• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.693-701
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• 2002

In this study, one dimensional sediment movement numerical model(HEC-6) and semi-two dimensional sediment movement numerical model(GSTARS 2.1) were applied to solve the change of channel geometry in Bocheong stream. GSTARS 2.1 model was applied for the three selected sediment transport formulas(Ackers and White's, Engelund and Hanson, Yang formula) from 1993 to 2000 measured data on each section. The simulation results of Ackers and White formula for long -term bed changes are good when compared to the measured data. The HEC-6 model was applied for the simulation of one dimensional sediment movement for the same period. Comparison of the long-term simulations by GSTARS 2.1 and HEC-6 models with measured data shows that simulations by both models are in fair agreement with measured data in overall trend of the river bed changes. Comparisons of simulated cross sectional bed-elevations with measured data shows that GSTARS 2.1 model gives better agreement with than simulated results bed changes on the HEC-6 model.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.94-101
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• 1994

This paper describes a short-term prediction model for the movement of an oil slick in shallow waters. Under the assumption that the initial movement of the oil slick is governed by spreading and advection, the model has been developed and applied to Kyungki-Bay near Incheon Harbor. The initial spreading is estimated by using an empirical formula. The depth-averaged momentum equations are solved numerically for the volume transport velocities, in which the $M_2$ tide is the main driving source. A staggered grid system is adopted fur spatial discretization and the half-time method is implemented for time marching. The numerical result is visualized with the help of animation and thus the contaminated area is displayed on a monitor in time sequence. The input data are the time, the location and the volume of spill accident as well as environmental data such as md and $M_2$ tide.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.53-60
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• 2006

Handover of WiBro is based on 802.16e hard handover scheme. When PSS is handover, it is handover that confirm neighbor's cell condition and RAS ID in neighbor advertisement message. Serving RAS transmits HO-notification message to neighbor RAS. Transmiting HO-notification message to neighbor RAS, it occurs many signaling traffics. Also, When WiBro is handover, It occurs many packet loss. Therefore, user suffer service degradation. LPM handover is supporting seamless handover because it buffers data packets during handover. So It is proposed scheme that predicts is LPM handover and reserves target RAS with pre-authentication. These schemes occur many signaling traffics. In this paper, we propose PSS Movement Prediction to solve signaling traffic. Target RAS is decided by old data in history cache. When serving RAS receives HO-notification-RSP message to target RAS, target RAS inform to crossover node. And crossover node bicast data packet. If handover is over, target RAS forward data packet. Therefore, It reduces signaling traffics but increase handover success rate. When history cache success, It decrease about 48% total traffic. But When history cache fails, It increase about 6% total traffic

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.37-39
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• 2000

The purpose of this paper is to present a neural network model based on change-point detection for the prediction of the U.S. Treasury Securities. Interest rates have been studied by a number of researchers since they strongly affect other economic and financial parameters. Contrary to other chaotic financial data, the movement of interest rates has a series of change points due to the monetary policy of the U.S. government. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in interest rates forecasting. The proposed model consists of three stages. The first stage is to detect successive change points in the interest rates dataset. The second stage is to forecast the change-point group with the backpropagation neural network (BPN). The final stage is to forecast the output with BPN. This study then examines the predictability of the integrated neural network model for interest rates forecasting using change-point detection.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1075-1088
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• 2001

In this paper, we propose a method for dynamic selection of unrestricted motion vector(UMV) or default prediction mode(DPM) in H.263 bit stream. For this, we use the error of compensated image and the magnitude of motion vector. In the proposed strategy, the UMV mode is dynamically applied in a frame according to average magnitude of motion vector and error of compensated image. This scheme has improved the quality of image compared to the fixed mode UMV or DPM only. Number of searching points are greatly reduced when comparing to UMV The proposed method is more profitable to long video sequences having camera movement locally.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.4
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• pp.383-390
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• 2000

The purpose of this study was to compare the soft tissue movements in facial profile predicted by a computer package with those that had actually accured following a sagittal split ramal osteotomy. The reliability of predicting the results of orthodontic surgical treatment was analysed. The study was based on the serial records of 30 consecutive patients who had been treated by means of a sagittal split ramal osteotomy. The serial lateral cephalometric radiographs used for the study were taken at the following stages: immediate preoperative : immediate postoperative : 6 months postoperative. A superimposition T1, T2-3 was generated to allow visual comparision. The results can be considered in relation to four important parts of the facial profile :the nose, upper lip, lower lip, and chin. The nose & Upper lip:The amount of movement of the upper lipwas not badly predicted for the average case. The lower lip: There was a significant trend over the whole sample for vertical positionof the lower lip to be less well predicted. The chin: The soft tissue movements of the chin were well predicted.

• Journal of ILASS-Korea
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• v.16 no.2
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• pp.69-75
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• 2011

This article presents computational fluid dynamics (CFD) simulations of sub-micron particle movements and flow characteristics in laboratory-scale electrostatic precipitator (ESP) without corona discharge, and for simulation, it uses the commercial CFD program (CFD-ACE) including electrostatic theory and Lagrangian-based equation for sub-micron particle movement. For validation of CFD results, a simple cylindrical type of ESP is simulated and numerical prediction shows fairly good agreement with the analytical solution. In particular, the present study investigates the effect of particle diameter, inlet flow rate, and applied electric potential on particle collection efficiency and compares the numerical prediction with the experimental data, showing good agreement. It is found that the particle collection efficiency decreases with increasing inlet flow rate because the particle detention time becomes shorter, whereas it decreases with the increase in sub-micron particle diameter and with the decrease of applied electric voltage resulting from smaller terminal electrostatic velocity.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1107-1115
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• 2016

Efficient Market Hypothesis (EMH), states that at any point in time in a liquid market security prices fully reflect all available information. This paper presents a study of proving the hypothesis through daily Twitter sentiments using the hybrid approach of the lexicon-based approach and the naïve Bayes classifier. In this research we analyze the currency exchange rate movement of Indonesia Rupiah vs US dollar as a way of testing the Efficient Market Hypothesis. In order to find a correlation between the prediction sentiments from Twitter data and the actual currency exchange rate trends we collect Twitter data every day and compute the overall sentiment to label them as positive or negative. Experimental results have shown 69% correct prediction of sentiment analysis and 65.7% correlation with positive sentiments. This implies that EMH is semi-strong Efficient Market Hypothesis, and that public information provide by Twitter sentiment correlate with changes in the exchange market trends.

• Tribology and Lubricants
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• v.25 no.4
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• pp.256-260
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• 2009

Fretting is a kind of wear which effects on reliability and durability. When machine parts are joined joint in parts such as a bolt or a rivet or a pin, fretting phenomenon is occurred by micro relative movement. When fretting occurs in joint parts, there is wear which is the cause of fatigue crack. Recently, although the ways of assessment of fatigue and damage tolerance are established, there is no way to evaluate fatigue crack initiation life by fretting phenomenon. Consequently, the prediction of life and prevention plan caused by fretting are needed to improve reliability. The objective of this paper is to predict fretting wear by using a experimental method and contact analysis considering wear process. For prediction of fretting wear volume, systematic and controlled experiments with a disc-plate contact under gross slip fretting conditions were carried out. A modified Archard equation is used to calculate wear depths from the contact pressure and stroke using wear coefficients obtained from the disc-plate fretting tests.