• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.88.3-88.3
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• 2015

Kepler mission is performing the quantitative and qualitative observations. Hence, it is possible to statistically study, which is called 'Ensemble asteroseismology', about seismic properties. They investigated about global oscillation parameters. In this study, we performed statistically study about global seismic parameters with Kepler data. Relation between global oscillation parameters (${\Delta}{\nu}$ and ${\nu}max$) are approximately confirmed. We investigated newly about distribution of Full-With-at-Half-Maximum (FWHM) and relation between FWHM and other global oscillation parameters.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.299-308
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• 2013

We investigated the effect of mulberry leaf extract (MLE) on blood biochemical parameters of white rats induced TCDD toxicity. Data were analyzed by One-way ANOVA and Post-Hoc Test. The numbers of leukocyte and platelet decreased by TCDD were increased dramatically after treated MLE (p<0.01). The concentration of calcium and magnesium decreased by TT were increased by MLE and shown a statistical significance (p<0.01) but the concentration of phosphorus increased by TT was decreased by MLE. In the test of parameters related to renal function, only the concentration of uric acid in the MLE group was decreased than it in TT group and shown a statistical significance (p<0.01). Also the concentration of blood glucose and the activity of amylase and lipase increased by TT were decreased after treated MLE and shown a statistical significance (p<0.01), and MLE had an control effect for elevating blood glucose. In the test of parameters related to liver function, the acticity of AST, ALT and ALP increased by TT was decreased after treated MLE and shown a statistical significance (p<0.01), and MLE had an improving effect for liver function. In the case of total cholesterol (T,cho), triglyceride( TG), LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C) related to lipid metabolism, the amount of T,cho, TG, LDL-C increased by TT were decreased after treated MLE and shown a statistical significance (p<0.01), and MLE had an ability of anti-hyperlipidemia. From these results, we concluded that MLE could mollified TCDD toxicity in white rats exposed to TCDD.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.40-44
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• 2010

opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. A dynamical sensing range as a important parameter introduced to maintain the our protocol performance. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.273-276
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• 2010

Opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.346-352
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• 2009

In the present study, the Weibull statistical analysis using the Monte-Carlo simulation has been performed to investigate the micro-Vickers hardness measurement reliability considering the variability. Experimental indentation test were performed with a micro-Vickers hardness tester for as-received and quenching and tempering specimens in SCM440 steels. The distribution of micro-Vickers hardness is found to be 2-parameter Weibull distribution function. The mean values and coefficients of variation (COV) for both data set are compared with results based on Weibull statistical analysis. Finally, Monte-Carlo simulation was performed in order to evaluate the effect of sample size on the micro-Vickers hardness measurement reliability. For the parent distribution with shape parameter 30.0 and scale parameter 200.0 (COV=0.040), the number of sample data required to obtain the true Weibull parameters was founded by 20. For the parent distribution with shape parameter 10.0 and scale parameter 200.0 (COV=0.1240), the number of sample data required to obtain the true Weibull parameters was founded by 30.

• Journal of the Korean Society of Tobacco Science
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• v.20 no.1
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• pp.108-114
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• 1998

This study was conducted to evaluate the techniques or analyzing tobacco smoke by statistical treatment method for the analytical data through Asia Collaborative Study V. In addition to five smoke components analysis, consisting of TPM, water, nicotine, NFDPM, and puff count of four cigarettes samples, statistical parameters such as mean, standard deviation, box-and-whisker plots, h plots, k plots, regression coefficients, reproducibility (R), and repeatability (r) were also calculated. Analysis of water content of cigarette smoke was the most difficult task, whereas puff count analysis was the easiest as well recognized by all laboratories. Analysis of nicotine and puff count accounted for both the lowest and the highest variation among four parameters. The water coefficients indicated more randomness or variation in the slops. The NFDPM data exhibited both types of deviations from linearity. Water content of sample D indicated the highest difference between two single results and between two interlaboratory test results. As a whole, KGTRI ranked higher in the analytical techniques for statistical evaluation of results when compared with the practices of 28 other laboratories.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.103-111
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• 2021

This study addresses a low-cost lidar sensor-based glass feature extraction method for an accurate map representation using statistical moments, i.e. the mean and variance. Since the low-cost lidar sensor produces range-only data without intensity and multi-echo data, there are some difficulties in detecting glass-like objects. In this study, a principle that an incidence angle of a ray emitted from the lidar with respect to a glass surface is close to zero degrees is concerned for glass detection. Besides, all sensor data are preprocessed and clustered, which is represented using statistical moments as glass feature candidates. Glass features are selected among the candidates according to several conditions based on the principle and geometric relation in the global coordinate system. The accumulated glass features are classified according to the distance, which is lastly represented on the map. Several experiments were conducted in glass environments. The results showed that the proposed method accurately extracted and represented glass windows using proper parameters. The parameters were empirically designed and carefully analyzed. In future work, we will implement and perform the conventional SLAM algorithms combined with our glass feature extraction method in glass environments.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.333-339
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• 2003

In this paper, we develop the probability matching priors for the parameters of non-regular Pareto distribution. We prove the propriety of joint posterior distribution induced by probability matching priors. Through the simulation study, we show that the proposed probability matching Prior matches the coverage probabilities in a frequentist sense. A real data example is given.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.525-534
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.327-336
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• 2001

This work concerns estimating a regression function, which is not linear, using aggregate data. In much of the empirical research, data are aggregated for various reasons before statistical analysis. In a traditional parametric approach, a linear estimation of the non-linear function with aggregate data can result in unstable estimators of the parameters. More serious consequence is the bias in the estimation of the non-linear function. The approach we employ is the kernel regression smoothing. We describe the conditions when the aggregate data can be used to estimate the regression function efficiently. Numerical examples will illustrate our findings.