• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1465-1474
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• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• ETRI Journal
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• v.42 no.6
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• pp.815-826
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• 2020

We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.157-164
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• 2005

Two methods, the bin averaging method and least square method, are often used in calibrating wind turbine test sites. The objective of this work was to determine a better method to predict the wind speed at wind turbine installing point. The calibration was done at the test site on a complex terrain located in Daegwallyeong, Korea. It was performed for two different cases based on the IEC 61400-12 power performance measurement standard. The wind speeds averaged for 10 minutes ranged between 4 m/s and 16 m/s. The wind-direction bins of each meteorological mast were 10 degrees apart, and only the bins having data measured for more than 24 hours were employed for the test site calibration. For both cases, the two methods were found to yield almost same results which estimated real wind speed very closely.

• Journal of Navigation and Port Research
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• v.38 no.2
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• pp.89-96
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• 2014

This paper presents an improvement for calculating method of astronomical ship position based on circle of equal altitude equation. In addition, to enhance the accuracy of ship position achieved from solving equation system, the authors used singular value decomposition (SVD) in least square method instead of normal decomposition. In maths, the SVD was proved more numerically stable than normal decomposition. Therefore, the solution of equation system will be more efficient and the result would be more accurate than previous methods. By proposal algorithm, a computer program have been developed to help the navigators in calculating directly ship position when the modern equipment has failure. Finally, some of experiments are carried out to verify effectiveness of proposed algorithm, the results show that the accuracy of ship position based on new method is better than the intercept method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.354-357
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• 2001

The developed method is proposed to identify rotor dynamic parameters. The method known imbalance vector, which renders over-determined linear system equation. The solution of the system equation can be obtained using least square method. The sensitivity analysis is performed to extract optimized solution, which is considered to be insensitive to inherent measurement errors. As an alternative approach to identify the parameters of bearings and rotor, adding a known imbalance to the rotor produces another equation set to make the system equations over-determined and linearly independent.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.5
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• pp.605-612
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• 1994

The methods to determine the hydrodynamic coefficients for the fixed type artificial reefs which were constructed to control ecological system in coastal waters are compared and discussed by model test results. To calculate the wave forces, least square method show good agreement with the experimental results and more stability than maximum force component method or Fourier decomposition method. This modified least square method of weighting the square of measured force turned out to be the most feasible method for maximum force. Using the feasible method, hydrodynamic characteristics for artificial reefs on uniform slopes offshore and breaking zone were studied. They were properly related to Keulegan-Carpenter's number and found larger than previous results. Wave force coefficients for artificial reefs around breaking zone were distributed from 1.5 to 2.5, and the mean value was 2.0. Drag force components were more in evidence than inertia force in maximum force which is important parameter to evaluate stability for high-permeability structures. A formula for the calculation of the maximum force for artificial reefs design is proposed, using structural dimension, water particle velocity and Keulegan-Carpenter's number.

• Journal of the Korean Chemical Society
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• v.23 no.2
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• pp.104-110
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• 1979

A new least square method for analysis of the whole time course of enzyme-catalyzed reactions is presented. This method requires only a programmable calculator with small capacity and is applicable to both uninhibited reactions and reactions inhibited by products or added compounds. This method fits the data to the nonlinear plot of substrate concentration vs. time, and, consequently, estimates the kinetic parameters better than the least square method based on linearly transformed equations.

• Transactions of the Society of Information Storage Systems
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• v.9 no.1
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• pp.5-9
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• 2013

Page-oriented holographic data storage (HDS) is very sensitive to the disturbances. However, vibration effect by disc imbalance can be ignored because data pages are recorded and retrieved with stop-go rotation. Therefore, just estimating de-track due to eccentricity of disc is enough to construct stable track servo system. In this paper, propose the spacing of track servo patterns optimization method using Least Mean Square (LMS) estimation algorithm. Through the patterns spacing optimization, storage density maximize can be achieved.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.595-611
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• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.