• 대한원격탐사학회지
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• 제18권2호
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• pp.97-105
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• 2002

In this paper, we proposed a simplified strategy for the epipolarity of linear pushbroom imagery. The proposed strategy is verified on "Gupta and Hartly" sensor model and "Orun and Natarajan" sensor model. It is also compared with the precise epipolarity model of each sensor model on SPOT and KOMPSAT imagery. For the quantitative analysis, 20 ground control points are used as independent checking points. Based on the results, the accuracy of the proposed strategy is not different from that of the precise epipolarity model of each sensor model (below 0.1 pixels). Under the worst circumstance, the proposed strategy is robust. We can assure that the proposed strategy will show high accuracy on most of sensor models based on the co-linearity equations.

• 산업경영시스템학회지
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• 제8권11호
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• pp.27-34
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• 1985

Recently the distributed lag models for time series data have been used in several quantitative analyses. But the analyses of time series which have the serial correlations in error terms and the lagged values of dependent variables violate the hypothesis of OLS method. This paper suggests that the approach technique of distributed lay model with serial correlation should be applied by the Bayesian inference to estimate the parameters. For the application of distributed lag model by Bayesian analysis, the data for monthly consumption expenditure per household by items of commodities from 1972 to 1981 are used in order to estimate the lagged coefficient of processed food and the regression coefficient of the food and beverage.

• 대한안전경영과학회지
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• 제14권4호
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• pp.23-29
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• 2012

There are insufficient models that find problems and solutions for accident prevention through risk assessment and suggest safe work process and work instruction from foundation works to finish work for accident decrease. This paper presents a quantitative risk assessment model by analysis of risk factors in each process such as appurtenant works, temporary works, structural works, equipment work, finishing work and etc based on accident examples and investigation on actual condition in plants construction work. In addition, the safety management system was developed to perform risk assessment of plants construction and use it for effective safety training for labor.

• 통합자연과학논문집
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• 제5권1호
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• pp.1-5
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• 2012

Quantitative structure-activity relationship (QSAR) methodologies have been applied for many years, to correlate the relationship between physicochemical properties of chemical substances and their biological activities to generate a statistical model for prediction of the activities of new chemical entities. The basic principle behind the QSAR models is that, how structural variation is responsible for the difference in biological activities of the compounds. 3D-QSAR has emerged as a natural extension to the classical Hansch and Free-Wilson approaches, which develops the 3D properties of the ligands to predict their biological activities using various chemometric techniques (PLS, G/PLS, ANN etc). It has served as a valuable predictive tool in the design of pharmaceuticals and agrochemicals. This review seeks to provide different 3D-QSAR approaches involved in drug designing process to develop structure-activity relationships and also discussed the fundamental limitations, as well as those that might be overcome with the improved methodologies.

• 드라이브 ㆍ 컨트롤
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• 제16권2호
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• pp.66-71
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• 2019

In this study, flow analysis and dehumidification experiments were performed on hollow fiber membrane module to confirm the dehumidification characteristics for its different configurations. The CFD for the three different models was conducted using $30^{\circ}C$ temperature and 30%RH inlet humidity for quantitative analysis. Each model has different shape parameters i.e. the number of baffles. Comparison between flow analysis results and dehumidification experiment results revealed a percentage error of about 5%. The difference in relative humidity between the inlet and outlet for each model was calculated using flow analysis data. It was established that the difference in relative humidity of the inlet and outlet for the refined model with three baffles was highest among the three modeled modules of hollow fiber membrane module, i.e. around 9%.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.399-409
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• 2019

Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.

• 천문학회보
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• 제44권1호
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• pp.47.1-47.1
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• 2019

A gas giant formed in a massive protoplanetary disk via gravitational instability migrates inward due to its gravitational interaction with the disk. Planet migration occurs in various ways depending on the disk structure and internal processes, but previous studies only considered quantitative radiative feedback resulting from mass accretion onto the planet. Allowing for accretion feedback, we perform three-dimensional hydrodynamic simulations with GIZMO to investigate orbital evolution of giant planets in a protoplanetary subject to -cooling. This work shows a planet gains mass due to accretion and gradually opens a gap as it moves inward. The migration in the end halts when the planet clears the gas around its orbit. A more massive planet grows its mass faster and migrates more rapidly, stalling at an orbit farther away from the protostar. Models with a cold disk readily construct a circumplanetary disk and result in high mass growth of the planet. Accretion feedback, in general, reduces the rate of the planet growth and delays migration. We discuss our results with GIZMO in comparison with the previous results with different codes.

• Computers and Concrete
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• 제24권5호
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• pp.469-488
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• 2019

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.

• 패션비즈니스
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• 제24권6호
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• pp.63-79
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• 2020

This study analyze consumers' unconscious visual attention to color and images of internet shopping malls by using eye-tracking method. Twenty-nine participants, including 15 females and 14 males, participated. The average ages of the male and female participants were 27.3 years and 27.7 years, respectively. Ten images of five layouts (multi-composition images, single-model images, gender-composed images, videos, and moving banner images) of internet shopping malls were shown on an eye-tracker computer screen. Quantitative analyses of the eye-tracking responses were conducted. SPSS was used to analyze the descriptive characteristics and to conduct an independent-sample t-test, along with an ANOVA. The data analysis showed that the image area generally had the shortest time to first fixation (TFF), the longest duration of fixation (DOF), the highest number of fixations (NOF), and the highest numbers of revisits(NOR).Notably, visual attention towards female models was high among various images. The results can be used to improve credibility and design online shopping layout with a scientific evidence that helps consumers through their purchase decisions.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.281-286
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• 2023

Diagnosing reading disorders involves complex procedures to evaluate complex cognitive processes. For an accurate diagnosis, a series of tests and evaluations by human experts are required. In this study, we propose a quantitative tool to diagnose reading disorders based on natural reading behaviors using minimal human input. The eye movements of the third- and fourth-grade students were recorded while they read a text at their own pace. Seven machine learning models were used to evaluate the gaze patterns of the words in the presented text and classify the students as normal or having a reading disorder. The accuracy of the machine learning-based diagnosis was measured using the diagnosis by human experts as the ground truth. The highest accuracy of 0.8 was achieved by the support vector machine and random forest classifiers. This result demonstrated that machine learning-based automated diagnosis could substitute for the traditional diagnosis of reading disorders and enable large-scale screening for students at an early age.