• The Journal of the Acoustical Society of Korea
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• v.3 no.1
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• pp.25-35
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• 1984

This paper analysis the Dynamic Time Warping algorithms for time normalization of speech pattern and discusses the Dynamic Programming algorithm for spoken Korean isolated digits recognition. In the DP matching, feature vectors of the reference and test pattern are consisted of first three formant frequencies extracted by power spectrum density estimation algorithm of the ARMA model. The major differences in the various DTW algorithms include the global path constrains, the local continuity constraints on the path, and the distance weighting/normalization used to give the overall minimum distance. The performance criterias to evaluate these DP algorithms are memory requirement, speed of implementation, and recognition accuracy.

• Korean Journal of Environment and Ecology
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• v.28 no.6
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• pp.642-649
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• 2014

Mallard (Anas platyrhynchos) is the abundant winter visitor in South Korea. Mallard migrates long distances between Russian Siberia and Korea. This species prefers a rice paddy area as their winter habitat. We captured birds using cannon-net, and attached the GPS-Mobile phone based Telemetry(WT-200) on Seven Mallards in the winter of 2011~2013. We were monitored wintering home-range and movement distance. We analyzed the tracking location data using ArcGIS 9.0 and calculated Kernel Density Estimation (KDE) and Minimum Convex Polygon (MCP). The average home-range in the wintering ground by MCP was $118.8km^2$(SD=70.1, n=7)and the maximum home-rang was $221.8km^2$ and the minimum was $27.7km^2$. Extents of home-range by KDE were $60.0km^2$(KDE 90%), $23.0km^2$(KDE 70%) and $11.6km^2$(KDE 50%). Mallard moved an average of 19.4 km from start site(attach to WT-200 site), maximum moved was 33.2 km and minimum moved was 9.4 km. The average distance of 0.8 km between GPS fixed point(range 0.2~1.6 km), maximum moved was 19.7 km. Mallard moved a very short distance in wintering season and showed a very high water-dependent trends in wintering site.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.119-124
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• 2014

Blind adaptive systems based on the Euclidean distance (ED) between the distribution function of the output samples and that of a set of random symbols generated at the receiver matching with the distribution function of the transmitted symbol points estimate the ED at each iteration time to examine its convergence state or its minimum ED value. The problem is that this ED estimation obtained by block?data processing requires a heavy calculation burden. In this paper, a recursive ED estimation method is proposed that reduces the computational complexity by way of utilizing the relationship between the current and previous states of the datablock. The relationship provides a ground that the currently estimated ED value can be used for the estimation of the next ED without the need for processing the whole new data block. From the simulation results the proposed recursive ED estimation shows the same estimation values as that of the conventional method, and in the aspect of computational burden, the proposed method requires only O(N) at each iteration time while the conventional block?processing method does $O(N^2)$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.191-199
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• 2017

PURPOSES : The objective of this study is to develop a methodology to estimate the minimum required separation distance (MRSD) between a vehicle and a bicycle when overtaking. METHODS : Three steps have been conducted to develop a methodology to estimate MSRD. First, a literature review has been conducted on the measurement of MSRD, and how it may be applied in Korea. Second, two assumptions have been made to develop a methodology to estimate the MSRD. The first assumption is that the maximum separation distance between a vehicle and a bicycle can be observed when they are at the same location longitudinally. In addition, it is assumed that the separation distance is invalid when the contra-flow exists. Finally, three cameras were installed at a height of 10 m to record the vehicle-bicycle interaction. Moreover, the vehicle trajectories as well as the separation distance were coded and analyzed. Through the hypothesis test and the interval estimation, the sample mean was tested and the confidence interval was estimated. RESULTS : 141 records of separation distance data were collected, and the hypothesis test demonstrated that the MSRD in Korea is significantly higher than other countries. In addition, the confidence interval of the population mean of MSRD is from 1.51 m to 1.65 m with 95% level of confidence. CONCLUSIONS : It is expected that the proposed methodology to estimate MSRD would be beneficial in studying road safety of vehicles and bicycles. Also, the proposed MSRD is expected to be designated in the act of road and transportation.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.64-68
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• 2007

The classic graphical method to determine the epicenter uses differences between the arrival times of P and S waves at each station. In this research, a robust approach is proposed, which provides a fast and intuitive estimation of earthquake epicenters. This method uses an empirical relationship between epicentral distance and traveltime of the first arrival P phase of local or regional earthquake. The relationship enables us to estimate epicentral distances and draw epicentral circles from each station with P-traveltimes counted from a probable origin time. As the assigned time is getting close to the origin time of the earthquake, epicentral circles begin to intersect each other at a possible location of the epicenter. Then the possibility of the epicenter can be expressed by a function of the time and the space. We choose the location which gives the minimum standard deviation of the origin time as an estimated epicenter. In this research, 918 P arrival times from 84 events occurring from 2005 to 2006 listed in the KMA earthquake catalog are used to determine the empirical P-traveltime function of epicentral distances.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.59-67
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• 2006

OFDM (Orthogonal frequency Division Multiplexing) systems convert serial data stream to N parallel data streams and modulate them to N orthogonal subcarriers. Thus spectrum utilization efficiency of the OFDM systems are high and high-speed data transmission is possible. However, with the OFDM systems using the same modulation method at all subcarriers, the error probability is dominated by the subcarriers which experience deep fades. Therefore, in order to enhance the performance of the system adaptive modulation is required, with which the modulation methods of the subcarriers are determined according to the estimated SNRs. The IEEE 802.11a system selects various transmission speed between 6 and 54 Mbps according to the modulation mode. There are three typical methods for SNR estimation: Direct estimation method uses the frequency domain symbols to estimate SNR directly by minimizing MSE (Mean Square Error), EVM method utilizes the distance between the demodulated constellation points and received complex values, and the method utilizing the Viterbi algorithm uses the cumulative minimum distance in decoding process to estimate the SNR indirectly. Through comparison analyses of three methods we propose a new SNR estimation method, which employs both the EVM method and the Viterbi algorithm. Finally, we perform extensive computer simulations to confirm the performance improvement of the proposed adaptive OFDM systems on the basis of IEEE 802.11a.

• Journal of the Korean Society of Safety
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• v.9 no.1
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• pp.89-94
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• 1994

Two methods, the numerical method of CPQRA and the manual method of IAEA, were used to estimate the effect distance from release and dispersion of toxic materials. The Gaussian plume model which has a weather stability class D with wind velocity of 5m/s was applied to calculate dispersion of toxic materials. Also, probit function were employed to evaluate the human fatality as a result of exposure to toxic gases. Furthermore, concentration of toxic materials corresponding to LC$_{50}$ for 30 min could be determined by setting Pr as 5.0 and solving the probit function. Calculations were conducted by employing chlorine and ammonia as toxic materials because they are not only most commonly used In chemical plants but also very harmful to humans. Calculated results by employing toxic materials indicated that the effect distance from the CPQRA method was between the minimum and maximum distance from the method proposed by IAEA.A.