• International Journal of Highway Engineering
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• v.16 no.3
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• pp.101-107
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• 2014

PURPOSES : This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS : To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS : The optimal model for pedestrian accidents is evaluated to be Tobit model.

• Journal of Information Technology Services
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• v.3 no.1
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• pp.5-20
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• 2004

It has been known generally that investment in the extending ability to use the IT applications have further enhanced the productivity of effects of IT on firms by reducing costs, increasing returns, and increasing the speed of operations, etc. Notwithstanding this fact, it was very complex and difficult to evaluate concretely the effect of informatization of firm. SMEs(Small- & Medium-sized Enterprises) in particular. In this study, I point out the weakness of SMEs and analyze the effects of informatization through the count data model. For this analysis, I separate the effects into two part, such as organizational effect and personal effect. It comes to conclusion that organizational effect is larger than personal effect and the ability to practical use of IT systems is most efficient item related with informatization level. Since it will be important to cencentrate on raising this ability for heightening the competitiveness of SMEs.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.239-250
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• 2022

In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.86-90
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• 2012

Purpose: Quantification of myocardial blood flow (MBF) using dynamic PET imaging has the potential to assess coronary artery disease. Rb-82 plays a key role in the clinical assessment of myocardial perfusion using PET. However, MBF could be overestimated due to the underestimation of left ventricular input function in the beginning of the acquisition when the scanner has non-linearity between count rate and activity concentration due to the scanner dead-time. Therefore, in this study, we evaluated the count rate linearity as a function of the activity concentration in PET data acquired in list mode. Materials & methods: A cylindrical phantom (diameter, 12 cm length, 10.5 cm) filled with 296 MBq F-18 solution and 800 mL of water was used to estimate the linearity of the Biograph 40 True Point PET/CT scanner. PET data was acquired with 10 min per frame of 1 bed duration in list mode for different activity concentration levels in 7 half-lives. The images were reconstructed by OSEM and FBP algorithms. Prompt, net true and random counts of PET data according to the activity concentration were measured. Total and background counts were measured by drawing ROI on the phantom images and linearity was measured using background correction. Results: The prompt count rates in list mode were linearly increased proportionally to the activity concentration. At a low activity concentration (<30 kBq/mL), the prompt net true and random count rates were increased with the activity concentration. At a high activity concentration (>30 kBq/mL), the increasing rate of the prompt net true rates was slightly decreased while the increasing rate of random counts was increased. There was no difference in the image intensity linearity between OSEM and FBP algorithms. Conclusion: The Biograph 40 True Point PET/CT scanner showed good linearity of count rate even at a high activity concentration (~370 kBq/mL).The result indicates that the scanner is useful for the quantitative analysis of data in heart dynamic studies using Rb-82, N-13, O-15 and F-18.

• 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.

• International Journal of Reliability and Applications
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• v.4 no.2
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• pp.79-95
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• 2003

Manufacturers collect and analyze field reliability data to enhance the quality and reliability of their products and to improve customer satisfaction. To reduce the data collecting and maintenance costs, the amount of data maintained for evaluating product quality and reliability should be minimized. With this in mind, some industrial companies assemble warranty databases by gathering data from different sources for a particular time period. This “marginal count failure data” does not provide (i) the number of failures by when the product entered service, (ii) the number of failures by product age, or (iii) information about the effects of the operating season or environment. This article describes a method for estimating age-based claim rates from marginal count failure data. It uses covariates to identify variations in claims relative to variables such as manufacturing characteristics, time of manufacture, operating season or environment. A Poisson model is presented, and the method is illustrated using warranty claims data for two electrical products.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

• Journal of Pharmacopuncture
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• v.17 no.1
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• pp.20-26
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• 2014

Objectives: The study aimed to determine changes in laboratory data for cancer patients receiving Korean medicine (KM) care, with a focus on patients' functional status, cancer-coagulation factors and cancer immunity. Methods: We conducted an observational study of various cancer patients in all stages admitted to the East-West Cancer Center (EWCC), Dunsan Korean Hospital of Daejeon University, from Mar. 2011 to Aug. 2011. All patients were under the center's multi-modality Korean-medicine-based inpatient cancer care program. The hospitalization stay at EWCC ranged from 9 to 34 days. A total of 80 patients were followed in their routine hematologic laboratory screenings performed before and after hospitalization. Patients were divided into three groups depending on the status of their treatment: prevention of recurrence and metastasis group, KM treatment only group, and combination of conventional and KM treatment group. The lab reports included natural killer cell count (CD16 + CD56), fibrinogen, white blood cell (WBC), lymphocytes, monocytes, neutrophil, red blood cell (RBC), hemoglobin, platelet, Erythrocyte Sedimentation Rate (ESR), and Eastern Cooperative Oncology Group (ECOG) performance status. Results: With a Focus on patients' functional status, cancer-coagulation factors and cancer immunity, emphasis was placed on the NK cell count, fibrinogen count, and ECOG scores. Data generally revealed decreased fibrinogen count, fluctuating NK cell count and decreased ECOG, meaning improved performance status in all groups. The KM treatment only group showed the largest decrease in mean fibrinogen count and the largest increase in mean NK cell count. However, the group's ECOG score showed the smallest decrease, which may be due to the concentration of late-cancer-stage patients in that particular group. Conclusions: Multi-modality KM inpatient care may have positive effect on lowering the cancer coagulation factor fibrinogen, but its correlation with the change in the NK cell count is not clear.

• Nuclear Engineering and Technology
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• v.3 no.1
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• pp.3-7
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• 1971

A method for determining dead times of a G.M. detector as a function of the count rate has been investigated using the Mn$^{56}$ radioactive sample. The formula, (equation omitted), seems to be useful for determining a relation between the dead time and the count rate. Here (equation omitted)(N$_1$) is the dead time for the count rate N$_1$, N$_1$is the count rate at time zero, Nt is the count rate at time t, λ is the radioactive decay constant of the sample used, and t is the time between the first and second runs. When all the counting data were corrected for the dead times evaluated with this formula and then a variation of these corrected counting data with rime was observed, the results showed quite a good agreement with the published data for the radioactive decay of Mn$^{56}$ . Besides, it appears that the dead time decreases as the count rate increases in a dead time-to-count rate relation obtained by the same formula.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2956-2958
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• 2000

This paper describes the design of a real time traffic data acquisition system using loop detector and piezzo sensor. Loop detector is the cheapest method to measure the speed and piezzo is used to detect the vehicle axle information. A ISA slot based I/O board is designed for data acquisition and PC process the raw traffic data and transfer the data to the host system. Simulation kit is designed with toy car kits. simulated loop detector and piezzo sensor. The data acquisition system collects up to 10 lane highway traffic data such as vehicle count. speed. length axle count. distance between the axles. The data is processed to generate traffic count, vehicle classification, which are to be used for ITS. The system architecture and simulation data is included and the system will be tested for field operation.