• Wind and Structures
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• v.36 no.3
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• pp.215-220
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• 2023

We study the progressive full-scale wind tunnel tests on a high solidity vertical axis wind turbine (VAWT) for various tip speeds and pitch angles to understand the VAWT shaft system's dynamics using 0-1 Test for chaos. We identify that while varying rotor speed (tip speed) of the turbine, the system's dynamics change from periodic to chaotic through quasiperiodic and strange non-chaotic (SNA) states. The present study is the first experimental evidence for the existence of these states in the VAWT shaft system to the best of our knowledge. Using the asymptotic growth value Kc in 0-1 test, when the turbine operates at the low tip speeds and high pitch angles for low incoming wind speeds, the system behaves periodic (Kc ≈ 0). However, when the incoming wind speed increases further the system's dynamics shift from periodic to chaotic vibrations through quasi-periodic and SNA. This phenomenon is due to the dynamic stalling of blades which induces chaotic vibration in the VAWT shaft system. Further, the singular continuous spectrum method validates the presence of SNA and differentiates the SNA from chaotic vibrations.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.46-55
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• 2016

This experimental study was aimed to estimate interfacial tension of brine-$CO_2$ by using a pendant bubble method and image analysis. Measurements were performed for wide ranges of temperatures, pressures, and salinities covering reservoir conditions in Pohang basin, a possible candidate for $CO_2$ storage operation in Korea. The profiles of $CO_2$ bubbles in brine obtained from image analysis with the densities of brine and $CO_2$ from previous studies were applied to Laplace-Young equation for calculating interfacial twnsion in brine-$CO_2$ system. The experimental results reveals that the interfacial tension is significantly affected by reservoir conditions such as pressure, temperature and water salinity. For conditions of constant temperature and water salinity, the interfacial tension decreases as pressure increases for low pressures (P < $P_c$), and approaches to a constant value for high pressures. For conditions of constant pressure and water salinity, the interfacial tension increases as temperature increases for T < $T_c$, with an asymptotic trend towards a constant value for high temperatures. For conditions of constant pressure and temperature, the interfacial tension increases with increasing water salinity. The trends in changes of interfacial tension can be explained by the effects of the reservoir conditions on the density difference of brine and $CO_2$, and the solubility of $CO_2$ in brine. The information on interfacial tensions obtained from this research can be applied in predicting the migration and distribution of injecting and residual fluids in brine-$CO_2$-rock systems in deep geological environments during geological $CO_2$ sequestrations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.10-16
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• 2007

This paper analyzes the output signal-to-interference-plus-noise ratio (SINR) for a multiple-input-multiple-output (MIMO) multicarrier code division multiple access (MC-CDMA) system with minium mean square error receivers. A previous work of a single antenna MC-CDMA system cannot directly applied to a MIMO MC-CDMA system because some assumptions for single antenna do not match the case of multiple antenna. Therefore this paper expands the concept of freeness to MIMO system by using the Marcenko Pastur law. The analysis shows that the output SINR asymptotically converges to a deterministic value and finds the value on the assumption of freeness. From the analysis, it is easy to calculate bit error rate and the calculation is verified by simulations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.5 s.236
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• pp.643-652
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• 2005

Saturated nucleate pool boiling experiments for binary mixtures, which are consisted of refrigerant R11 and R113, were performed with constant wall temperature condition. Results for binary mixtures were also compared with pure fluids. A microscale heater array and Wheatstone bridge circuits were used to maintain the constant temperature of the heating surface and to obtain heat flow rate measurements with high temporal and spatial resolutions. Bubble growth images were captured using a high speed CCD camera synchronized with the heat flow rate measurements. The departure time for binary mixtures was longer than that for pure fluids, and binary mixtures had a higher onset of nucleate boiling (ONB) temperature than pure fluids. In the asymptotic growth region, the bubble growth rate was proportional to a value between $t^{\frac{1}{6}}$ and $t^{\frac{1}{4}}$. The bubble growth behavior was analyzed to permit comparisons with binary mixtures and pure fluids at the same scale using dimensionless parameters. There was no discernable difference in the bubble growth behavior between binary mixtures and pure fluids for a given ONB temperature. And the departure radius and time were well predicted within a ${\pm}30{\%}$ error. The minimum heat transfer coefficient of binary mixtures occurred near the maximum ${\mid}y-x{\mid}$ value, and the average required heat flux during bubble growth did not depend on the mass fraction of R11 as more volatile component in binary mixtures. Finally, the results showed that for binary mixtures, a higher ONB temperature had the greatest effect on reducing the heat transfer coefficient.

• Smart Media Journal
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• v.9 no.3
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• pp.122-129
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• 2020

The possibility that an asymptotic coronavirus-19 infected person around the world is not aware of his infection and can spread it to people around him is still a very important issue in that the public is not free from anxiety and fear over the spread of the epidemic. In this paper, the K-means clustering algorithm and deep learning-based crowd aggregation were proposed to determine the possibility of contact with confirmed cases of infectious diseases. As a result of 300 iterations of all input learning images, the PSNR value was 21.51, and the final MAE value for the entire data set was 67.984. This means the average absolute error between observations and the average absolute error of fewer than 4,000 people in each CCTV scene, including the calculation of the distance and infection rate from the confirmed patient and the surrounding persons, the net group of potential patient movements, and the prediction of the infection rate.

• Animal Bioscience
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• v.35 no.5
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.833-845
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• 2011

This paper conducts a statistical analysis of extreme values for both daily log-returns and daily negative log-returns, which are computed using a collection of KOSPI data from January 3, 1998 to August 31, 2011. The Poisson-GPD model is used as a statistical analysis model for extreme values and the maximum likelihood method is applied for the estimation of parameters and extreme quantiles. To the Poisson-GPD model is also added the Bayesian method that assumes the usual noninformative prior distribution for the parameters, where the Markov chain Monte Carlo method is applied for the estimation of parameters and extreme quantiles. According to this analysis, both the maximum likelihood method and the Bayesian method form the same conclusion that the distribution of the log-returns has a shorter right tail than the normal distribution, but that the distribution of the negative log-returns has a heavier right tail than the normal distribution. An advantage of using the Bayesian method in extreme value analysis is that there is nothing to worry about the classical asymptotic properties of the maximum likelihood estimators even when the regularity conditions are not satisfied, and that in prediction it is effective to reflect the uncertainties from both the parameters and a future observation.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.193-225
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• 2006

The purpose of this paper is to analyze contagion in Asian foreign exchange markets using Extreme Value Theory and Copula. Our application deals with asymptotic dependence of daily exchange rate return for a sample of eight countries over period 1997.1.1-2005.4.13. The empirical results are summarized as follows. Firstly, Gumbel Copula is a good model to our data according to the value of AIC. Secondly, the extremal dependence between East Asian crisis countries became lower in the post crisis period than the crisis period. Thirdly, It seemed that high extremal dependence exists between East Asian countries with Singapore. Fourthly, the tail dependence between Indonesia, Malaysia, Thailand, Philippine became higher in the crisis period than the total period and post crisis period. Fifthly, the fact that the extremal dependence between Korea and Indonesia, Malaysia, Thailand, Philippine did not increase during the Asian Financial Crisis showed that the contagion effect was not the reason of the Korea's Fiancial Crisis. Sixthly, the extremal dependence between Asian exchange markets was not very high while comparing with the European exchange markets.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.2
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• pp.99-103
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• 2010

A new analytic solution was derived for the diffusion into or from an immobile zone of a rectangular 2-D pore. For a long time, the new solution converges to a traditional mobile-immobile zone (MIM) model, but only if the latter is used with an apparent initial concentration that is smaller by almost 20% than the true one. This is the tradeoff for using a simple MIM model instead of an exact model based on the diffusion equation. The mass-transfer coefficient was found to be constant for a sufficiently long time; it was proportional to the molecular diffusion and inversely proportional to the square of the pore depth. The mass-transfer coefficient was time-dependent for a sufficiently short time and may be significantly larger than its asymptotic value.