• Proceedings of the Korean Society of Crop Science Conference
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• 2003.05a
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• pp.55-55
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• 2003

• Atmosphere
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• v.27 no.3
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• pp.301-316
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• 2017

This study analyzes the spatio-temporal variability of terrestrial carbon flux and the response of land carbon sink with climate factors to improve of understanding of the variability of land-atmosphere carbon exchanges accurately. The coupled carbon-climate models of CMIP5 (the fifth phase of the Coupled Model Intercomparison Project) and CT (CarbonTracker) are used. The CMIP5 multi-model ensemble mean overestimated the NEP (Net Ecosystem Production) compares to CT and GCP (Global Carbon Project) estimates over the period 2001~2012. Variation of NEP in the CMIP5 ensemble mean is similar to CT, but a couple of models which have fire module without nitrogen cycle module strongly simulate carbon sink in the Africa, Southeast Asia, South America, and some areas of the United States. Result in comparison with climate factor, the NEP is highly affected by temperature and solar radiation in both of CT and CMIP5. Partial correlation between temperature and NEP indicates that the temperature is affecting NEP positively at higher than mid-latitudes in the Northern Hemisphere, but opposite correlation represents at other latitudes in CT and most CMIP5 models. The CMIP5 models except for few models show positive correlation with precipitation at $30^{\circ}N{\sim}90^{\circ}N$, but higher percentage of negative correlation represented at $60^{\circ}S{\sim}30^{\circ}N$ compare to CT. For each season, the correlation between temperature (solar radiation) and NEP in the CMIP5 ensemble mean is similar to that of CT, but overestimated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.146-153
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• 2010

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. The CV control chart is an effective tool to control the mean and variability of process simultaneously. The CV control chart, however, is not sensitive at small shifts in the magnitude of CV. The CV-EWMA(exponentially weighted moving average) control chart which was developed recently is effective in detecting a small shifts of CV. Since the CV-EWMA control chart scheme can be viewed as a weighted average of all past and current CV values, it is very sensitive to small change of mean and variability of the process. In this paper, we propose an FIR(Fast initial response) CV-EWMA control chart to improve the sensitivity of a CV-EWMA scheme at process start-up or out-of-control process. Moreover, we suggest the values of design parameters and show the results of the performance study of FIR CV-EWMA control chart by the use of average run length(ARL). Also, we compared the performance of FIR CV-EWMA control chart with that of the CV-EWMA control chart and we found that the CV-EWMA control chart gives longer in-control ARL and much shorter out-of-control ARL.

• Environmental and Resource Economics Review
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• v.25 no.4
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• pp.471-494
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• 2016

This study investigates the effect of remittance and agricultural aid inflows on GDP growth rate volatility in response to climate change shocks in twenty-eight African countries by using system generalized method of moments from 1996 to 2013 with three years grouped data. The climate change shocks are indicated by four variables; natural disasters, rainfall variability, fluctuation in temperature and the weighted anomaly standardized precipitation (WASP) index. Consequently, natural disasters and temperature variability have a significant effect on GDP volatility, while rainfall variability and WASP index have no adverse consequence on stabilization of the economy. On the other hand, in general, remittances and agricultural aid are helpful to stabilize the economy and especially remittances inflows can play a crucial role as insurance when natural disasters occur.

• Journal of Forest and Environmental Science
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• v.38 no.2
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• pp.110-121
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• 2022

Leaf functional traits widely have been used to understand the environmental controls of resource utilization strategy of plants along the environmental gradients. By using key leaf functional traits, we quantified the relationships between leaf traits and local climate throughout the distributional range of Rhododendron caucasicum Pall. in eastern and western Georgian mountains (the South Caucasus). Our results revealed, that all traits showed high levels of intraspecific variability across study locations and confirmed a strong phenotypic differentiation of leaf functional variation along the east-west longitudinal gradient in response to the local climate; out of the explored climatic variables, the moisture factors related to precipitation and number of precipitation and dry days for winter and growth seasons were more strongly related to leaf trait variation than the elevation and air temperature. Among studied leaf traits, the leaf specific area (SLA) showed the highest level of variability indicating the different resource utilization strategies of eastern and western-central Rh. caucasicum individuals. High SLA leaves for western-central Caucasian individuals work in relatively resource-rich environments (more humid in terms of precipitation amount and the number of precipitation days in winter) and could be explained by preferential allocation to photosynthesis and growth, while eastern Caucasian samples work in resource-poor environments (less humid in terms of precipitation amount and the number of precipitation days in winter) and the retention of captured resources is a higher priority appearing in a low SLA leaves. However, more evidence from a broader study of the species throughout its distribution range by including additional environmental factors and molecular markers are needed for firmer conclusions of intraspecific variability of Rh. caucasicum.

• Ocean and Polar Research
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• v.32 no.3
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• pp.187-201
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• 2010

The purpose of this study was to investigate the temporal and spatial variability of taxonomic groups and major species of the mesozooplankton community in Lake Shihwa, Korea. Monthly collections were carried out at five stations in Lake Shihwa for a period of one year. The mesozooplankton community showed distinct seasonal variability with water temperature and salinity. Major mesozooplankton species in each seasonal community were derived from non-metric MDS and SIMPER as follows: winter community (Acartia hongi and Eurytemora pacifica), spring community (Acartia hudsonica and Polychaeta larvae), summer community (Acartia sinjiensis, Pavocalanus crassirostris, Evadne tergestina and Cirripedia nauplii) and fall community (Paracalanus indicus and Podon leuckarti). The succession of the seasonal species, A. hudsonica and A. sinjiensis, was the most remarkable event during the seasonal changes of the mesozooplankton community. The species response curve of these species fitted with the logistic regression in relation to water temperature and salinity. The curve also correctly represented the characteristics of the occurrence of A. hudsonica and A. sinjiensis in Lake Shihwa.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.789-799
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• 2007

In this paper, we propose a stochastic finite element formulation which takes into account the randonmess in the material and geometrical parameters. The formulation is proposed for plate structures, and is based on the weighted integral approach. Contrary to the case of elastic modulus, plate thickness contributes to the stiffness as a third-order function. Furthermore, Poisson's ratio is even more complex since this parameter appears in the constitutive relations in the fraction form. Accordingly, we employ Taylor's expansion to derive decomposed stochastic field functions in ascending order. In order to verify the proposed formulation, the results obtained using the proposed scheme are compared with those in the literature and those of Monte Carlo analysis as well.

• The Plant Pathology Journal
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• v.35 no.1
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• pp.51-62
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• 2019

A great variable response was observed when PP-3 and PP-J encumbered with 116 populations of root knot nematode (RKN) at two different temperatures ($25{\pm}2^{\circ}C$ and $30{\pm}2^{\circ}C$) and concentrations ($10^4$ and $10^5$ spores/ml). The PCR reaction amplified intergenic region between cytochrome oxidase subunit II gene (COII) and large subunit of rRNA gene (lrRNA) of the mitochondrial genome of different RKN species. The primer C2F3 and 1108 identified M. incognita with the highest frequency (52.6%) followed by M. javanica (36.8%) and M. arenaria (10.5%). The sizes of PCR products were 1.7 kb for M. incognita and M. javanica populations while populations of M. arenaria produced 1.1 kb fragment. The digestion with Hinf I yielded three different fragment length patterns on 1.5 % agarose gel. From current research it is concluded that intra-Meloidogyne genetic variability exist in RKN populations which have better encumbrance with P. penetrans.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.186-189
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• 2005

In a clinical setting, developing a reliable method for the automated drug infusion system would improve a drug therapy under the unexpected and acute changes of hemodynamics. The conventional proportional-integral-derivative (PID) controller might not be able to achieve maximum performance because of the unexpected change of the intra- and inter-patient variability. The fuzzy PID control and the conventional PID control were tested under the unexpected response of mean arterial blood pressure (MAP) to a vasopressor agent during acute hypotension. Compared with the conventional PID control, the fuzzy PID control performed the robust MAP regulation regardless of the unexpected MAP response (average absolute value of the error between target value and actual MAP: 0.98 vs. 2.93 mmHg in twice response of the expected MAP and 2.59 vs. 9.75 mmHg in three-times response of the expected MAP). The result was due to the adaptive change of the proportional gain in PID parameters.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.164-172
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• 2005

A loss function approach to a multiresponse problem is considered, when process parameters are regarded as random variables. The variation of each response may be amplified through so called propagation of error (POE), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. The forms of POE for each response and for a pair of responses are proposed and they are reflected in our loss function approach to determine the optimal condition. The proposed method is illustrated using a polymer case. The result is compared with the case where parameter fluctuation is not considered.