• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.3185-3199
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• 2018

Middle- and old-aged driver's capability in recognition for driving scene elements was compared. Central and ambient stimuli were selected from natural driving scene and sensitivity, bias and reaction time were measured as dependent measures. The results are as follows. First, in general, older drivers showed lower sensitivity than middle-aged drivers. In particular, the older drivers' sensitivity was significantly lower for the ambient stimuli than central stimuli, whereas the middle-aged drivers showed no significant difference between the two types of stimuli. Second, the older drivers tended to show more lenient responses whereas the middle-aged drivers responded more conservatively. Third, the older drivers showed longer reaction time than the middle-aged drivers, in particular, in the responses of miss and correct rejection. This results suggested that the older drivers' retention for driving scene elements in their working memory may not be stable, which can be resulted in difficulties in rapid and accurate responses in a real life driving.

• Convergence Security Journal
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• v.24 no.2
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• pp.55-61
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• 2024

With the development of IoT technology, wearable services have also developed rapidly. Wearable devices required for this service are used as sensors and controllers in the form of smart bands. Wearable devices implement very concise SWlogic for possible long-term use and use wireless communication protocols to improve convenience. However, because this wearable device aims to be lightweight, it is more vulnerable to security than terminals used for other information services. Many smart healthcare or smart medical services are passive or do not apply security technology. By exploiting this security environment, attackers can obtain or modify important information through access to wearable devices. In this study, we analyzed the technical operating environment of wearable services and identified authentication information reuse attacks, BIAS attacks, battery drain attacks and firmware attacks on wearable devices. And we analyzed the mechanism of each security threat and confirmed the attack effect. In this study, we presented a response plan to respond to the identified security threats. When developing wearable services, it is expected that safer services can be built if the response plan proposed in this study is considered.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.283-295
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• 2024

Many studies have been conducted to properly handle nonresponse. Recently, many nonresponse imputation methods have been developed and practically used. Most imputation methods assume MCAR (missing completely at random) or MAR (missing at random). On the contrary, there are relatively few studies on imputation under the assumption of MNAR (missing not at random) or NN (nonignorable nonresponse) that are affected by the study variable. The MNAR causes Bias and reduces the accuracy of imputation whenever response probability is not properly estimated. Lee and Shin (2022) proposed a nonresponse imputation method that can be applied to nonignorable nonresponse assuming homoscedasticity in super-population model. In this paper we propose an generalized version of the imputation method proposed by Lee and Shin (2022) to improve the accuracy of estimation by removing the Bias caused by MNAR under heteroscedasticity. In addition, the superiority of the proposed method is confirmed through simulation studies.

• Journal of Korean Academy of Nursing
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• v.44 no.4
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• pp.446-457
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• 2014

Purpose: This study was done to evaluate the effects of psychosocial interventions on cortisol and immune response in adult patients with cancer. Methods: MEDLINE via PubMed, Cochrane Library CENTRAL, EMBASE, CINAHL and domestic electronic databases were searched. Twenty controlled trials (11 randomized and 9 non-randomized trials) met the inclusion criteria with a total of 862 participants. Methodological quality was assessed using the Cochrane's Risk of Bias for randomized studies and the Risk of Bias Assessment tool for non randomized studies. Data were analyzed using the RevMan 5.2.11 program of Cochrane library. Results: Overall, study quality was moderate to high. The weighted average effect size across studies was -0.32 (95% CI [-0.56, -0.07], p=.010, $I^2 $=45%) for cortisol concentration, -0.62 (95%CI [-0.96,-0.29], p<.001, $I^2 $=0%) for T lymphocyte (CD3) and -0.45 (95%CI [-0.74, -0.16], p=.003, $I^2 $=0%) for Th lymphocyte (CD4) numbers. Psychosocial interventions were not effective for Tc lymphocyte (CD4), NK cell, monocyte, and cytokine response. Conclusion: Although these results provide only small evidence of successful immune modulation, they support the conclusion that psychosocial interventions can assist cancer patients in reducing emotional distress and improving immune response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.625-633
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• 2013

Multiple response surface optimization (MRSO) aims at finding a setting of input variables which simultaneously optimizes multiple responses. The minimization of mean squared error (MSE), which consists of the squared bias and variance terms, is an effective way to consider the location and dispersion effects of the responses in MRSO. This approach basically assumes that both the terms have an equal weight. However, they need to be weighted differently depending on a problem situation, for example, in case that they are not of the same importance. This paper proposes to use the weighted MSE (WMSE) criterion instead of the MSE criterion in MRSO to consider an unequal weight situation.

• The Journal of Fisheries Business Administration
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• v.40 no.3
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• pp.147-167
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• 2009

The objective of this study is to analyze the determinants of at-home laver consumption expenditures using the data from a survey of households implemented in 2009. It happened that non-response ratios of monthly expenditures on dry laver and flavored laver among sampled households are 18.8% and 25.6%. Accordingly, this study tries to analyze the determinants affecting at-home laver consumption expenditures by using type II tobit model, one of sample selection models, to deal with sample selection bias caused from non-response data. Analysis results show the age variable positively affects expenditures on dry laver but negatively contributes to expenditures on flavored laver. In addition, the household size, the household's income, the degree of preference for laver have positive relationships with both expenditures. Household size elasticity and income elasticity of the expenditure on dry laver are estimated as 0.220 and 0.251. In the case of flavored laver, these elasticities are estimated as 0.484 and 0.261. Such analysis results can provide information on division of the at-home laver consumption market into groups with high willingness to expense and implementation of detailed marketing strategies to increase at-home laver consumption. The methodology of this study can be applied to consumer preference analysis on other marine products and other analyses on sample with non-response data in the fishery research.

• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.145-172
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• 1980

Draper and Lawrence (1965a) have given mixture designs for three factors when all the mixture components can vary on the entire factor space so that the region of interest is an equilateral triangle in two dimensions. In this paper their work is extended to the cases when the region of interest is an echelon, parallelogram, pentagon or hexagon, because of the restirctions imposed on some or all of the mixture components. The principles used in the choice of appropriate designs are those originally introduced by Box and Draper(1959). It is assumed that a response surface equation of first order is fitted, but there is a possibility of bias error due to presence of second order terms in the true model. Minimum bias designs for several cases of restricted regions of interest are illustrated.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.69-82
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• 2017

R-indicator (representativeness indicator) is used to check the representativeness of samples when non-responses occur. The representativeness is related with the accuracy of parameter estimator and the accuracy is related with bias of the estimator. Hence, unbiased estimator generates high accuracy. Therefore, high value of R-indicator guarantees the accuracy of parameter estimation with a small bias. R-indicator is calculated through propensity scores obtained by logit or probit modeling. In this paper we investigate the degree of relation between R-indicator and different non-response rates in strata using simulation studies. We also analyze a modified Korea Economic Census data for real data analysis.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.102-112
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• 1995

Estimation of each of mean response, difference between mean responses and derivatives of the response function is a possible objective of a response surface design. These objectives are to be achieved simultaneously when an experiment is designed to improve mean response. For the situations where departure from the assumed model is suspected, first and second order designs for improving mean response are obtained by combining minimum bias designs for the individual design objectives. D- and A-optimalities are used for selecting specific second order designs. The results are applied to central composite designs.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.649-661
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• 2019

Objective: To systematically review the evaluation of the diagnostic accuracy of pre-treatment apparent diffusion coefficient (ADC) and change in ADC during the intra- or post-treatment period, for the prediction of locoregional failure in patients with head and neck squamous cell carcinoma (HNSCC). Materials and Methods: Ovid-MEDLINE and Embase databases were searched up to September 8, 2018, for studies on the use of diffusion-weighted magnetic resonance imaging for the prediction of locoregional treatment response in patients with HNSCC treated with chemoradiation or radiation therapy. Risk of bias was assessed by using the Quality Assessment Tool for Diagnostic Accuracy Studies-2. Results: Twelve studies were included in the systematic review, and diagnostic accuracy assessment was performed using seven studies. High pre-treatment ADC showed inconsistent results with the tendency for locoregional failure, whereas all studies evaluating changes in ADC showed consistent results of a lower rise in ADC in patients with locoregional failure compared to those with locoregional control. The sensitivities and specificities of pre-treatment ADC and change in ADC for predicting locoregional failure were relatively high (range: 50-100% and 79-96%, 75-100% and 69-95%, respectively). Meta-analytic pooling was not performed due to the apparent heterogeneity in these values. Conclusion: High pre-treatment ADC and low rise in early intra-treatment or post-treatment ADC with chemoradiation, could be indicators of locoregional failure in patients with HNSCC. However, as the studies are few, heterogeneous, and at high risk for bias, the sensitivity and specificity of these parameters for predicting the treatment response are yet to be determined.