• Journal of the Korean Society of Tobacco Science
• /
• v.22 no.2
• /
• pp.151-156
• /
• 2000

The variability of a ventilated filter cigarette depends on the details of its construction and on the variabilities of its components. Variations in filter ventilation arise from many sources, including variations in tobacco rod pressure drop, filter tip pressure drop, tipping paper permeability, and plugwrap permeability. To reduce the filter ventilation variability, the variability of filter ventilation levels in ventilated cigarettes is studied by Monte Carlo Analysis. For each trials a value is selected for tobacco rod pressure drop, filter tip pressure drop, tipping paper permeability, and plugwrap permeability. These values are selected randomly from a normal distribution based on the target and coefficient of variation for each input variable. The results of this analysis for filter ventilation variation suggest that the variations of filter ventilation are dependent on the details of cigarette designs studied and reducing the variability of any cigarette component will reduce filter ventilation variability. For typical cigarettes, variation in the permeability of tipping paper is usually the most significant contributor to filter ventilation variability. Results of a Monte Carlo Analysis could provide both general insights and specific practical guidance about the design of ventilated filter cigarettes.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.12 no.2
• /
• pp.84-95
• /
• 2008

Background and purpose: Health is characterized by variability and a loss variability is associated with aging and disease. Normal healthy respiratory patterns are characterized by breath to breath variability. The aim of this study is to analyze Correlation Analysis of 10 respiratory indices(include breath to breath variability) and K-POMS factors score. Method: Respiratory data were measured during 15 minutes and transferred to text file. We calculated 10 respiratory parameters in use of MATLAB7.1. After then do correlation analysis of 10 respiratory indices and K-POMS factors score. Result and conclusion: Respiratory variability is showed significant correlation with vigor factor. Respiratory rate is showed significant correlation with depression factor.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.12 no.2
• /
• pp.74-83
• /
• 2008

Background and purpose : Health is characterized by variability, and the loss of variability is associated with aging and disease. Normal healthy respiratory patterns are characterized by breath to breath variability. Cold-Heat scores are quantified indices in Korean Medicine. The aim of this study is to analyze relations between 9 respiratory indices (including breath to breath variability) and HRV(heart rate variability). Method : Respiratory data were measured during a period of 15 minutes and transferred to text file. We calculated 9 respiratory parameters using MATLAB 7.1. Afterwards we did correlation analysis of the 9 respiratory indices and HRV. Results and conclusion : Respiratory variability showed significant correlation with HRV.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1247-1251
• /
• 2016

This study aims to investigate the effect of sampling frequency to the time domain and frequency domain analysis of pulse rate variability (PRV). Typical time domain variables - AVNN, SDNN, SDSD, RMSSD, NN50 count and pNN50 - and frequency domain variables - VLF, LF, HF, LF/HF, Total Power, nLF and nHF - were derived from 7 down-sampled (250 Hz, 100 Hz, 50 Hz, 25 Hz, 20 Hz, 15 Hz, 10 Hz) PRVs and compared with the result of heart rate variability of 10 kHz-sampled electrocardiogram. Result showed that every variable of time domain analysis of PRV was significant at 25 Hz or higher sampling frequency. Also, in frequency domain analysis, every variable of PRV was significant at 15 Hz or higher sampling frequency.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.479-482
• /
• 2004

This paper proposes a new framework for variability analysis in QFD. The proposed framework considers the uncertainty of the information contained in the house of quality chart and analyzes the variability resulting in the outcome. A new framework provides a dominance index and a difference index for each pairwise ECs. The indices are helpful to evaluate priorities of each pairwise EC.

• Korean Journal of Applied Biomechanics
• /
• v.18 no.4
• /
• pp.49-57
• /
• 2008

The purpose of this study was to determine the effects of 12-week elastic resistance exercise for the elderly on the magnitude of frequency and variability of ground reaction force signals. To this aim, total 12 elderly women aged in their 70 were participated in this study and asked to do a 12-week elastic resistance exercise program. FFT(fast Fourier Transform) was used to analyze the frequency domain analysis of the ground reaction forces's signals and an accumulative PSD (power spectrum density) normalized by support phase of walking was calculated to reconstruct the certain signals. To estimate the gait stability between the before and after exercise, values of variability were determined in a coefficient of variance. The magnitude of frequency and variability analysis for media-lateral signal revealed significantly less after exercise (p<.05). In contrast, variability of this signal's frequency that have used to evaluate the local stability during walking exhibited significantly greater after exercise(p<.05). In summary, magnitude frequency and variability of media-lateral ground reaction force's signal were significantly changed after a 12-week elastic resistance exercise.

• The Journal of Fisheries Business Administration
• /
• v.48 no.2
• /
• pp.1-17
• /
• 2017

This work studies the variability of flatfish sales revenue. The theoretical analysis draws functions for equilibrium price and quantity using expectation hypotheses. The functions include unpredictable phenomenon with dummy variable and GARCH. The equilibrium function, using adaptive expectation hypothesis, contains the independent variables of supply and demand, while the equilibrium function, embodying rational expectation hypothesis, includes only the independent variables of supply side, because the demand side disappears by the information extraction process theoretically, if economic subjects build the expectation rational. The empirical analysis shows: the variability of flatfish production has a spillover effect on the variability of revenue with the adaptive expectation hypothesis. In the case when the model has a rational expectation hypothesis, the variability of flatfish production has a spillover effect on the revenue (the mean equation of GARCH model). This study indicates that there is the variability in flatfish production and sales revenue, and the spillover effect between them. The result can help to build of the rational system for the fishery income stability.

• Korean Journal of Applied Biomechanics
• /
• v.17 no.4
• /
• pp.1-8
• /
• 2007

The purpose of this study was to investigate the difference in the stride-to-stride variability between two treadmill conditions; traditional treadmill and special treadmill whose speed can be adjusted automatically by subject's walking speed. Eight male subjects (25.1 years, 172.7 cm, 66.6 kg) were participated in treadmill walking experiment. First, preferred walking speed (PWS) of each subject was determined. Second, each subject performed walking experiment with fixed PWS condition and with free PWS condition for 10 minutes. 3D motion capture system (Motion analysis Corp., USA) with 6 cameras was used to collect motion data with sampling frequency of 120Hz. Temporal and spatial variables for stride-to-stride variability were calculated. Coefficient of variance (CV) which quantifies the amount of variability and Detrended Fluctuation Analysis (DFA) which explains the structure (self-similarity) of the variability were used for analysis. Results showed that the amount of variability during free PWS condition was greater than that of fixed PWS condition. DFA results showed that there was a statistical difference between two treadmill conditions for the variables of step length, stance time, and double support time. From these results, it is possible that traditional treadmill study might give incorrect conclusion about gait variability study. Further study is necessary to clarify these matters by considering the number of subjects, experimental time, and gait variables for the study of stride-to-stride variability.

• The KIPS Transactions:PartD
• /
• v.16D no.6
• /
• pp.927-934
• /
• 2009

This paper presents a commonality and variability analysis method for UML CASE tool frameworks. Commonality and Variability analysis increase extension and reusability by separating common area and variable area. We suggest class category based on property and the notation to represent commonality and variability. It is also implements frameworks based on analysis method and verify method using defect removal efficiency.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.3
• /
• pp.55-63
• /
• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.