• Safety and Health at Work
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• v.11 no.1
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• pp.61-70
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• 2020

Background: This study aims to assess whether the TSI PortaCount (Model 8020) is a measuring instrument comparable with the flame photometer. This would provide an indication for the suitability of the PortaCount for determining the workplace protection factor for particulate filtering facepiece respirators. Methods: The PortaCount (with and without the N95-Companion^TM) was compared with a stationary flame photometer from Moores (Wallisdown) Ltd (Type 1100), which is a measuring instrument used in the procedure for determining the total inward leakage of the particulate filtering facepiece respirator in the European Standard. Penetration levels of sodium chloride aerosol through sample respirators of two brands (A and B) were determined by the two measuring systems under laboratory conditions. For each brand, thirty-six measurements were conducted. The samples were split into groups according to their protection level, conditioning before testing, and aerosol concentration. The relationship between the gauged data from two measuring systems was determined. In addition, the particle size distribution inside the respirator and outside the respirator was documented. Linear regression analysis was used to calculate the association between the PortaCount (with and without the N95-Companion^TM) and the flame photometer. Results: A linear relationship was found between the raw data scaled with the PortaCount (without N95-Companion^TM) and the data detected by the flame photometer (R² = 0.9704) under all test conditions. The distribution of particle size was found to be the same inside and outside the respirator in almost all cases. Conclusion: Based on the obtained data, the PortaCount may be applicable for the determination of workplace protection factor.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1035-1039
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• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• Journal of Technology Innovation
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• v.14 no.3
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• pp.23-42
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• 2006

This study investigates the determinants of output of a manufacturing firm's innovative activity (the number of patent applications) and spillover effects using a count data model. This paper attempted a negative binomial distribution In order to take into account unobserved heterogeneity. The results of our study suggested that Firm size, R&D intensity, technical network activity, and online business performance have significantly positive effects in the Korean manufacturing industry. Moreover, there are significantly positive spillover effects in the same industry sector.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.5
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• pp.91-96
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• 2012

The surface of bushing is contaminated with rain, dust, salt and others. A bushing with contaminations in air is serious problem in insulation. Therefore, it is important to understand the inspection and diagnoses of the safety. The ultra-violet rays(UV) camera has attracted interest from the view point of easy judgement. In this paper, we will report on the corona discharge characteristics of surface flashover model with contaminations in air. Also, UV images of discharge and corona pulse count in air are analyzed using prototype UV camera of Korea and a UV sensor with an optic lens. These results are studied at both AC and DC voltage under a non-uniform field.

• Journal of Gastric Cancer
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• v.9 no.1
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• pp.26-30
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• 2009

Purpose: The aim of this study was to evaluate the prognostic value of the peripheral blood lymphocyte count before surgery in those patients with gastric cancer. Materials and Methods: The study group was comprised of a series of 1,054 patients who underwent curative gastrectomy. The appropriate lymphocyte count cutoff value was determined. The prognostic factors were evaluated by univariate and multivariate analyses. Results: The lymphocyte count cutoff value was 1,500/ul. The patients were classified into two groups: Group A had a lymphocyte count $\geq$ 1,500/ul (n=765) and Group B had a lymphocyte count <1,500/ul (n=289). There were statistically significant differences between the groups according to their age (P<0.001), the tumor stage (P=0.038) and the tumor size (P<0.001). The 5- and 10-year survival rates of Group A were 80.1% and 76.6%, respectively and those of Group B were 72.4% and 63.5%, respectively (P=0.002). When multivariate analysis was performed by the Cox proportional hazards model, the lymphocyte count was not an independent prognostic factor. Conclusion: Although the prognosis of patients with a high lymphocyte count was better than that of the patients with a low lymphocyte count, our results did not support using the preoperative peripheral blood lymphocyte count as an independent prognostic factor for patients with gastric cancer.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.505-519
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• 2006

We consider zero-inflated count data, which is discrete count data but has too many zeroes compared to the Poisson distribution. Zero-inflated data can be found in various areas. Despite its increasing importance in practice, appropriate statistical inference on zero-inflated data is limited. Classical inference based on a large number theory does not fit unless the sample size is very large. And regular Poisson model shows lack of St due to many zeroes. To handle the difficulties, a mixture of distributions are considered for the zero-inflated data. Specifically, a mixture of a point mass at zero and a Poisson distribution is employed for the data. In addition, when there exist meaningful covariates selected to the response variable, loglinear link is used between the mean of the response and the covariates in the Poisson distribution part. We propose a Bayesian inference for the zero-inflated Poisson regression model by using a Markov Chain Monte Carlo method. We applied the proposed method to a Korean oral hygienic data and compared the inference results with other models. We found that the proposed method is superior in that it gives small parameter estimation error and more accurate predictions.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.12
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• pp.55-67
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• 2010

The electrical properties of a back drilled via-hole (BDH) without the open-stub and the plated through via-hole (PTH) with the open-stub, which is called the conventional structure, in a high-count multi~layered (HCML) printed circuit board (PCB) were investigated for a high-speed digital system, and a selected inner layer to transmit a high-speed signal was farthest away from the side to mount the component. Within 10 GHz of the broadband frequency, a design of experiment (DOE) methodology was carried out with three cause factors of each via-hole structure, which were the distance between the via-holes, the dimensions of drilling pad and the anti-pad in the ground plane, and then the relation between cause and result factors which were the maximum return loss, the half-power frequency, and the minimum insertion loss was analyzed. Subsequently, the empirical formulae resulting in a macro model were extracted and compared with the experiment results. Even, out of the cause range, the calculated results obtained from the macro model can be also matched with the measured results within 5 % of the error.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.733-749
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• 2018

Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.

• Journal of Information Technology and Architecture
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• v.10 no.3
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• pp.387-397
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• 2013

This paper proposes an approach to big data analytics for phon call data. The analytical models for phon call data is composed of the PVPF (Parallel Variable-length Phrase Finding) algorithm for identifying verbal phrases of natural language and the word count algorithm for measuring the usage frequency of keywords. In the proposed model, we identify words using the PVPF algorithm, and measure the usage frequency of the identified words using word count algorithm in MapReduce. The results can be interpreted from various viewpoints. We design and implement the model based HDFS (Hadoop Distributed File System), verify the proposed approach through a case study of phon call data. So we extract useful results through analysis of keyword correlation and usage frequency.