Journal of the Computational Structural Engineering Institute of Korea
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v.15
no.3
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pp.491-499
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2002
A p-version finite element model based on degenerate shell element is proposed tot the analysis of orthotropic laminated plates. In the nonlinear formulation of the model, the total Lagrangian formulation is adopted with large deflection and moderate rotation being accounted tot in the sense of yon Karman hypothesis. The material model is based on the Huber-Mises yield criterion and Prandtl-Reuss flow rule in accordance with the theory of strain hardening yield function, which is generalized lot anisotropic materials by introducing the parameters of anisotropy. The model is also based on extension of equivalent-single layer laminate theory(ESL theory) with shear deformation, leading to continuous shear strain at the interface of two layers. The integrals of Legendre polynomials are used for shape functions with p-level varying from 1 to 10. Gauss-Lobatto numerical quadrature is used to calculate the stresses at the nodal points instead of Gauss points. The validity of the proposed P-version finite element model is demonstrated through several comparative points of iew in terms of ultimate load, convergence characteristics, nonlinear effect, and shape of plastic tone.
The objective of this study was to evaluate the probability of norovirus foodborne illness by raw oyster consumption. One hundred fifty-six oyster samples were collected to examine the norovirus prevalence. The oyster samples were inoculated with murine norovirus and stored at 4℃-25℃. A plaque assay determined norovirus titers. The norovirus titers were fitted with the Baranyi model to calculate shoulder period (h) and death rate (Log PFU/g/h). These kinetic parameters were fitted to a polynomial model as a function of temperature. Distribution temperature and time were surveyed, and consumption data were surveyed. A dose-response model was also searched through literature. The simulation model was prepared with these data in @RISK to estimate the probability of norovirus foodborne. One sample of 156 samples was norovirus positive. Thus, the initial contamination level was estimated by the Beta distribution (2, 156), and the level was -5.3 Log PFU/g. The developed predictive models showed that the norovirus titers decreased in oysters under the storage conditions simulated with the Uniform distribution (0.325, 1.643) for time and the Pert distribution (10, 18, 25) for temperature. Consumption ratio of raw oyster was 0.98%, and average consumption amount was 1.82 g, calculated by the Pert distribution [Pert {1.8200, 1.8200, 335.30, Truncate (0, 236.8)}]. 1F1 hypergeometric dose-response model [1 - (1 + 2.55 × 10-3 × dose)-0.086] was appropriate to evaluate dose-response. The simulation showed that the probability of norovirus foodborne illness by raw oyster consumption was 5.90 × 10-10 per person per day. The annual socioeconomic cost of consuming raw oysters contaminated with norovirus was not very high.
We increasingly see the importance of employees acquiring enough expert capability or innovation capability to prepare for ever growing uncertainties in their operation domains. However, despite the above circumstances, there have not been an enough number of researches on how operational input components for employees' innovation outcome, innovation activities such as acquisition, exercise and promotion effort of employee's innovation capability, and their resulting innovation outcome interact with each other. This trend is believed to have been resulted because most of the current researches on innovation focus on the units of country, industry and corporate entity levels but not on an individual corporation's innovation input components, innovation outcome and innovation activities themselves. Therefore, this study intends to avoid the currently prevalent study frames and views on innovation and focus more on the strategic policies required for the enhancement of an organization's innovation capabilities by quantitatively analyzing employees' innovation outcomes and their most suggested relevant innovation activities. The research model that this study deploys offers both linear and structural model on the trio of learning, innovation capability and innovation outcome, and then suggests the 4 relevant hypotheses which are quantitatively tested and analyzed as follows: Hypothesis 1] The different levels of innovation capability produce different innovation outcomes (accepted, p-value = 0.000<0.05). Hypothesis 2] The different amounts of learning time produce different innovation capabilities (rejected, p-value = 0.199, 0.220>0.05). Hypothesis 3] The different amounts of learning time produce different innovation outcomes. (accepted, p-value = 0.000<0.05). Hypothesis 4] the innovation capability acts as a significant parameter in the relationship of the amount of learning time and innovation outcome (structural modeling test). This structural model after the t-tests on Hypotheses 1 through 4 proves that irregular on-the-job training and e-learning directly affects the learning time factor while job experience level, employment period and capability level measurement also directly impacts on the innovation capability factor. Also this hypothesis gets further supported by the fact that the patent time absolutely and directly affects the innovation capability factor rather than the learning time factor. Through the 4 hypotheses, this study proposes as measures to maximize an organization's innovation outcome. firstly, frequent irregular on-the-job training that is based on an e-learning system, secondly, efficient innovation management of employment period, job skill levels, etc through active sponsorship and energization community of practice (CoP) as a form of irregular learning, and thirdly a model of Yί=f(e, i, s, t, w)+${\varepsilon}$ as an innovation outcome function that is soundly based on a smart system of capability level measurement. The innovation outcome function is what this study considers the most appropriate and important reference model.
VALYAVIN G.;KOCHUKHOV O.;SHULYAK D.;LEE B.-C.;GALAZUTDINOV G.;KIM K.-M.;HAN I.
Journal of The Korean Astronomical Society
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v.38
no.2
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pp.283-287
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2005
The slow evolution of global magnetic fields and other dynamical processes in atmospheres of CP magnetic stars lead to the development of induced electric currents in all conductive atmospheric layers. The Lorentz force, which results from the interaction between a magnetic field and the induced currents, may modify the atmospheric structure and provide insight into the formation and evolution of stellar magnetic fields. This modification of the pressure-temperature structure influences the formation of absorption spectral features producing characteristic rotational variability of some spectral lines, especially the Balmer lines (Valyavin et al., 2004 and references therein). In order to study these theoretical predictions we began systematic spectroscopic survey of Balmer line variability in spectra of brightest CP magnetic stars. Here we present the first results of the program. A0p star $\Theta$ Aur revealed significant variability of the Balmer profiles during the star's rotation. Character of this variablity corresponds to that classified by Kroll (1989) as a result of an impact of significant Lorentz force. From the obtained data we estimate that amplitudes of the variation at H$\alpha$, H$\beta$, H$\gamma$ and H$\delta$ profiles reach up to $2.4\%$during full rotation cycle of the star. Using computation of our model atmospheres (Valyavin et al., 2004) we interpret these data within the framework of the simplest model of the evolution of global magnetic fields in chemically peculiar stars. Assuming that the field is represented by a dipole, we estimate the characteristic e.m.f. induced by the field decay electric current (and the Lorentz force as the result) on the order of $E {\~} 10^{-11}$ cgs units, which may indicate very fast (< < $10^{10}$ years) evolution rate of the field. This result strongly contradicts the theoretical point of view that global stellar magnetic fields of CP stars are fossil and their the characteristic decay time of about $10^{10}$ yr. Alternatively, we briefly discuss concurring effects (like the ambipolar diffusion) which may also lead to significant atmospheric currents producing the observable Lorentz force.
We have investigated the atomic and electronic structures of Cu-adsorbed Si(100)-2$\times$1 surface, by using LEED and UPS. In the UPS spectra, the weak structures (peaks) related to Cu silicide appeared for low coverages less than 1.3 ML at room temperature, and the intensity of Cu 3d band rapidly increased with respect to Cu coverages. The Cu silicide peaks become clear after Cu deposition at room temperature followed by high temperature annealing ($\geq 300^{\circ}C$) or for Cu deposited surface at the substrate temperature of $400^{\circ}C$. On the other hand, these structures disappeared by annealing at $750^{\circ}C$. At very low coverage, a surface state near Fermi level $(E_F)$ was observed at $400^{\circ}C$. According to the rigid band model, it seems to be originated from the surface empty state occupied partially with Cu 4s electron. In the LEED patterns, no Cu-induced superstructure observed for RT-depositions and post annealing, while there were several surface structures which depend on substrate temperatures and coverages. we observed the clean surface 2$\times$1+2$\times$2 phase for 1.5 ML at $400^{\circ}C$, the clean surface 2$\times$1+5$\times$1 phase for 0.5 ML at $450^{\circ}C$ and the clean surface 2$\times$1+2$\times$2+5$\times$2+5$\times$5+10$\times$2 mixed phases for 3 ML at $450^{\circ}C$.
The purpose of this study is to explore the factors affecting the social capital of youth and to draw implications for the policies related to development of the social capital of them. To this end, we utilized the OLS regression model and the quantile regression model exploiting the 12th year dataset of the Korean Education & Employment Panel(KEEP). First, this study shows that the effect on trust is higher than that of the counterpart when the case is a) unmarried, b) with the high level of education, c) with a large asset, d) with high self-respect and the satisfaction for financial situation, and e) social media user. On the other hand, the higher the monthly average income, the lower the trust level. In addition, when the cases are grouped into 25 quantile, 50 quantile, and 75 quantile according to the level of trust, it is revealed empirically that the factors affecting social capital formation are somewhat different. Second, this study also shows that the effect is higher in a specific condition. The effect is higher compared to the counterpart when the case is a) male, b) with children, c) metropolitan city resident, d) non-employee, e) with a large asset, f) with high level of happiness, g) with high expense of purchasing books, and h) social media user. As a result, it is found that there are no personal characteristics that have statistically significant influence on students belonging to the 25th quantile of social capital. This study suggests that, in order to support the formation of social capital of Korean youths, it is necessary to enhance their psychological satisfaction and to provide cultural support or policies. In addition, it suggests that a tailored social capital accumulation program is needed according to the level of social capital, and the support for this need to be changed according to the amount of social capital of young people.
F. moniliforme MRC 826, a common fungal contaminant of com, has been known to produce a group of mycotoxins, the fumonisins. By thin layer chromatography, fumonisin $B_{1}$ was detected in the F. moniliforme MRC 826 com culture material(CM) extracts. This study was performed to compare the toxicity and carcinogenicity of F. moniliforme MRC 826 CM with those of aflatoxin $B_1(AFB_1)$ in rats. The toxicity was tested over a period of 7 days in ten female Sprague-Dawley (SD) rats. Treatment group were fed a 1 : 1 mixture(wt/wt) of ground CM and basal diet in powder form, while other negative control group were given basal diet alone. The principal pathological changes in rats treated with 50% CM were hepatocellular hydropic degeneration and renal tubular necrosis. The cancer-promoting activity of CM was evaluated in the rat liver diethylnitrosamine-two thirds partial hepatectomy(DEN-PH) model for carcinogenesis. 70 male SO rats(ca. 170 g) were randomized into 5 groups. Group I served as the positive controls and received the basal diet containing 2 ppm $AFB_{1}$ group 2 received 5% CM, group 3 received 2.5% CM, group 4 received 5% normal com and group 5 received 2.5% normal com. 5% treated group showed cancer promoting activity in rat liver using DEN as initiator and the induction of glutathione S-transferase placental form positive foci as an end point after 6 weeks of promotion.
As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.
Excessive earth pressure is one of the major mechanical factors in the deformation and damage of Cut-and-Cover Tunnel lining in shallow tunnels and portals of mountain tunnels (Kim, 2000). Excessive earth pressure may be attributed to insufficient compaction and consolidation of backfill material due to self-weight, precipitation and vibration caused by traffic (Komiya et al., 2000; Taylor et al., 1984; Yoo, 1997). Even though there were a lot of tests performed to determine the earth pressure acting on the tunnel lining, unfortunately there were almost no case histories of studies performed to determine remedial measures that reduce differential settlement and excessive earth pressure. In this study the installation of geotextile mat was selected to reduce the differential settlement and excessive earth pressure acting on the cut-and-cover tunnel lining. In order to determine settlement and earth pressure reduction effect (reinforcement effect) of geotextile mat reinforcement, laboratory tunnel model tests were performed. This study was limited to the modeling of rigid circular cut-and-cover tunnel constructed at a depth of $1.0D\sim1.5D$ in loose sandy ground and subjected to a vibration frequency of 100 Hz. Model tests with varying soil cover, mat reinforcement scheme and slope roughness were performed to determine the most effective mat reinforcement scheme. Slope roughness was adjusted by attaching sandpaper #100, #400 and acetate on the cut slope surface. Mat reinforcement effect of each mat reinforcement scheme were presented by the comparison of earth pressure obtained from the unreinforced and mat reinforced model tests. Soil settlement reduction was analyzed and presented using the Picture Analysis Method (Park, 2003).
The classification of airflow patterns during high ozone ($O_3$) and $PM_{10}$ episodes on Jeju Island in recent years (2009-2015), as well as their correlation with meteorological conditions according to classified airflow patterns were investigated in this study. The airflow patterns for $O_3$ and $PM_{10}$ were classified into four types (Types A-D) and three types (Types E-G), respectively, using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and synoptic weather charts. Type A was the most dominant airflow pattern for $O_3$ episodes, being characterized by the transport of airflows from urban and industrial areas in China with the highest frequency (about 69%, with a mean of 67 ppb). With regard to the $PM_{10}$ episodes, Type E was the most dominant airflow pattern, and was mostly associated with long distance transport from Asian dust source regions along northwesterly winds, having the highest frequency (about 92%, with a mean of $136{\mu}g/m^3$). The variations in the concentration of $O_3$ and $PM_{10}$ during the study period were clarified in correlation with two pollutant and meteorological variables; for example, the high (low) $O_3$ and $PM_{10}$ concentrations with high (low) air temperature and/or wind speed and vice versa for precipitation. The contribution of long-range transport to the observed $PM_{10}$ levels in urban sites for different airflow patterns (Types E-F), if estimated in comparison to the data from the Gosan background site, was found to account for approximately 87-93% (on average) of its input. The overall results of the present study suggest that the variations in $O_3$ and $PM_{10}$ concentrations on Jeju Island are mainly influenced by the transport effect, as well as the contribution of local emissions.
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