• Journal of Korea Multimedia Society
• /
• v.21 no.7
• /
• pp.737-744
• /
• 2018

This paper presents a study on the performance of the higher-order moments for speech/music classification. For a successful speech/music classifier, extracting features that allow direct access to the relevant speech or music specific information is crucial. In addition to the conventional variance-based features, we utilize the higher-order moments of features, such as skewness and kurtosis. Moreover, we investigate the subband decomposition parameters in extracting features, which improves classification accuracy. Experiments on two speech/music datasets, which are publicly available, were performed and show that the higher-order moment features can improve classification accuracy when combined with the conventional variance-based features.

• Proceedings of the KSPS conference
• /
• 2006.11a
• /
• pp.92-95
• /
• 2006

The purpose of this study is to find the acoustic parameters on frequency domain to distinguish the Korean nasals, /m, n, ng/ from each other. Since it is not easy to characterize the antiformant on frequency domain, we suggest the new parameters that are calculated by LTAS(Long term average spectrum). Maximum energy value and its frequency and minimum energy and its frequency of zero are obtained from the spectrum respectively. In addition, slope1, slope2, total energy value, centroid, skewness, and kurtosis are suggested as new parameters as well. The parameters that are revealed as to be statistically signigicant difference are roughly peak1_a, zero_f, slope_1, slope_2, highENG, zero_ENG, and centroid.

• Communications for Statistical Applications and Methods
• /
• v.18 no.2
• /
• pp.155-164
• /
• 2011

This paper suggests two ratio-cum-product estimators of finite population mean using known coefficient of variation and co-efficient of kurtosis of auxiliary characters. The bias and mean squared error of the proposed estimators with large sample approximation are derived. It has been shown that the estimators suggested by Upadhyaya and Singh (1999) are particular case of the suggested estimators. Almost ratio-cum product estimators of suggested estimators have also been obtained using Jackknife technique given by Quenouille (1956). An empirical study is also carried out to demonstrate the performance of the suggested estimators.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2003.11a
• /
• pp.201-209
• /
• 2003

In the mixed lubrication regime, the roughness effects are very important due to the presence of interacting asperities. An average Reynolds equation using flow factors is very useful to determine effects of surface roughness on mixed lubrication. In this paper, the pressure flow factors and shear stress factor for Gaussian and non-Gaussian surfaces are evaluated in terms of kurtosis and skewness. particularly, the elastic deformation of the surface is considered.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.10a
• /
• pp.745-750
• /
• 2014

The chatter vibration in the machining process plays bad role in machining quality such as high roughness as well as tool life and machine failure. And the grinding process under this risk in the fully automated factory is exposed to the unexpected mass machining quality problem. Studying the vibration signal of the hub bearing grinding process, the reason of chatter vibration was explained with the specific machining pattern of chatter. And this study suggests the chatter detecting method in the production line, which is monitoring the peak acceleration level around the natural frequencies of the specimen, and calculating kurtosis value by assuming the chatter is related to the resonance of the specimen. The suggested method was applied to the vehicle hub bearing grinding process and proved good to detecting the chatter induced machining quality problem.

• 한국기계연구소 소보
• /
• s.19
• /
• pp.61-68
• /
• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.6
• /
• pp.825-832
• /
• 2013

In this study, Independent Component Analysis (ICA) algorithms are suggested to extract the original ECG part from the mixed signal contaminated with the unwanted frequency components and especially 60Hz power line disturbances. With this aim, we implement a novel method to suppress the baseline-wandering disturbances and power line artefacts contained in patch-electrodes sensory ECG data by separating the unmixed signal with finding the optimal weight W based on Kurtosis value. With applying brutal force and gradient ascent searching algorithm to find W, we can conclude that the unwanted frequency components especially in the ambulatory ECG data can be eliminated by Independent Component Analysis.

• The Mathematical Education
• /
• v.42 no.3
• /
• pp.419-423
• /
• 2003

The main purpose of this paper is to investigate effects of skewness and kurtosis on the one-sample test. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. Also the change of type I error was completely based on skewness under the same size of the sample. We conclude that using t-test is more similar to robust than using z-test. In introductory statistics classes where data analysis includes techniques for detecting skewness, we recommend the t-test when skewness is smaller than the value 1 to the one-sample test for a mean when the variances is unknown using the probability of a type I error as the criterion of interest.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1171-1181
• /
• 2014

Different power quality (PQ) disturbance sources can have major impacts on the power supply grid. This study proposes, for the first time, an early warning approach to identifying PQ problems and providing early warning prompts based on the monitored data of PQ disturbance sources. To establish a steady-state power quality early warning index system, the characteristics of PQ disturbance sources are analyzed and summed up. The higher order statistics anomaly detection (HOSAD) algorithm, based on skewness and kurtosis, and hierarchical power quality early warning flow, were then used to mine limit-exceeding and abnormal data and analyze their severity. Cases studies show that the proposed approach is effective and feasible, and that it is possible to provide timely power quality early warnings for limit-exceeding and abnormal data.

• Journal of Information Processing Systems
• /
• v.8 no.3
• /
• pp.421-436
• /
• 2012

Different types of fingerprint detection algorithms that are based on extraction of minutiae points are prevalent in recent literature. In this paper, we propose a new algorithm to locate the virtual core point/centroid of an image. The Euclidean distance between the virtual core point and the minutiae points is taken as a random variable. The mean, variance, skewness, and kurtosis of the random variable are taken as the statistical parameters of the image to observe the similarities or dissimilarities among fingerprints from the same or different persons. Finally, we verified our observations with a moment parameter-based analysis of some previous works.