• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.381-388
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• 2016

It is common to quantify the concept of interest in the social and human sciences to test a research hypothesis. In such a case, it is strongly recommended to investigate if the procedure is appropriately designed and implemented according the research purpose since the quantification procedure highly affects the result of statistical analysis. In this work, we propose a visualization tool which enables us to check the construct validity of a measurement tool (such a questionnaire) in a concise and convenient way based on a penalized factor analysis model. We illustrate our method with numerical simulation and real data analysis.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.531-541
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• 2016

Cerebral atrophy affects the brain and is a common feature of patients with mild cognitive impairment or Alzheimer's diseases. It is evaluated by the radiologist or reader based on patient's history, age and the space between the brain and the skull as indicated by magnetic resonance (MR) images. A total of 70 patients were scanned in the supine and prone positions before three radiologist assessed their atrophy level. This study examined the radiologist's assessment of the cerebral atrophy level using a graded response model of item response theory (IRT). A graded response model (GRM) is fitted to our data and then item-fit and person-fit statistics are evaluated to assess the fitted model. Our analysis found that the cerebral atrophy level is better discriminated by readers in the prone position because all item slopes were greater than 2 at this position, versus the supine position where all the slope parameters were less than 1. However, the thresholds are very similar for the first reader and are quite different for the second and third readers because the scanning position affects readers differently as the category threshold estimates vary considerably between the readers..

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.187-187
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• 2016

High intensity of population distribution in deltaic setting especially in Asia tends to have increased and causes coastal flood risk due to lower elevations and significant subsidence. Maximum or peak discharge of flood always causes numerous deaths and huge economic losses. New technology of spatial satellite image has been applied to analyze flood damage. In this research, the relationship of nightlight intensity associated with flood damages has been determined during 1992-2013 with spatial resolution of 30 arc sec ($0.0083^{\circ}$) which is nearly one kilometer at the equator in whole six countries along the Mekong River (i.e., China, Myanmar, Lao PDR, Thailand, Cambodia and Vietnam). ArcGIS Hydrological Flow Length Tool has been used to determine the distance of each pixel areas from the rivers and streams. Statistical analysis results highlight the significant correlation R = 0.47 between nightlight digital number and economic damages per unit area (US$/km2) and R = 0.62 for number of affected people for unit area ($people/km^2$). The areas near by the Mekong River and its tributaries correspond to high flood damage. This spatial analysis result is going to be prestigious key information to the regions and all related stakeholders for decisions and mitigation strategies.

• PNF and Movement
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• v.18 no.1
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• pp.133-141
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• 2020

Purpose: The purpose of this study was to conduct balance training through vision control to improve the balance, postural control, and balance confidence and to decrease the visual and sensory dependence of stroke patients. Methods: Twenty-eight chronic stroke patients volunteered to participate in the study. They were randomly assigned to the eyes-closed and the eyes-open training groups. Three times a week for four weeks each group performed an unstable-support session and a balance training session for thirty minutes per set. Their balance, postural control, and balance confidence were assessed using BIO Rescue (BR), the postural assessment scale for stroke (PASS), and the Korean activity-specific balance confidence scale (K-ABC), respectively. All data were analyzed using SPSS version 22.0. Statistical methods before and after working around the average value of each dataset were independent T-test. The significance level for statistical analyses was set at 0.05. Results: Comparison between the groups showed statistically significant effects on all variables before and after the intervention (p < 0.05). Conclusion: This study reflected that balance-training programs involving vision control improve the balance, postural control, and balance confidence of chronic stroke patients. Thus, stroke patients should undergo training programs that increase the use of their other senses with vision control in clinical practice.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.186-195
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• 2021

In Korea, groundwater quality is monitored through National Groundwater Quality Monitoring Network (NGQMN) administered by Ministry of Environment. For a given contaminant, compliance to groundwater quality standards is assessed on a annual basis by monitoring the number of incidents that concentration exceeds the regulatory limit. However, this approach provides only a fractional information about groundwater quality degradation, and more crucial information such as location and severity of the contamination cannot be obtained. For better groundwater quality management on a watershed, a more spatially informative and intuitive method is required. This study presents two statistical methods to convert point-wise monitoring data into information on groundwater quality status of a watershed by using a proposed grading scale. The proposed grading system is based on readily available reference standards that classify the water quality into 4 grades. The methods were evaluated with NO₃^-, Cl^-, and total coliform data in Geum River basin. The analyses revealed that groundwater in most watersheds of Geum River basin is good for domestic or/and drinking with no treatment. But, there was notable quality degradation in Bunam seawall and So-oak downstream standard watersheds contaminated by NO₃^- and Cl^-, respectively.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.373-380
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• 2004

This paper presents the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The impedance-based damage detection method is based on monitoring the changes in the electrical impedance. Those changes in the electrical impedance are due to the electro-mechanical coupling property of the piezoelectric material and structure. An effective integrated structural health monitoring system must include a statistical process of damage detection that is automated and real time assessment of damage in the structure. Once measured, damage sensitive features from this impedance change can be statistically quantified for various damage cases. The results of the experimental study on three kinds of structural members show that cracks or loosened bolts/nuts near the PZT sensors may be effectively detected by monitoring the shifts of the resonant frequencies. The root mean square (RMS) deviations of impedance functions between before and after damages were also considered as a damage indicator. The subsequent statistical methods using the impedance signature of the PZT sensors were investigated.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.984-991
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• 2022

The use of the sustainability rating systems in infrastructure construction projects is not as common in comparison to building construction projects. While the sustainability rating systems share some commonalities, they differ from one another in certain ways. Thus, project teams cannot make reliable decisions when choosing the best sustainability rating tools for a given infrastructure projects. The Department of Transportation (DOT) in several states are developing its own rating system to address the infrastructure sustainability, but not in the case of California. Therefore, this paper presents the statistical results on the important sustainability determinants that affects the success of meeting sustainability goals of infrastructure construction projects. The authors conducted an online survey using the structured questionnaires. The categories considered include site, water/wastewater, energy, materials/resources, environmental, and others. The statistical analyses such as Kruskal-Wallis and ANOVA are conducted using a total of 25 valid and complete data out of 59 surveys collected. The results demonstrate several factors under each of six major sustainable categories have received higher ranks than other factors. The results also show that a statistically significant difference can be found from water, energy, and environmental categories against the other category based on the pairwise comparisons.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.291-309
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• 2023

Longitudinal count data has been widely collected in biomedical research, public health, and clinical trials. These repeated measurements over time on the same subjects need to account for an appropriate dependency. The Poisson regression model is the first choice to model the expected count of interest, however, this may not be an appropriate when data exhibit over-dispersion or under-dispersion. Recently, Conway-Maxwell-Poisson (CMP) distribution is popularly used as the distribution offers a flexibility to capture a wide range of dispersion in the data. In this article, we propose a Bayesian CMP regression model to accommodate over and under-dispersion in modeling longitudinal count data. Specifically, we develop a regression model with random intercept and slope to capture subject heterogeneity and estimate covariate effects to be different across subjects. We implement a Bayesian computation via Hamiltonian MCMC (HMCMC) algorithm for posterior sampling. We then compute Bayesian model assessment measures for model comparison. Simulation studies are conducted to assess the accuracy and effectiveness of our methodology. The usefulness of the proposed methodology is demonstrated by a well-known example of epilepsy data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.323-333
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• 2024

Recently, Syntheic data has been in the spotlight as a technology that can protect personal information while maintaining the patterns and characteristics of actual data. Accordingly, technical and institutional research on synthetic data is actively being conducted, but it is difficult to actively use synthetic data due to the lack of clear standards and guidelines. This study is a preliminary study for quantifying the disclosure risk of synthetic data, and derives a privacy disclosure risk index through statistical methodology and suggests specific application measures to comply with the General Data Protection Regulation(GDPR). It is expected that the disclosure risk and the balance of data utility can be controlled through the privacy disclosure risk index of this study in an open data environment.

• Journal of The Korean Association For Science Education
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• v.29 no.3
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• pp.277-290
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• 2009

In the era of the outcome-based education, multiple-choice test has been widely employed owing to its efficiency that enables educators to evaluate a quantity of students with much objectiveness. However, the prevalent test has not been reconsidered enough to overcome its apparent shortcomings: examiners' effort for developing plausible and faultless distracters defending from every falsification, and students' random guessing on key choices. For alleviating such defects, tiered test as an experimental format of multiple-choice tests has been suggested in science education. Since there has not accumulated much study on the implementation of tiered tests, our research aim is set to construct a framework suggesting statistical indexes for rationally discerning tiered units that develop an effective tiered test. Graded both by our tiered-scoring and by the conventional partial-scoring, the preliminary tiered test in secondary physics attests the improvement in its discrimination and difficulty distribution. The findings reveal that the two indexes discern effective tiered items: discrimination increase (Ct-p) and difficulty decrease (Dp-t). Based on the index information, 4 heterogeneous tier types are recommended in the content of secondary physics: directional manipulation, repeated calculation, diverse explanation, and plural variables.