• Research in Mathematical Education
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• v.15 no.1
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• pp.81-91
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• 2011

The aim of this study was to explore the grade 1-3 students' geometrical thinking level descriptors based on van Hiele level descriptors. The data were collected through collection of geometric curriculum materials such as indicators and learning standards in Basic Education Core Curriculum and mathematics textbook for grades 1-3. The findings were found that 1) Inconsistency between descriptors appeared on mathematics curriculum and Thai mathematics textbooks. 2) Using topics on textbooks as criterion for exploring 5 of 7 descriptors appeared on Thai mathematics textbook indicated geometrical thinking levels based on van Hiele's model merely level 0 (Visualization) across textbooks for grades 1-3.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.2009-2016
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• 2008

The relationship between thermal decomposition temperature and structure of a new data set of eighty monomers of different polymers were studied by multiple linear regression (MLR). The stepwise method was used in order to variable selection. The best descriptors were selected from over 1400 descriptors including; topological, geometrical, electronic and hybrid descriptors. The effect of number of descriptors on the correlation coefficient (R) and F-ratio were considered. Two models were suggested, one model having four descriptors ($R^2$ = 0.894, $Q^2_{cv}$ = 0.900, F = 172.1) and other model involving 13 descriptors ($R^2$ = 0.956, $Q^2_{cv}$ = 0.956, F = 125.4).

• Environmental Analysis Health and Toxicology
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• v.14 no.3
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• pp.103-111
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• 1999

To effectively predict the lipophilicity, the aryl hydrocarbon receptor (AhR) affinity, and TEF (Toxic equivalency factor) of dioxins by geometrical descriptors, the multiple linear regression methods with the forward selection and backward elimination were employed with statistical validity. The lipophilicity, the Ah receptor binding affinity, and the toxic equivalency factor of dioxins could be predicted using some geometrical descriptors.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.23-30
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• 2014

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.

• Environmental Analysis Health and Toxicology
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• v.14 no.1_2
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• pp.65-73
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• 1999

Dioxins refer to a family of chemicals comprising 75 polychlorinated dibenzo-p-dioxin (PCDD) and 135 polychlorinated dibenzo-p-furan (PCDF) congeners, which may cause skin disorder, human immune system disruption, birth defects, severe hormonal imbalance, and cancer. The effects of exposure of dioxin-like compounds such as PCBs are mediated by binding to the aryl hydrocarbon receptor (AHR), which is a ligand-activated transcription factor. To grasp physicochemical factors affecting human toxicity of dioxins, six geometrical and topological indices, eleven thermodynamic variables, and quantum mechanical descriptors including ESP (electrostatic potential) were analyzed using QSAR and semi-empirical AM1 method. Planar dioxins with high lipophilicity and large surface tension show the probability that negative electrostatic potential in the lateral oxygen may make hydrogen bonding with DNA bases to be a carcinogen.

• Journal of Biomedical Engineering Research
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• v.18 no.1
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• pp.9-16
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• 1997

We develop an automatic imaging matching technique for combining portal image and simulator image for improvements in localization of treatment in radiation therapy. Fusion of images from two imaging modalities is treated as follows. We archive images thxough a frame-yabber. The simulator and portal images are edge detected and enhanced with interpolated adaptive histouam equalization and combined using geometrical parameters relating the coordinates of two image data sets which are calculated using Fourier descriptors. We don't use any kind of imaging markers for patient's convenience. clinical use of this image matching technique for treatment planning will result in improvements in localization of treatment volumes and critical structures. These improvements will allow greater sparing of normal tissues and more precise delivery of energy to the desired irradiation volume.