Its RMS(root-mean-square) values are continuously shown on a screen of computer systems and its time-histories graphs are additionally illustrated under a graphic user interface(GUI) mode. Lastly, we carry out real-time experiments using the generator system with the monitoring device to demonstrate its reliability and superiority by comparing results of a generic power analyzer which is well-used in measuring various power systems practically.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.419-430
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• 2014

An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.346-350
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• 2007

Almost all network systems provide an authentication mechanism based on user ID and password. In such system, it is easy to obtain the user password using a sniffer program with illegal eavesdropping. The one-time password and challenge-response method are useful authentication schemes that protect the user passwords against eavesdropping. In client/server environments, the one-time password scheme using time is especially useful because it solves the synchronization problem. It is the stability that is based on Square Root Problem, and we would like to suggest PBSI(Password Based Secure Identification), enhancing the stability, for all of the well-known attacks by now including Off-line dictionary attack, password file compromise, Server and so on. The PBSI is also excellent in the aspect of the performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2075-2083
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• 2016

The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).