• 환경영향평가
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• 제16권5호
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• pp.351-361
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• 2007

To evaluate dominant synoptic classes which affect on $PM_{10}$ concentration in Seoul, 64 synoptic classes are classified from four seasons, 850hPa geopotential wind and lower level stability Index. In this study, we used air monitoring and meteorological data in Seoul for five years from 2001 to 2005. The results indicate that the highest occurrence frequency of synoptic class is under a strong westerly geopotential wind and stable lower atmosphere in spring. The highest $PM_{10}$ concentration of synoptic class is associated with a weak geopotential wind speed and high lower level stability. In that class, not only $PM_{10}$ but $SO_2$, $NO_2$ and CO concentrations are also higher than other classes. The analysis of spacial distribution of $PM_{10}$ concentration in each class are indicate that the influence of synoptic class are similar in the Metropolitan area in Korea. But $PM_{10}$ concentration in some areas in Kyoung-Gi are more higher than in Seoul. The relationship between $PM_{10}$ concentration and Meteorological indicator (relative humidity, temperature, surface wind speed) under same synoptic class is more correlative in Winter than other season.

• BMB Reports
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• 제53권4호
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• pp.191-205
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• 2020

The unexpected pandemic set off by the novel coronavirus 2019 (COVID-19) has caused severe panic among people worldwide. COVID-19 has created havoc, and scientists and physicians are urged to test the efficiency and safety of drugs used to treat this disease. In such a pandemic situation, various steps have been taken by the government to control and prevent the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). This pandemic situation has forced scientists to rework strategies to combat infectious diseases through drugs, treatment, and control measures. COVID-19 treatment requires both limiting viral multiplication and neutralizing tissue damage induced by an inappropriate immune reaction. Currently, various diagnostic kits to test for COVID-19 are available, and repurposing therapeutics for COVID-19 has shown to be clinically effective. As the global demand for diagnostics and therapeutics continues to rise, it is essential to rapidly develop various algorithms to successfully identify and contain the virus. This review discusses the updates on specimens/samples, recent efficient diagnostics, and therapeutic approaches to control the disease and repurposed drugs mainly focusing on chloroquine/hydroxychloroquine and convalescent plasma (CP). More research is required for further understanding of the influence of diagnostics and therapeutic approaches to develop vaccines and drugs for COVID-19.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.176.2-176.2
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• 2013

Property of optical diagnostics for pulse-discharged plasma in liquid and its biological applications to proteins are investigated by making use of high voltage Marx generator. The Marx generator has been consisted of 5 stages, where each charging capacitor is 0.5 ${\mu}F$, to generate a high voltage pulse with rising time of $1{\mu}s$. We have applied an input voltage of 6 kV to the each capacitor of 0.5 ${\mu}F$. High voltage pulsed plasma has been generated inside a polycarbonate tube by a single-shot operation, where the breakdown voltage is measured to be 7 kV, current of 1.2 kA, and pulse width of ~ 1 ${\mu}s$ between the two electrodes of anode-cathode whose material is made of tungsten pin, which are immersed into the liquids. We have investigated the emitted hydrogen lines for optical diagnostics of high voltage pulsed plasma. The emission line of 656.3 nm from $H-{\alpha}$ and 486.1 nm from $H-{\beta}$ have been measured by a monochromator. If we assumed that the focused plasma regions satisfy the local thermodynamic equilibrium conditions, the electron temperature and density of the high voltage pulsed plasma in liquid could be obtained by the Stark broadening of optical emission spectroscopy. For the investigation of the influence of pulsed plasma on biological proteins, we have exposed it onto the proteins such as hemoglobin and myoglobin. The structural changes in these proteins and their analysis have also been obtained by circular dichroism (CD) and ultraviolet (UV) visible spectroscopy.

• Journal of the Korean Data and Information Science Society
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• 제3권1호
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• pp.1-16
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• 1992

In regression diagnostics, a number of joint influence measures based on various statistical tools have been discussed. We consider an alternate representation in terms of the predicted residual and g-leverage determined by the remaining points. By this approach, we choose the predicted residual sum of squares for the keypoints as joint influence measure and propose a new expression of it so that we can extend the single case form to the multiple case one. Furthermore we suggest a seach method for joint influence after investigating some properties of the new expression.

• 품질경영학회지
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• 제28권2호
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• pp.57-69
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• 2000

This paper discusses the local influence approach to the linear regression models with AR(2) errors. Diagnostics for the linear regression models with AR(2) errors are proposed and developed when simultaneous perturbations of the response vector are allowed- That is, the direction of maximum curvature of local influence analysis is obtained by studying the curvature of a surface associated with the overall discrepancy measure.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.155-162
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• 2017

In this paper we propose influence measures for two basic goodness-of-fit statistics, the coefficient of determination $R^2$ and test statistic F in the linear regression model using the deletion method. Some useful lemmas are provided. We also express the influence measures in terms of basic building blocks such as residual, leverage, and deviation that showed them as increasing function of residuals and a decreasing function of deviation. Further, the proposed measure reduces computational burden from O(n) to O(1). As illustrative examples, we applied the proposed measures to the stackloss data sets. We verified that deletion of one or few influential observations may result in big change in $R^2$ and F-statistic.

• 산업경영시스템학회지
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• 제15권25호
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• pp.97-101
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• 1992

This paper proposes a new procedures for assessing the influence of individual or groups of cases when any regressors are included. At first, various influence measures pickout influential cases when one regress-or is deleted. Next find influential subsets by using heuristic approach and perform group deletion. Retaining or removing any regressors may depend on the presence or absence of one or few cases. Then, we can identify the interrelationships that exist among regressors and cases and examine their impact on the fitted regression equation. We conclude with an example using fuel consumption data.

• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.111-118
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• 2002

We study the influence of observations on testing a linear hypothesis using single and multiple case-deletions. The change in the F-test statistic due to case-deletions is shown to be completely determined by two externally Studentized residuals. These residuals we used for investigating the outlyingness when there are linear constraints or not. An illustrative example is given. It shows the usefulness of case-deletions.

• Communications for Statistical Applications and Methods
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• 제21권3호
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• pp.253-260
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• 2014

The intraclass correlation model has a long history of applications in several fields of research. Case deletion diagnostic methods for the intraclass correlation model are proposed. Based on the likelihood equations, we derive a formula for a case deletion diagnostic method which enables us to investigate the influence of observations on the maximum likelihood estimates of the model parameters. Using the Taylor series expansion we develop an approximation to the likelihood distance. Numerical examples are provided for illustration.

• Journal of the Korean Statistical Society
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• 제31권2호
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.