• Journal of The Korean Society of Grassland and Forage Science
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• v.14 no.2
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• pp.120-124
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• 1994

Browse from oriental white oak(Quercus aliena Blume) was analysed for nutritive value and biomass estimation. The content of cmde protein was high on August and September. NDF, ADF and lignin contents were increased with progressing the seasons but IVDMD, TDN, DE and ME levels were not different from the variation of seasons. Tannin content was high on May and June. Basal stem diameter $\times$ height of tress was highly correlated with browse dry weights(r=0.80**) and the linear regression equation are the follows; Y = 8.23 + O.57X(Y = browse dry weight(g), X= basal stem diameter $\times$ height(cm)). Using the traditional cutting method, the amounts of browse was determined as 823 g dry weight per tree, while the new method by the above equation gave a similar results, i. e., 793 g dry weight per tree. The possibility of browse biomass estimation of oriental white oak by the basal stem diameter $\times$ height index was found.

• Journal of Korean Society of Rural Planning
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• v.27 no.2
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• pp.43-48
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• 2021

In this study, an analysis was performed using the growth data and environment data of Korean melon farmers to confirm the influence of environmental factors variables on fruit weight of Korean melon. The analysis results can be summarized as follows. First, it was confirmed that humidity and temperature were recognized as the most important factors among the core factors of korean melon farm production management. Second, The correlation analysis of fruit weight and environmental factors showed a statistically significant soil temperature, internal humidity. Third, The Pooled OLS model estimation results showed that the estimation coefficient for soil temperature is (-), and the estimation coefficient for soil temperature square is (+), indicating that optimal control temperature exists.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.281-290
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• 2007

Linear estimator, a weighted sum of the sample observation, is commonly adopted to estimate the finite population parameters such as population totals in survey sampling. The weight for a sampled unit is often constructed by multiplying the base weight, which is the inverse of the first-order inclusion probability, by an adjustment term that takes into account of the auxiliary information obtained throughout the population. The linear estimator using the weight adjustment is often more efficient than the one using only the bare weight, but its valiance estimation is more complicated. We discuss variance estimation for a general class of weight-adjusted estimator. By identifying that the weight-adjusted estimator can be viewed as a function of estimated nuisance parameters, where the nuisance parameters were used to incorporate the auxiliary information, we derive a linearization of the weight-adjusted estimator using a Taylor expansion. The method proposed here is quite general and can be applied to wide class of the weight-adjusted estimators. Some examples and results from a simulation study are presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.9
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• pp.723-734
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• 2018

A structural weight estimation methodology for the multicopter design process is presented. In general, a multicopter is composed of an airframe, motors, propellers, battery and so on. Among these, the weight of motors, propellers and battery can be obtained from the weight trends with respect to design parameters. However, the structural weight is hard to be estimated due to the various configurations and design concepts of multicopters. Moreover, the airframe weights of most commercial multicopter products are not provided. Thus, an accurate airframe weight model is required for the reliable mutlcopter design process. Firstly, the standard configuration of multicopters is defined. Then, we proposed the structural weight estimation method using the number and diameter of propellers determined from the initial step of sizing process. Finally, we validated our suggested method using the commerical products.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1529-1547
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• 2015

Establishment of trust is important in wireless sensor networks for security enhancement and successful collaboration. Basically, a node establishes trust with other nodes by estimating a trust value based on monitored behavior of the other nodes. Since a malicious/misbehaving node might launch different attack strategies and might demonstrate random misbehavior, a trust estimation method should be robust against such attacks and misbehavior. Otherwise, the operation of trust establishment will be meaningless, and performance of an application that runs on top of trust establishment will degrade. In this paper, we propose a robust and novel trust estimation method. Unlike traditional trust estimation methods, we consider not only the weight of misbehavior but also the frequency of misbehavior. The frequency-of-misbehavior component explicitly demonstrates how frequently a node misbehaves during a certain observed time period, and it tracks the behavior of nodes more efficiently, which is a main factor in deriving an accurate trust value. In addition, the weight of misbehavior is comprehensively measured to mitigate the effect of an on-off attack. Frequency and weight of misbehavior are comprehensively combined to obtain the trust value. Evaluation results show that the proposed method outperforms other trust estimation methods under different attacks and types of misbehavior.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.43-56
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• 2005

In this study, a robust estimation method for the first-order autocorrelation coefficient in the time series model following AR(l) process with additive outlier(AO) is investigated. We propose the L-type trimmed least squares estimation method using the preliminary estimator (PE) suggested by Rupport and Carroll (1980) in multiple regression model. In addition, using Mallows' weight function in order to down-weight the outlier of X-axis, the bounded-influence PE (BIPE) estimator is obtained and the mean squared error (MSE) performance of various estimators for autocorrelation coefficient are compared using Monte Carlo experiments. From the results of Monte-Carlo study, the efficiency of BIPE(LAD) estimator using the generalized-LAD to preliminary estimator performs well relative to other estimators.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.98-106
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• 1999

In GMAW, the spatters are generated according to the variation of the arc. Of the arc is stable, Few spatters are generated. But if unstable, too many spatters are generated. So, this means the spatters are dependent on the arc state. The aim of this study is to accurately estimate the arc state. To do this, the generated spatters were captured under the some welding conditions, and the waveforms of the arc voltage and welding current were collected. From the collected signals, the waveform factors and their standard deviations were extracted. Using these factors as input parameters of multi-layer artificial neural network, the learning for the weight of the generated spatters is performed and the estimation results to the real spatter are assessed. Obtained results are as follow: the linear correlation coefficient between the estimated result and the real spatters was 0.9986. And although the average convergence error was set 0.002, the estimated error to the real spatter was within 0.1 gr/min at each welding condition. In the estimation for the weight generated spatters, the result with multi-layer neural network was far better than with multiple regression analysis. Especially, even though under the welding condition which the arc state is unstable (the spatter is generated much more), very excellent estimation performance was shown.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.16-22
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• 2019

This study proposed estimation methods for weight and center of gravity of small fishing vessels. Weights loaded on small fishing vessels were divided into fixed weights such as crew, fishing gear, and variable weights such as fuel, fresh water, provision, bait, and fish. Based on statistical analyses with weight data of several small fishing vessels, weight, longitudinal center of gravity (LCG), vertical center of gravity (KG) of each item were represented as linear functions of vessel gross tonnage. In addition, weighting factors of variable weights were added on estimation formulas in accordance with vessel loading conditions, e.g. full load departure condition. Estimation methods were verified using actual small fishing vessel data.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.87-92
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• 2003

In this paper, a new speech enhancement method using level adapted wavelet packet is presented. First, we propose a level adapted wavelet packet to alleviate a drawback of the conventional node adapted one in noisy environment. Next, we suggest an adaptive noise estimation method at each node on level adapted wavelet packet tree. Then, for more accurate noise component subtraction, we propose a new estimation method of spectral subtraction weight. Finally, we present a modified spectral subtraction method. The proposed method is evaluated on various noise conditions: speech babble noise, F-l6 cockpit noise, factory noise, pink noise, and Volvo car interior noise. For an objective evaluation, the SNR test was performed. Also, spectrogram test and a very simple listening test as a subjective evaluation were performed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.6
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• pp.602-606
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• 1994

The study was conducted to investigate the relationships between the value of fresh leaf lengh ${\times}$ width and actual fresh or cured leaf area, Cured leaf weight of cutter and leaf in Burley tobacco plants. In all tested varieties, Actual fresh leaf area or cured leaf area, cured leaf weight was high significantly correlated with the value of fresh leaf length ${\times}$ width. The linear regression equation between them could be exploited for rapid and easy estimation of either fresh or cured leaf area, cured leaf weight. Highly significant correlation between fresh leaf area and cured leaf area or cured leaf weight was confirmed and a linear regression equation was also obtained for easy estimation of cured leaf area or cured leaf weight.