• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.4
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• pp.4232-4241
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• 1976

This study was carried out to clarify the stochastic characteristics of monthly rainfalls and to select a proper model for generating the sequential monthly rainfall amounts. The results abtained are as follows: 1. Log-Normal distribution function is the best fit theoretical distribution function to the empirical distribution of monthly rainfall amounts. 2. Seasonal and random components are found to exist in the time series of monthly rainfall amounts and non-stationarity is shown from the correlograms. 3. The Monte Carlo model shows a tendency to underestimate the mean values and standard deviations of monthly rainfall amounts. 4. The 1st order Markov model reproduces means, standard deviations, and coefficient of skewness with an error of ten percent or less. 5. A correlogram derived from the data generated by 1st order Markov model shows the charaterstics of historical data exactly. 6. It is concluded that the 1st order Markov model is superior to the Monte Carlo model in their reproducing ability of stochastic properties of monthly rainfall amounts.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.560-566
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• 2008

Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.285-294
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• 2018

In this study, we implemented the data quality monitoring algorithm which is the previous step for real-time Global Navigation Satellite System (GNSS) correction generation and compared Global Positioning System (GPS) and BeiDou System (BDS). Signal Quality Monitoring (SQM), Data QM, and Measurement QM (MQM) that are well known in Ground Based Augmentation System (GBAS) were used for quality monitoring. SQM and Carrier Acceleration Ramp Step Test (CARST) of MQM result were divided by satellite elevation angle and analyzed. The data which are judged as abnormal are removed and presented as Root Mean Square (RMS), standard deviation, average, maximum, and minimum value.

• Earthquakes and Structures
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• v.8 no.6
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• pp.1463-1480
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• 2015

This research aims to develop an empirical model for simulation of time-varying frequency in earthquake ground motion so as to be used easily in engineering applications. Briefly, 10545 recordings of the Next Generation Attenuation (NGA) global database of accelerograms from shallow crustal earthquakes are selected and binned by magnitude, distance and site condition. Then the wavelet spectrum of each acceleration record is calculated by using one-dimensional continuous wavelet transform, and the frequencies corresponding to the maximum values of the wavelet spectrum at a series of sampling time, named predominant frequencies, are extracted to analyze the variation of frequency content of seismic ground motions in time. And the time-variation of the predominant frequencies of 178 magnitude-distance-site bins for different directions are obtained by calculating the mean square root of predominant frequencies within a bin. The exponential trigonometric function is then use to fit the data, which describes the predominant frequency of ground-motion as a function of time with model parameters given in tables for different magnitude, distance, site conditions and direction. Finally, a practical frequency-dependent amplitude envelope function is developed based on the time-varying frequency derived in this paper, which has clear statistical parameters and can emphasize the effect of low-frequency components on later seismic action. The results illustrate that the time-varying predominant frequency can preferably reflect the non-stationarity of the frequency content in earthquake ground motions and that empirical models given in this paper facilitates the simulation of ground motions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.1-13
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• 2020

There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering "demand spike" during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

• Wind and Structures
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• v.25 no.6
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• pp.569-588
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• 2017

The aim of this paper is to present a method to obtain the dynamic response of a wind turbine tower in time domain by means of the generation of time series and to estimate the associated fatigue damage by means of a Rainflow counting algorithm. The proposed method is based on assuming the vortex shedding is a bidimensional phenomena and on following a classical modal superposition method to obtain the structure dynamic response. Four different wind turbine tower geometric configurations have been analyzed in a range of usual wind velocities and covering extreme wind velocities. The obtained results have shown that, depending on the turbulence intensity and the mean wind velocity, there are tower geometric configurations more advantageous from the fatigue load standpoint. Consequently, the presented model can be utilized to define assembly strategies oriented to fatigue damage minimization.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.622-632
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• 1995

The present numerical study is aimed to investigate time-dependent characteristics of a two-dimensional lid-driven square cavity flow of three high Reynolds numbers, $7.5{\times}10^3$, $10^4$ and $3{\times}10^4$. A conservative convection term on irregular grids was adopted by renewing the MAC type difference schemes on regular grids. Relaxation of velocity and pressure is implemented by SOLA algorithm. In case of $Re=7.5{\times}10^3$, flow behavior converges to steady state after a transient period. But for $Re=10^4$, periodic unsteady sinusoidal fluctuation of local velocity and kinetic energy is found and continuous movements of small eddies in the secondary flow regions are also discovered. Random generation of eddies and their active migrating behavior are detected for $Re=3{\times}10^4$, resulting in complete unsteady and non-linear flow characteristics. And, an organized structure similar to a Moffat vortex is also observed from the time-mean flow patterns. Furthermore, a typoon-like vortex(TLV) appears intemittently and rotates along the separation regions and boundary layers.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.345-351
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• 2006

Software-In-the-Loop Simulation(SILS) and Rapid Control Prototyping(RCP) are proposed as an integrated development environment to support the development process from system design to implementation. SILS is an environment used to simulate control systems with temporal behavior. RCP offers seamless phase shift from design to implementation based on automatic code generation. There are several toolsets that support control system design and analysis. A few of these tools generate the control software automatically. However, most of these design toolsets do not cover temporal behavior which appears after implementation. In earlier toolsets, the design and the implementation of a control system are considered as two separate processes which mean the conventional development process is not connected strictly. SILS/RCP environments work under an identical platform and use the same representation for system modeling. An integrated SILS/RCP environment makes it possible to design controllers under conditions similar to real execution during off-line simulation and to realize controllers in the early design phase. SILS/RCP environments integrate the design and implementation phases which reduce the time-to-market and provide greater performance-assured design. The establishment of SILS/RCP and the practical design approaches are presented.

• Korean Journal of Mathematics
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• v.30 no.1
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• pp.67-72
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• 2022

For a locus with two alleles (I^A and I^B), the frequencies of the alleles are represented by $$p=f(I^A)={\frac{2N_{AA}+N_{AB}}{2N},\;q=f(I^B)={\frac{2N_{BB}+N_{AB}}{2N}$$ where N_AA, N_AB and N_BB are the numbers of I^AI^A, I^AI^B and I^BI^B respectively and N is the total number of populations. The frequencies of the genotypes expected are calculated by using p², 2pq and q². Choi showed the method of whether some genotypes is in these probabalities. Also he calculate the probability generating function for offspring number of genotype under a diploid model( [1]). In this paper, let x(t, p) be the probability that I^A become fixed in the population by time t-th generation, given that its initial frequency at time t = 0 is p. We find adapted equations for x using the mean change of frequence of alleles and fitness of genotype. Also we apply this adapted equations to several diploid model and it also will apply to actual examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1369-1389
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• 2024

In the era of 6G, the rapid increase in communication data volume poses higher demands on traditional channel estimation techniques and those based on deep learning, especially when processing large-scale data as their computational load and real-time performance often fail to meet practical requirements. To overcome this bottleneck, this paper introduces quantum computing techniques, exploring for the first time the application of Quantum Generative Adversarial Networks (QGAN) to broadband channel estimation challenges. Although generative adversarial technology has been applied to channel estimation, obtaining instantaneous channel information remains a significant challenge. To address the issue of instantaneous channel estimation, this paper proposes an innovative QGAN with a dual-module design in the generator. The adversarial loss function and the Mean Squared Error (MSE) loss function are separately applied for the parameter updates of these two modules, facilitating the learning of statistical channel information and the generation of instantaneous channel details. Experimental results demonstrate the efficiency and accuracy of the proposed dual-module QGAN technique in channel estimation on the Pennylane quantum computing simulation platform. This research opens a new direction for physical layer techniques in wireless communication and offers expanded possibilities for the future development of wireless communication technologies.