• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.579-585
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• 2014

A phoneme is the minimal unit of speech, and it plays a very important role in speech recognition. This paper proposes a novel method that can be used to recognize 'ㅅ', 'ㅈ', and 'ㅊ' among Korean phonemes. The proposed method is based on a volatility indicator and a turning point indicator that are calculated for each constituting block of the input speech signal. The volatility indicator is the sum of the differences between the values of each two samples adjacent in a block, and the turning point indicator is the number of extremal points at which the direction of the increment or decrement of the values of the sample are inverted in a block. A phoneme recognition algorithm combines the two indicators to finally determine the positions at which the three target phonemes mentioned above are recognized by utilizing optimized thresholds related with those indicators. The experimental results show that the proposed method can markedly reduce the error rate of the existing methods both in terms of the false reject rate and the false accept rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.563-568
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• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.361-372
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• 2011

This study analyzed the characteristics of stormwater runoff by rainfall type in orchard areas for two years. Effluents were monitored to calculate the EMCs and runoff loads of each pollutant. The runoff characteristics for nonpoint sources from vineyards were also inspected based on independent variables that affect runoff such as rainfall and rainfall intensity. The average runoff loads of each pollutant from vineyard_A and vineyard_B were found as follows: BOD 39.13 mg/$m^2$, COD 112.13 mg/$m^2$, TOC 54.98 mg/$m^2$, SS 1,681.8 mg/$m^2$, TN 18.29 mg/$m^2$, and TP 4.06 mg/$m^2$, which indicates that the COD's runoff load was especially high. The average EMCs from vineyard_A and vineyard_B, which represents the quality of rainfall effluent, were also analyzed: BOD 3.5 mg/L, COD 11.5 mg/L, TOC 5.2 mg/L, SS 211.7 mg/L, TN 1.774 mg/L, and TP 0.324 mg/L. This suggested that the COD, as an indicator of organic pollutants, is high in terms of EMCs as well. As rainfall increased, the EMCs of BOD, COD, TOC and SS kept turning upward. At a point, however, the high rainfall brought about dilution effects and began to push down the EMCs. Higher rainfall intensities led to the increase in the EMCs that displays the convergence of rainfall. Low rainfall intensities also raised pollutant concentrations, although the concentrations themselves were slightly different among pollutants.