• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.756-763
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• 2009

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.19-23
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• 2015

In this paper, we present the return link ACM method to improve the link availability and system throughput for satellite communication service. Also, we describe the optimization of an algorithm for channel prediction using the LMS (Least Mean Square) adaptive filter and the MODCOD (Modulation & Code rate) decision. The simulation results show that the optimized filter taps and step-size of adaptive filter are 2 and 0.00026, respectively. And also confirms the required SNR margin for minimization of MODCOD decision error is 0.3dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.884-889
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• 2021

The number of people infected with Covid-19 in Korea seemed to be gradually decreasing thanks to various efforts such as social distancing and vaccines. However, just as the number of infected people increased after a particular incident on February 20, 2020, the number of infected people has been increasing rapidly since December 2020 by approximately 500 per day. Therefore, the future Covid-19 is predicted through the Prophet algorithm using Kaggle's dataset, and the explanatory power for this prediction is added through the coefficient of determination, mean absolute error, mean percent error, mean square difference, and mean square deviation through Scikit-learn. Moreover, in the absence of a specific incident rapidly increasing the cases of Covid-19, the proposed method predicts the number of infected people in Korea and emphasizes the importance of implementing epidemic prevention and quarantine rules for future diseases.

• Journal of the Korean Statistical Society
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• v.12 no.2
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• pp.69-80
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• 1983

The purpose of this paper is to obtain representation of the mathematical special functions and the numerical values of the mean square errors for the quasi-ranges in random small smaples ($n \leq 30$) from the Weibull distribution with a shape and a scale parameters, and to estimate the scale parameter by use of unbiased estimator based on the quasi-range. It will be shown that the jackknife estimator of the range is worse than the range of random samples from the given distribution in the sense of the mean square error.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.253-255
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• 2010

Needs to study on distance measurement accuracy in aerial and satellite photogrammetry are rapidly increased. However, conventional studies show some confused definitions between measurement accuracy and measurement precision as well as standard deviation(STDEV) and root mean square error(RMSE or RMSD). So, Finite definitions of measurement accuracy and measurement precision as well as STDEV and RMSD are addressed in this paper. Experiment result show using correct definitions improve the distance measurement accuracy in aerial and satellite photogrammetry rapidly, but not the distance measurement accuracy in aerial and satellite photogrammetry.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1406-1409
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• 2016

In this paper, we propose the heuristic signal grouping algorithm to estimate channel state value over full blind communication situation which means that there is no information about the modulation scheme and the channel state information between the transmitter and the receiver. Hereafter, using the constellation rotation method and the probability density function(pdf) the modulation scheme is determined to perform automatic modulation classification(AMC). Furthermore, the modulation type and a channel state value estimation capability is evaluated by comparing the proposed scheme with other conventional techniques from the simulation results in terms of the symbol error rate(SER) and the root mean square error (RMSE).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.10
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• pp.863-871
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• 2017

LMS (least mean square) algorithm widely used in the AVCS (active vibration control system) of helicopters calculates control input using the forward path transfer function and error signal. If the error signal is sinusoidal, it can be represented as the combination of cosine and sine functions with frequency and phase synchronized with the reference signal. The control input also has the same frequency, therefore control algorithm can be simply implemented if the cosine and the sine amplitudes of the control input are calculated and the frequency and phase of the reference signal are used. Calculation of the control input is implemented as simple matrix operation and the change of the control command is slower than the frequency of the error signal, consequently control algorithm can be operated at lower frequency. The signal processing algorithm extracting cosine and sine components of the error signals are modeled using Simulink and PIL (processor-in-the-loop) mode simulation was executed for real-time performance evaluation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.27-33
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• 2013

In this paper, we propose a pilot based channel estimation technique in two-way relay networks. We propose to transmit a pilot symbol together with the data symbol during transmission. In absence of Channel State Information (CSI), destination uses the pilot symbol to estimate the channel. In this system, the relay amplifies the pilot and the data symbol then forward them to the destination using amplify and forward (AF) protocol. We assume that the relay gain is fixed, so the relay does not need to estimate the channel, the destination only estimate the channel. We apply well-known Least-square (LS) and minimum mean-square error (MMSE) channel estimation methods to estimate the channel.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.