• Korean Journal of Exercise Nutrition
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• v.25 no.1
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• pp.23-29
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• 2021

[Purpose] This preliminary study aimed to develop a regression model to estimate the non-exercise activity thermogenesis (NEAT) of Korean adults using various easy-to-measure dependent variables. [Methods] NEAT was measured in 71 healthy adults (male n = 29; female n = 42). Statistical analysis was performed to develop a NEAT estimation regression model using the stepwise regression method. [Results] We confirmed that age^A, weight^B, heart rate (HR)_average^C, weight × HR_average^D, weight × HR_sum^E, systolic blood pressure (SBP) × HR_rest^F, fat mass ÷ height^2G, gender × HR_average^H, and gender × weight × HR_sum^I were important variables in various NEAT activity regression models. There was no significant difference between the measured NEAT values obtained using a metabolic gas analyzer and the predicted NEAT. [Conclusion] This preliminary study developed a regression model to estimate the NEAT in healthy Korean adults. The regression model was as follows: sitting = 1.431 - 0.013 × (A) + 0.00014 × (D) - 0.00005 × (F) + 0.006 × (H); leg jiggling = 1.102 - 0.011 × (A) + 0.013 × (B) + 0.005 × (H); standing = 1.713 - 0.013 × (A) + 0.0000017 × (I); 4.5 km/h walking = 0.864 + 0.035 × (B) + 0.0000041 × (E); 6.0 km/h walking = 4.029 - 0.024 × (C) + 0.00071 × (D); climbing up 1 stair = 1.308 - 0.016 × (A) + 0.00035 × (D) - 0.000085 × (F) - 0.098 × (G); and climbing up 2 stairs = 1.442 - 0.023 × (A) - 0.000093 × (F) - 0.121 × (G) + 0.0000624 × (E).

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.13-23
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• 2022

In this study, from January 2015 to April 2020, we propose a stochastic volatility model to capture the leverage effect on daily freight yields in the dry cargo market and analyze the freight yields. Estimation involving the Bayesian Markov Chain Monte Carlo method for the leverage effect based on the negative correlation that exists between returns and volatility in stochastic volatility analysis yields similar estimates, and the statistcs indicates significant. That is, the results of the empirical analysis show that the degree of correlation between returns and volatility, and the magnitude and sign of fluctuations differ, which suggests that taking into account the leverage effect in the SV model improves the goodness of fit of the estimates. In addition to the statistical significance of the estimated model's leverage effect, the analysis by log predictive power score presents the estimated results with improved predictive power of the model considering the leveraged effect. These astatistically significant empirical results show that the stochastic volatility model considering the leverage effect is important for freight rate risk modeling in the marine industry.

• Wind and Structures
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• v.37 no.3
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• pp.211-227
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• 2023

To investigate the non-Gaussian feature of fluctuating wind pressures on rectangular high-rise buildings, wind tunnel tests were conducted on scale models with side ratios ranging from 1/9~9 in an open exposure for various wind directions. The high-order statistical moments, time histories, probability density distributions, and peak factors of pressure fluctuations are analyzed. The mixed normal-Weibull distribution, Gumbel-Weibull distribution, and lognormal-Weibull distribution are adopted to fit the probability density distribution of different non-Gaussian wind pressures. Zones of Gaussian and non-Gaussian are classified for rectangular buildings with various side ratios. The results indicate that on the side wall, the non-Gaussian wind pressures are related to the distance from the leading edge. Apart from the non-Gaussianity in the separated flow regions noted by some literature, wind pressures behind the area where reattachment happens present non-Gaussian nature as well. There is a new probability density distribution type of non-Gaussian wind pressure which has both long positive and negative tail found behind the reattachment regions. The correlation coefficient of wind pressures is proved to reflect the non-Gaussianity and a new method to estimate the mean reattachment length of rectangular high-rise building side wall is proposed by evaluating the correlation coefficient. For rectangular high-rise buildings, the mean reattachment length calculated by the correlation coefficient method along the height changes in a parabolic shape. Distributions of Gaussian and non-Gaussian wind pressures vary with side ratios. It is inappropriate to estimate the extreme loads of wind pressures using a fixed peak factor. The trend of the peak factor with side ratios on different walls is given.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• The Journal of Advanced Prosthodontics
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• v.15 no.4
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• pp.171-178
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• 2023

PURPOSE. The purpose of this study was to determine the effect of the connector configuration on the fracture load in conventional and translucent zirconia of three-unit fixed dental prostheses (FDPs). MATERIALS AND METHODS. Six different three-unit FDPs were prepared (n = 6) from three types of zirconia (3Y-TZP (Katana ML^®), 4Y-TZP (Katana STML^®), and 5Y-TZP (Katana UTML^®)) in combination with two connector configurations (4 × 2.25, 3 × 3 mm). The CoCr master models were scanned, and the FDPs were designed and fabricated using CAD-CAM. The FDPs were cemented on the metal model and then loaded with a UTM at a crosshead speed of 1 mm/min until failure. Two-way ANOVA and Tukey's test were used for statistical analysis (α = .05). RESULTS. Fracture loads of 3Y-TZP (2740.6 ± 469.2 and 2718.7 ± 339.0 N for size 4 × 2.25 mm and 3 × 3 mm, respectively) were significantly higher than those of 4Y-TZP (1868.3 ± 281.6 and 1663.6 ± 372.7 N, respectively) and 5Y-TZP (1588.0 ± 255.0 and 1559.1 ± 110.0 N, respectively) (P < .05). No significant difference was found between fracture loads of 4Y-TZP and 5Y-TZP (P > .05). The connector configuration within 9 mm² was found to have no effect on the fracture loads on all three types of zirconia (P > .05). CONCLUSION. Fracture loads of three-unit FDPs were affected by the type of zirconia. The fracture loads of conventional zirconia were higher than those of translucent zirconia. However, it was not affected by the connector configuration when the connector had a cross-sectional area of 9 mm².

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.349-360
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• 2023

Dynamic Nelson-Siegel model is widely used in modeling term structure of interest rates for financial products. In this study, we explain dynamic Nelson-Siegel model from the perspective of the state space model and explore Bayesian approaches that can be applied to that model. By applying SOFR term rate data to the Bayesian dynamic Nelson-Siegel model, we confirm the performance and compare it with other competing models such as Vasicek model, dynamic Nelson-Siegel model based on the frequentist approach, and the two-factor Bayesian dynamic Nelson-Siegel model. We also confirm that the Bayesian dynamic Nelson-Siegel model outperformed its competitors on SOFR term rate data based on RMSE.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.337-347
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• 2023

Sampling designs often use stratified sampling, where elements or clusters of the study population are divided into strata and an independent sample is chosen from each stratum. The stratification strategy consists of stratification and sample allocation, which are important issues that are repeatedly considered in survey sampling. Although a stratified multistage sample design is often used in practice, the literature tends to discuss simple sampling in terms of stratum effects or stratum efficiency. This study examines an existing stratum efficiency measure for two-stage sampling and further proposes additional stratum efficiency measures using the design effect model. The proposed measures are used to evaluate the stratification strategy of the sample design for high school students of the 4^th Korean National Environmental Health Survey (KoNEHS).

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.685-701
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• 2022

FDR is widely used in high-dimensional data inference since it provides more liberal criterion contrary to FWER which is known to be very conservative by controlling Type-1 errors. This paper proposes a sparse VHAR model estimation method controlling FDR by adapting the knockoff introduced by Barber and Candès (2015). We also compare knockoff with conventional method using adaptive Lasso (AL) through extensive simulation study. We observe that AL shows sparsistency and decent forecasting performance, however, AL is not satisfactory in controlling FDR. To be more specific, AL tends to estimate zero coefficients as non-zero coefficients. On the other hand, knockoff controls FDR sufficiently well under desired level, but it finds too sparse model when the sample size is small. However, the knockoff is dramatically improved as sample size increases and the model is getting sparser.

• Journal of Oral Medicine and Pain
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• v.47 no.4
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• pp.198-205
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• 2022

Purpose: The first-line treatment of temporomandibular joint disorders (TMDs) should include self-management and education. Self-management techniques include moist heat application, stretching, diet control, and mandibular rest position adjustment. Although the effectiveness of video educational resources has been studied in multiple sectors, their application in TMD management has not yet been explored. This study seeks to assess how effective media education was at motivating TMD patients to self-management and improve symptoms. Methods: Data were obtained from the hospital records of TMD patients who visited the Department of Oral Medicine, Yonsei University Dental Hospital, between May 2020 and December 2021. First, without any differences between groups, a significance analysis was conducted between the degree of self-management and symptom improvement over time. At the second visit, one group received media education (n=31) linked to TMD management, while the other received written-oriented education (n=45). At the third visit, the number of precautions taken by the patients was determined and contrasted to that recorded in the previous visit between the groups. Generalized estimated equation multivariate models were applied for statistical analysis. Results: In the media education group, the frequency of stretching and the number of patients on pain-free diets increased substantially. Taking precautions improved daily pain intensity, maximum mouth opening, and pain intensity during the maximum unassisted opening. Conclusions: Media education could be beneficial for TMD patients because it allows them to take self-management precautions. The symptoms of the media education group improved, with no considerable distinction between both groups.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.151-160
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• 2023

The Hadith is the second source of Islamic jurisprudence after Qur'an. Both sources are indispensable for muslims to practice Islam. All Ahadith are collected and are written. But most books of Hadith contain Ahadith that can be weak or rejected. So, quite a long time, scholars of Hadith have defined laws, rules and principles of Hadith to know the correct Hadith (Sahih) from the fair (Hassen) and weak (Dhaif). Unfortunately, the application of these rules, laws and principles is done manually by the specialists or students until now. The work presented in this paper is part of the automatic treatment of Hadith, and more specifically, it aims to automatically process the chain of narrators (Hadith Isnad) to find its different components and affect for each component its own tag using a statistical method: the Hidden Markov Models (HMM). This method is a power abstraction for times series data and a robust tool for representing probability distributions over sequences of observations. In this paper, we describe an important tool in the Hadith isnad processing: A chunker with HMM. The role of this tool is to decompose the chain of narrators (Isnad) and determine the tag of each part of Isnad (POI). First, we have compiled a tagset containing 13 tags. Then, we have used these tags to manually conceive a corpus of 100 chains of narrators from "Sahih Alboukhari" and we have extracted a lexicon from this corpus. This lexicon is a set of XML documents based on HPSG features and it contains the information of 134 narrators. After that, we have designed and implemented an analyzer based on HMM that permit to assign for each part of Isnad its proper tag and for each narrator its features. The system was tested on 2661 not duplicated Isnad from "Sahih Alboukhari". The obtained result achieved F-scores of 93%.