• Title/Summary/Keyword: Kurtosis

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Analysis of Parameters on Partial Discharges from Insulation Defects of used Hydro Generator Stator Windings (수력발전기 고정자 노후권선의 모의결함 시편에 대한 부분방전 파라미터 변화 분석)

  • Oh, Bong-Keun;Kim, Hyun-Il;Kang, Seong-Hwa;Lim, Kee-Joe
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.20 no.7
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    • pp.645-649
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    • 2007
  • Partial discharge(PD) test for simulated insulation defects of used hydro generator stator winding was conducted to analyze the PD Parameters. Simulated insulation defects are classified by 5 types corona, slot, internal, multi and aging defect. Phase resolved partial discharge, statistical parameter (skewness, kurtosis), PD magnitude as a function of the test voltage(Q-V curve) and PD magnitude change under test voltage for 2 minutes are used as PD parameters. The analysis of PD parameters by 4 types are proved to be useful methods. In particular, PD parameter characteristics of aging defect could help to assess the aging condition of stator winding because aging defect has more weak insulation strength than other insulation defects : PD distribution is wide and flat, PD rises rapidly near $0^{\circ}\;and\;180^{\circ}$ and Q-V curve rises sharply and then gently drops.

Efficiency of MINQE for arbitrary underlying distribution under one way random effects model (일원변량모형에서의 임의의 분포에 대한 NINQE 추정량의 효율성)

  • 이장택
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.355-370
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    • 1993
  • The estimations of variance components for the unbalanced one way random effects model when the underlying distributions are not necessarily normal are considered. ANOVA, REML, ML, MIVQUE, and MINQE estimators are compared with respect to their mean squared errors and biases through a simulation study. Explicit, computable expressions with no matrix inversion necessary are given for these estimators. An efficient rule to provide a prior guess of MINQE is given. Our results indicate that the efficiency of MINQE is excellent for arbitrary underlying distribution in the sense of MSE even in the presence of nontrivial bias. Also, MINQE is a worthwhile improvement over other estimators when kurtosis of underlying distributions become large 1.

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Use of beta-P distribution for modeling hydrologic events

  • Murshed, Md. Sharwar;Seo, Yun Am;Park, Jeong-Soo;Lee, Youngsaeng
    • Communications for Statistical Applications and Methods
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    • v.25 no.1
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    • pp.15-27
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    • 2018
  • Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

Long Term Average Spectral Analysis for Acoustical Discrimination of Korean Nasal Consonants (한국어 비음의 음향학적 구분을 위한 장구간 스펙트럼(LTAS) 분석)

  • Choi, Soon-Ai;Seong, Cheol-Jae
    • MALSORI
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    • no.60
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    • pp.67-84
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    • 2006
  • The purpose of this study is to find some acoustic parameters on frequency domain to distinguish the Korean nasals, $/m,\;n,\;{\eta}/$ from each other. The new parameters are devised on the basis of LTAS (Long Term Average Spectrum). The maximum peak amplitude and the relevant formant frequency are measured in low and high frequency range, respectively. The frequency of spectral valley and its energy level are also obtained in the specific frequency range of the spectrum. Spectral slope, total energy value in specific frequency range, statistical distribution of spectral energy like centroid, skewness, and kurtosis are suggested as new parameters as well. The parameters that show statistically significant differences across nasals are summerized as follows. 1) in syllable initial positions: the total energy value from 1,500 to 2,200 Hz(zeroENG); 2) in syllable final positions: the peak amplitude of the first formant(peak1_a), the formant frequency with maximum peak amplitude from 4,000 to 8,000 Hz(peak2_f), the maximum peak amplitude of the formant frequency from 4,000 to 8,000 Hz(peak2_a), and the total energy value from 1,500 to 2,200 Hz(zeroENG).

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Application of Neural Network for Damage Diagnosis of Marine Engine Cylinder Liner (선박 엔진의 실린더 라이너의 손상 진단을 위한 신경회로망의 적용)

  • Cho, Yonsang;Koo, Hyunhoo;Park, Junhong;Park, Heungsik
    • Tribology and Lubricants
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    • v.30 no.6
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    • pp.356-363
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    • 2014
  • Marine diesel engines operate in environments in which damage easily occurs from corrosion. Recently, damage to cylinder liners has increased from corrosion wear caused by increased engine power. This damage can cause serious problems in the economy. Thus, many researchers have treated and studied damaged cylinder liners. However, a method is necessary for real-time monitoring of damage to cylinder liners during operation of the engine, before serious damage can occur. This study carries out reciprocating friction and wear tests on a cast iron specimen under various corrosion atmospheres and verifies the variations of friction coefficient and friction surface. Additionally, the friction coefficient and friction status are predicted by using a neural network that learns the vibration and frequency spectrum data from an acceleration sensor. According to our conclusions, amplitude is distributed highly at high frequencies, and values of standard deviation and kurtosis are high when damage to the friction surface is serious. The accuracy rate of the friction coefficient predicted by the neural network is over 80% of the real measured value without NaCl, and application of the neural network is very effective for diagnosing the friction condition and damage to the cylinder liner.

Statistical damage classification method based on wavelet packet analysis

  • Law, S.S.;Zhu, X.Q.;Tian, Y.J.;Li, X.Y.;Wu, S.Q.
    • Structural Engineering and Mechanics
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    • v.46 no.4
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    • pp.459-486
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    • 2013
  • A novel damage classification method based on wavelet packet transform and statistical analysis is developed in this study for structural health monitoring. The response signal of a structure under an impact load is normalized and then decomposed into wavelet packet components. Energies of these wavelet packet components are then calculated to obtain the energy distribution. Statistical similarity comparison based on an F-test is used to classify the structure from changes in the wavelet packet energy distribution. A statistical indicator is developed to describe the damage extent of the structure. This approach is applied to the test results from simply supported reinforced concrete beams in the laboratory. Cases with single and two damages are created from static loading, and accelerations of the structure from under impact loads are analyzed. Results show that the method can be used with no reference baseline measurement and model for the damage monitoring and assessment of the structure with alarms at a specified significance level.

KATSTIC SINKHOLE SEDIMENTS OF DOLOSTONE IN THE UPPER MIDWEST'S DRIFTLESS AREA, USA

  • Oh, Jong-woo
    • Journal of the Speleological Society of Korea
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    • v.34 no.35
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    • pp.78-104
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    • 1993
  • Analysis of one sinkhole, the Dodgeville sinkhole, developed in Ordovician dolostones in the Driftless Area of Wisconsin in the Upper Midwest'd Driftless Area reveals homogenous clayey sediment fills reflecting a range of dissolutional processes during the Quaternary or Pre-Quaternary. Granulometric analysis, graphical moments statistics, carbonate minerals, ana sand grain lithology were used to differentiate sinkhole sediment sources and modes of accumulation. Sediments in the dolostone sinkholes developed by dissolution. Sediments contain two major types of sediments : residual redish clay( autogenic sediments) and aeolian silt (allogenic sediments). The massive clay is generated from the weathered dolostone bedrocks as a in situ materials. The loessial silt is mostly derived from transportation of the surrounding surface materials, with some evidences of penetrated deposition. Unlike the collapsed sandstone sinkholes (Oh et al., 1993), dolostone sinkholes reveal homogenous, autogenic clay materials, and a geochemical composition indicative of in situ autogenic karstification. Dolostone sinkhole si1ts (26.9%) and sands (34.9%) are derived from weathered Plattevi1le-Galena dolostones, and contain high carbonate(37.5%), chert (57.2%) and lead ore (3%). Graphical moments statistics for sorting, skewness, and kurtosis indicate that sand grains from dolostones were derived entirely from local bedrock by in situ dissolution. Upper sinkhole sediments are pedagogically very young as carbonate is unleashed. Materials of the sinkhole sediment are definitely inherited from internal dolostones by dissolution and weathering, because not only a granulomatric comparison of dolostone and sandstone sediments demonstrates that they have heterogeneous paticle size distributions, but also 1ithologic analyses displays they differ completely.

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Regime Dependent Volatility Spillover Effects in Stock Markets Between Kazakhstan and Russia

  • CHUNG, Sang Kuck;ABDULLAEVA, Vasila Shukhratovna
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.8
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    • pp.297-309
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    • 2021
  • In this study, to capture the skewness and kurtosis detected in both conditional and unconditional return distributions of the stock markets of Kazakhstan and Russia, two versions of normal mixture GARCH models are employed. The data set consists of daily observations of the Kazakhstan and Russia stock prices, and world crude oil price, covering the period from 1 June 2006 through 1 March 2021. From the empirical results, incorporating the long memory effect on the returns not only provides better descriptions of dynamic behaviors of the stock market prices but also plays a significant role in improving a better understanding of the return dynamics. In addition, normal mixture models for time-varying volatility provide a better fit to the conditional densities than the usual GARCH specifications and has an important advantage that the conditional higher moments are time-varying. This implies that the volatility skews implied by normal mixture models are more likely to exhibit the features of risk and the direction of the information flow is regime-dependent. The findings of this study contain useful information for diverse purposes of cross-border stock market players such as asset allocation, portfolio management, risk management, and market regulations.

Antecedents of Purchase Decision of Over-The-Counter (OTC) Medicine from Pharmaceutical Distribution Channels in Jordan

  • ALMRAFEE, Mohammad Nabeel Ibrahim
    • Journal of Distribution Science
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    • v.21 no.1
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    • pp.1-12
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    • 2023
  • Purpose: The primary purpose of this research is to understand the potential influence of various factors, namely, pharmacies' recommendations, families' and friend recommendations, price, country of origin, and past experience, on the purchasing decision of nonprescription medicines in the Jordanian context. Research design, data, and methodology: A survey was conducted among 220 Jordanian consumers through a self-administered questionnaire. Further, the authors utilized the mall intercept method as a convenience sampling technique to recruit the respondents who shop at different pharmacies. The data were analyzed using various statistical techniques, such as frequency and percentage for describing the demographics of the sample, Cronbach's alpha for testing the reliability of the data, skewness and kurtosis to check the normality of data, and further, multiple regression using SPSS version 25 was performed for examining the hypotheses. Results: The findings revealed that pharmacists' recommendation, recommendations from friends and family, and price positively influenced consumers' purchase decisions of OTC medicines in Jordan, whereas consumers' past experience and country of origin had no influence on consumers' purchasing decisions of OTC medicines. Conclusions: The paper examines the influence of various factors on customers' purchase decisions of OTC medicines, draws conclusions, and makes recommendations. Also, research limitations are mentioned.

Development and Validation of S.T.E.P+ Diagnostic Tool: Assessing Organizational Competence for Self-management in Daycare Centers (어린이집 자율관리를 위한 조직역량 진단도구(S.T.E.P+)의 개발 및 타당화)

  • Jeong-Won Kang;So-Young Park;Won-Seon Lee;Yoe-Jeong Lim
    • Korean Journal of Childcare and Education
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    • v.20 no.2
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    • pp.105-126
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    • 2024
  • Objective: The study aimed to develop and validate a tool for assessing daycare center organizational competence and for autonomously managing childcare quality. Methods: Through literature review and expert reviews, items were derived and validated using the Content Validity Index. Data from a survey involving 216 directors and 509 teachers were analyzed using SPSS and AMOS to assess reliability and conduct confirmatory factor analysis. Results: Results revealed a 36-item diagnostic tool across four subcategories: shared values (6 items), training abilities (18 items), environmental support (6 items), and organizational promotion (6 items). A diagnostic tool named S.T.E.P+ was developed, named after the first letters of the four subfactors. Skewness and kurtosis were within normality assumptions. Good fit indices (CFI, TLI) and low SRMR and RMSEA values indicated a satisfactory model fit. Cronbach's α values showed high reliability for all factors. The tool enables autonomous diagnosis of childcare quality. Conclusion/Implications: This tool can effectively autonomously diagnose whether a daycare center is providing quality childcare.