• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.35-42
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• 2003

This paper provides the first known flexural vibration data for thick (Mindlin) rectangular plates having V-notches. The V-notch has bending moment and shear force singularities at its sharp corner due to the transverse vibratory bending motion. Based upon Mindlin plate theory, in which transverse shear deformation and rotary inertia effects are considered, the Ritz procedure is employed with a hybrid set of admissible functions assumed for the rotational and transverse vibratory displacements. This set includes: (1) a mathematically complete set of admissible algebraic-trigonometric polynomials which guarantee convergence to exact frequencies as sufficient terms are retained; and (2) an admissible set of Mindlin corner functions which account for the bending moment and shear force singularities at the sharp corner of the V-notch. Extensive convergence studies demonstrate the necessity of adding the Mindlin corner functions to achieve accurate frequencies for rectangular plates having sharp V-notches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• Korean Chemical Engineering Research
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• v.58 no.1
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• pp.106-112
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• 2020

Analyzing vitamin D levels is important for monitoring health conditions because vitamin D deficiency is associated with various diseases such as rickets, osteomalacia, cardiovascular disorders and some cancers. However, vitamin D concentration in the blood is very low with optimal level of 75 nmol/L, making quantitative analysis difficult. The objective of this study was to develop a highly sensitive analysis method for vitamin D using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-MS). 25-hydroxyvitamin D (25(OH)D), which has been used as an indicator of vitamin D metabolites in human biofluids was chemically derivatized using a secosteroid signal enhancing tag (SecoSET) with powerful dienophile and permanent positive charge. The SecoSET-derivatized 25(OH)D provided good linearity (R² > 0.99) and sensitivity (limit of quantitation: 11.3 fmol). Chemical derivatization of deuterated 25-hydroxyvitamin D₃ (d₆-25(OH)D3) with SecoSET enabled absolute quantitative analysis using MALDI-MS. The highly sensitive method could be successfully applied into monitoring of quantitative changes of bioactive vitamin D metabolites after treatment with ketoconazole to inhibit 1α-hydroxylase reaction related to vitamin D metabolism in human breast cancer cells. Taken together, we developed a MALDI-MS-based platform that could quantitatively analyze vitamin D metabolites from cell products, blood and other biofluids. This platform may be applied to monitor various diseases associated with vitamin D deficiency such as rickets, osteomalacia and breast cancer.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.223-229
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• 2014

In an attempt to retrieve useful information for an efficient decision in the large knowledge system, it is generally necessary and important for a refined feature selection. Rough set has difficulty in generating optimal reducts and classifying boundary objects. In this paper, we propose quick reduction algorithm generating optimal features by rough entropy analysis for condition and decision attributes to improve these restrictions. We define a new conditional information entropy for efficient feature extraction and describe procedure of feature selection to classify the significance of features. Through the simulation of 5 datasets from UCI storage, we compare our feature selection approach based on rough set theory with the other selection theories. As the result, our modeling method is more efficient than the previous theories in classification accuracy for feature selection.

• Journal of KSNVE
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• v.9 no.4
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• pp.730-737
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• 1999

This paper illustrates the sound vibration phenomenon of mono type TV set produced by spearker and suggests guidelines for reducing the noise induced by the sound vibrations. In order to illustrate the sound vibration phenomenon, the structural acoustic coupled analysis for the grill and cavity of speaker and structural analysis for main frame are performed. To veify the structural analysis results, experimental modal test is carried out. It is found that the acoustic excitation in the cavity is negligible and main sound vibrations occur near the bottom of TV set. An improved model is found by doing structural modifications based on structural analysis and sound vibration tests are performed to verify the validation of the improved model. The obtained results are applied to similar models and design guide lines for noise reduction are suggested.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.437-448
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• 2016

Gene set analysis utilizing biologic information is expected to produce more interpretable results because the occurrence of tumors (or diseases) is believed to be associated with the regulation of related genes. Many methods have been developed to identify statistically significant gene sets across different phenotypes; however, most focus exclusively on either the differential gene expression or the differential correlation structure in the gene set. This research provides a new method that simultaneously considers the differential expression of genes and differential coexpression with multiple genes in the gene set. Application of this NEW method is illustrated with real microarray data example, p53; subsequently, a simulation study compares its type I error rate and power with GSEA, SAMGS, GSCA and GSNCA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.197-203
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• 2012

This paper studies network recovery method using logical multiple ring architecture embedded in WDM optical Internet environment. The multiple ring-based recovery method provides fast and simple network restoration operation, and performs local recovery that is detouring the failed link. The multiple ring architecture can provide higher resource efficiency by sharing the backup routes and reducing the number of spare wavelengths. This paper calculates the required spare capacity ratio using Cut-Sets in the given network topology and performs simulation for comparative analysis.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.249-274
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• 2022

This study is to focuses on users' attitudes toward augmented reality games. Based on the Technology Acceptance Model (TAM) and Flow theory, continuous usage intention was set as a dependent variable, and immersion was set as a mediating variable. As independent variables, spatial presence, perceived interactivity, perceived pleasure, and sickness were set. Besides, this study strived to compare and analyze Korean and Chinese Data. The results of this study were as follows. First of all, Korean users significantly affected spatial presence, perceived pleasure, and immersion. Spatial presence and perceived pleasure had also mediated effects on continuous usage intention through immersion. However, perceived interactivity and sickness did not affect immersion and even no mediating effect to continuous usage intention. In the case of Chinese users, spatial presence, perceived interactivity, and perceived pleasure were grouped into one variable. This variable influenced immersion and also had mediated effect on continuous usage intention. However, sickness, like Korean users, did not affect the set path. This study had implications for analyzing user perspective using immersion, a significant variable in previous research. In addition, this study found similarities and characteristics through a comparative analysis between Korean and Chinese users indirectly.

• Wind and Structures
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• v.31 no.2
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• pp.143-152
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• 2020

The wind design of buildings is typically based on strength provisions under ultimate loads. This is unlike the ductility-based approach used in seismic design, which allows inelastic actions to take place in the structure under extreme seismic events. This research investigates the application of a similar concept in wind engineering. In seismic design, the elastic forces resulting from an extreme event of high return period are reduced by a load reduction factor chosen by the designer and accordingly a certain ductility capacity needs to be achieved by the structure. Two reasons have triggered the investigation of this ductility-based concept under wind loads. Firstly, there is a trend in the design codes to increase the return period used in wind design approaching the large return period used in seismic design. Secondly, the structure always possesses a certain level of ductility that the wind design does not benefit from. Many technical issues arise when applying a ductility-based approach under wind loads. The use of reduced design loads will lead to the design of a more flexible structure with larger natural periods. While this might be beneficial for seismic response, it is not necessarily the case for the wind response, where increasing the flexibility is expected to increase the fluctuating response. This particular issue is examined by considering a case study of a sixty-five-story high-rise building previously tested at the Boundary Layer Wind Tunnel Laboratory at the University of Western Ontario using a pressure model. A three-dimensional finite element model is developed for the building. The wind pressures from the tested rigid model are applied to the finite element model and a time history dynamic analysis is conducted. The time history variation of the straining actions on various structure elements of the building are evaluated and decomposed into mean, background and fluctuating components. A reduction factor is applied to the fluctuating components and a modified time history response of the straining actions is calculated. The building components are redesigned under this set of reduced straining actions and its fundamental period is then evaluated. A new set of loads is calculated based on the modified period and is compared to the set of loads associated with the original structure. This is followed by non-linear static pushover analysis conducted individually on each shear wall module after redesigning these walls. The ductility demand of shear walls with reduced cross sections is assessed to justify the application of the load reduction factor "R".