• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.321-327
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• 2014

In this paper, linear dynamic equations are derived from nonlinear dynamic equations of constrained multibody systems using the QR decomposition method. The derived linear equations are applied to a railway vehicle bogie. The vibration characteristics of the railway vehicle are investigated by calculating the natural mode and transfer function of the bogie frame in relation to rail-roughness input. The main modes of the bogie were found below 35Hz, and the local modes above 198Hz. The magnitude of the vertical transfer function varied with the forward velocity due to vertical and pitch modes, which were influenced by the forward velocity. The magnitude of the lateral transfer function was negligibly small, and the mode in the longitudinal direction was excited for longitudinal transfer function regardless of the forward velocity.

• Steel and Composite Structures
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• v.8 no.5
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• pp.389-402
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• 2008

In December 2005, one(A) of the two pre-engineered warehouse buildings in the port of K City of Korea was completely destroyed and the other(B) was seriously damaged to be demolished. Over-loaded snow and unexpected blast of wind were the causes of the accident and destructive behavior was brittle fracture caused by web local buckling and lateral torsional buckling at the flange below rafter. However, the architectural design technology of today based on material non-linear method does not consider the tolerances to solve the problem of such brittle fracture. So, geometric non-linear evaluation which includes initial deformation, width-thickness ratio, web stiffener and unbraced length is required. This study evaluates the structural safety of 4 models in terms of width-thickness ratio and unbraced length using ANSYS 9.0 with parameters such as width-thickness ratio of web, existence/non-existence of stiffener and unbraced length. The purpose of this study is to analyze destructive mechanism of the above-mentioned two warehouse buildings and to provide ways to promote the safety of pre-engineered buildings.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.143-156
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• 2022

This article examines the effect of inward foreign direct investments (FDI) on the export performance of micro, small & medium enterprises (MSMEs) in India, and investigates the spillover impact and absorption capacity of the MSMEs sector. For the first time, the researchers applied the intersectoral linkage approach to investigate the matter and used a panel dataset between 2006 and 2017. The coefficients of forward and backward linkages are estimated by using the Rasmussen method, the study employs a basic linear panel data model, followed by various diagnostic tests to identify the problem of heteroscedasticity, autocorrelation / serial correlation, cross-sectional dependencies, multicollinearity, time-individual specific tests, and unobserved effects. The PCSE model was applied for robust standard error and the Hausman-Taylor IV model to check the robustness of the result generated in the linear panel data model. Despite the high prevalence of forward and backward intersectoral connections and the Lack of absorption capacity of local firms, the results show that FDI has little of an impact on the export performance of micro, small, and medium-sized businesses in India. This study adds to the existing literature on determining local firms' spillover effect and absorption capacity in response to inward FDI.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.55-56
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• 2022

Hypertension is a severe health problem and increases the risk of other health issues, such as heart disease, heart attack, and stroke. In this research, we propose a machine learning-based prediction method for the risk of chronic hypertension. The proposed method consists of four main modules. In the first module, the linear interpolation method fills missing values of the integration of gas and meteorological datasets. In the second module, the OrdinalEncoder-based normalization is followed by the Decision tree algorithm to select important features. The prediction analysis module builds three models based on k-Nearest Neighbors, Decision Tree, and Random Forest to predict hypertension levels. Finally, the features used in the prediction model are explained by the DeepSHAP approach. The proposed method is evaluated by integrating the Korean meteorological agency dataset, natural gas leakage dataset, and Korean National Health and Nutrition Examination Survey dataset. The experimental results showed important global features for the hypertension of the entire population and local components for particular patients. Based on the local explanation results for a randomly selected 65-year-old male, the effect of hypertension increased from 0.694 to 1.249 when age increased by 0.37 and gas loss increased by 0.17. Therefore, it is concluded that gas loss is the cause of high blood pressure.

• Computational Structural Engineering
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• v.8 no.4
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• pp.129-136
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• 1995

This paper presents a boundary element method for obtaining approximate solutions of 2-dimensional consolidation problems based on the Biot's linear theory. Laplace transform is applied to differential equation system in order to eliminate the time dependency. The boundary integral equations in transformed space are formulated and the fundamental solutions are shown in a closed form. In order to convert the transformed solutions to the ones in real space, the Hosono's numerical Laplace transform inversion method is applied. As a numerical example, a half-space consolidation problem subjected to a strip local load is selected and the applicability of the method is demonstrated through the comparison with the exact solutions.

• Steel and Composite Structures
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• v.26 no.4
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• pp.439-452
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• 2018

This paper presents experimental and numerical study on buckling behaviors and hysteretic performance of Class 1 H-shaped steel beam subjected to cyclic pure bending within the scope of ultra-low cycle fatigue (ULCF). A loading device was designed to achieve the pure bending loading condition and 4 H-shaped specimens with a small width-to-thickness ratio were tested under 4 different loading histories. The emphasis of this work is on the impacts induced by local buckling and subsequent ductile fracture. The experimental and numerical results indicate that the specimen failure is mainly induced by elasto-plastic local buckling, and is closely correlated with the plastic straining history. Compared with monotonic loading, the elasto-plastic local buckling can occur at a much smaller displacement amplitude due to a number of preceding plastic reversals with relative small strain amplitudes, which is mainly correlated with decreasing tangent modulus of the material under cyclic straining. Ductile fracture is found to be a secondary factor leading to deterioration of the load-carrying capacity. In addition, a new ULCF life evaluation method is proposed for the specimens using the concept of energy decomposition, where the cumulative plastic energy is classified into two categories as isotropic hardening and kinematic hardening correlated. A linear correlation between the two energies is found and formulated, which compares well with the experimental results.

• Journal of Dental Anesthesia and Pain Medicine
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• v.17 no.3
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• pp.183-190
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• 2017

Background: It is important to evaluate preoperative anxiety and prepare sedation when performing dental surgery under local anesthesia. Spielberger's State-Trait Anxiety Inventory (STAI) is useful for predicting preoperative anxiety. State anxiety is defined as a subjective feeling of nervousness. Reduction in the number of the state anxiety items (questions) will be clinically important in allowing us to predict anxiety more easily. Method: We analyzed the STAI responses from 1,252 patients who visited our institution to undergo dental surgery under local anesthesia. Multiple linear regression analysis was conducted for 9 groups comprising anxiety level determinations using the STAI; we then developed a coefficient of determination and a regression formula. We searched for a group satisfying the largest number of requirements for regression expression while setting any necessary conditions for accurately predicting anxiety before dental surgery under local anesthesia. Results: The regression expression from the group determined as normal for preoperative state anxiety was deemed the most suitable for predicting preoperative anxiety. Conclusion: It was possible to reduce the number of items in the STAI by focusing on "Preoperative anxiety before dental surgery."

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.795-802
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• 2020

This study seeks to determine the effect of the application of accounting information system (AIS), internal control system, and human resource (HR) competency on the quality of local government financial statements (FS). This study uses agency theory and compliance theory. Agency theory is used to explain that there is a link between the society as the principal and the government as the agent. Compliance theory is a theory, which states that every agency is obliged to comply with regulations because the law-drafting authority has the right to dictate behavior. The population in this study were employees of the financial division of local government organizations in one of the districts in Central Java, Indonesia. The total samples in this study was 106 respondents. The data used are primary data taken from distributing questionnaires to respondents. The method of analysis used to test the hypothesis was multiple linear regression analysis. The results of hypothesis testing indicate that HR competency has an effect on the quality of FS; however, the application of AIS and internal control system has no effect on the quality of FS. The implication of this research underlines the importance of HR competency to improve the quality of local government FS.

• Journal of The Korean Astronomical Society
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• v.44 no.2
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• pp.59-65
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• 2011

A small number of active galactic nuclei are known to exhibit prominent double peak emission profiles that are well-fitted by a relativistic accretion disk model. We develop a Monte Carlo code to compute the linear polarization of a double peaked broad emission line arising from Thomson scattering. A Keplerian accretion disk is adopted for the double peak emission line region and the geometry is assumed to be Schwarzschild. Far from the accretion disk where flat Minkowski geometry is appropriate, we place an azimuthally symmetric scattering region in the shape of a spherical shell sliced with ${\Delta}{\mu}=0.1$. Adopting a Monte Carlo method we generate line photons in the accretion disk in arbitrary directions in the local rest frame and follow the geodesic paths of the photons until they hit the scattering region. The profile of the polarized flux is mainly determined by the relative location of the scattering region with respect to the emission source. When the scattering region is in the polar direction, the degree of linear polarization also shows a double peak structure. Under favorable conditions we show that up to 0.6% linear polarization may be obtained. We conclude that spectropolarimetry can be a powerful probe to reveal much information regarding the accretion disk geometry of these active galactic nuclei.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.301-303
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• 2003

The extraction of 3D road network from high-resolution aerial images is still one of the current challenges in digital photogrammetry and computer vision. For many years, there are many researcher groups working for this task, but unt il now, there are no papers for doing this with TLS (Three linear scanner), which has been developed for the past several years, and has very high-resolution (about 3 cm in ground resolution). In this paper, we present a methodology of road extraction from high-resolution digital imagery taken over urban areas using this modern photogrammetry’s scanner (TLS). The key features of the approach are: (1) Because of high resolution of TLS image, our extraction method is especially designed for constructing 3D road map for next -generation digital navigation map; (2) for extracting road, we use the global context of the intensity variations associated with different features of road (i.e. zebra line and center line), prior to any local edge. So extraction can become comparatively easy, because we can use different special edge detector according different features. The results achieved with our approach show that it is possible and economic to extract 3D road data from Three Linear Scanner to construct next -generation digital navigation road map.