• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3637-3641
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• 2014

In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted $EC_{50}$. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/water partition coefficient (Pow) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR $EC_{50}$ equation = $1.76997-1.12249{\times}TOL+1.21045{\times}MEK$), as well as to SG, VP, and LEL (MLR equation $EC_{50}=15.44388-19.84549{\times}SG+0.05091{\times}VP+1.85846{\times}LEL$). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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• pp.699-710
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• 2006

The objective of this study was to identify the texture-related components of woven fabrics and to develop a multidimensional perceptual structure map to represent the tactile textures. Eighty subjects in clothing and tektite industries were selected for multivariate data on each fabric of 30 using the questionnaire with 9 pointed semantic differential scales of 20 texture-related adjectives. Data were analyzed by factor analysis, hierarchical cluster analysis, and multidimensional scaling(MDS) using SPSS statistical package. The results showed that the five factors were selected and composed of density/warmth-coolness, stiffness, extensibility, drapeability, and surface/slipperiness. As a result of hierarchical cluster analysis, 30 fabrics were grouped by four clusters; each cluster was named with density/warmth-coolness, surface/slipperiness, stiffness, and extensibility, respectively. By MDS, three dimensions of tactile texture were obtained and a 3-dimensional perceptual structure map was suggested. The three dimensions were named as surface/slipperiness, extensibility, and stiffness. We proposed a positioning perceptual map of fabrics related to texture naming system(TNS). To classify the textural features of the woven fabrics, hierarchical cluster analysis containing all the data variations, even though it includes the errors, may be more desirable than texture-related multidimensional data analysis based on factor loading values in respect of the effective variables reduction without losing the critical variations.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.138-146
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• 2007

Geotechnical performance at the soft ground is strongly dependent on the properties of the soil beneath and adjacent to the structure of interest. These soil properties can be described using deterministic and/or probabilistic models. Deterministic models typically use a single discrete descriptor for the parameter of interest. Probabilistic models describe parameters by using discrete statistical descriptors or probability distribution density functions. The consolidation process depends on several uncertain parameters including the coefficients of consolidation and coefficients of permeability in vertical and horizontal directions. The implication of this uncertain parameter in the design of prefabricated vertical drains for soil improvement is discussed. A sensitivity analysis of the degree of consolidation and calculation of settlements to these uncertain parameters is presented for clayey deposits.

• Nuclear Engineering and Technology
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• v.20 no.4
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• pp.253-264
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• 1988

Our experience of neutron noise analysis in French-type 900 MWe pressurized water reactor (PWR) is presented. Neutron noise analysis is based on the technique of interpreting the signal fluctuations of ex-core detectors caused by core reactivity changes and neutron attenuation due to lateral core motion. It also provides advantages over deterministic dynamic-testing techniques because existing plant instrumentation can be utilized and normal operation of the plant is not disturbed. The data of this paper were obtained in the ULJIN unit 1 reactor during the start-up test period and the statistical descriptors, useful for our purpose, are power spectral density (PSD), coherence function (CF), and phase difference between detectors. It is found that core support barrel (CSB) motions induced by coolant flow forces and pressure pulsations in a reactor vessel were indentified around 8 Hz of frequency.

• The Korean Journal of Pesticide Science
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• v.11 no.2
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• pp.72-81
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• 2007

Quantitative structure-activity relationships (QSARs) on the pre-emergency herbicidal activity and reactivity of a series of new O,O-dialkyl-1-phenoxyacetoxy-1-methylphosphonates (S) analogues against seed of cucumber (Cucumus Sativa) were discussed quantitatively using 2D-QSAR and HQSAR methods. The statistical values of HQSAR model were better than that of 2D-QSAR model. From the frontier molecular orbital (FMO) interaction between substrate molecule (S) and $BH^+$ ion (I) in PDH enzyme, the electrophilic reaction was superior in reactivity. From the effect of substituents, $R_2$-groups in substrate molecule (S) contributed to electrophilic reaction with carbonyl oxygen atom while X, Y-groups contributed to nucleophilic reaction with carbonyl carbon atom. And the influence of X,Y-groups was more effective than that of $R_2$-groups. As a results of 2D-QSAR model (I & II) and atomic contribution maps with HQSAR model, the more length of X, Y-groups is longer, the more herbicidal activity tends to increased. And also, the optimal ${\epsilon}LUMO$ energy, $({\epsilon}LUMO)_{opt.}$=-0.479 (e.v.) of substrate molecule is important factor in determining the herbicidal activity. It is predicted that the herbicidal activity proceeds through a nucleophilic reaction. From the analytical results of 2D-QSAR and HQSAR model, it is suggested that the structural distinctions and descriptors that contribute to herbicidal activities will be able to applied new herbicide design.

• Convergence Security Journal
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• v.19 no.2
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• pp.91-104
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• 2019

In this paper, we present a novel local descriptor, Local Prominent Directional Pattern (LPDP), to represent the description of facial images for gender recognition purpose. To achieve a clearly discriminative representation of local shape, presented method encodes a target pixel with the prominent directional variations in local structure from an analysis of statistics encompassed in the histogram of such directional variations. Use of the statistical information comes from the observation that a local neighboring region, having an edge going through it, demonstrate similar gradient directions, and hence, the prominent accumulations, accumulated from such gradient directions provide a solid base to represent the shape of that local structure. Unlike the sole use of gradient direction of a target pixel in existing methods, our coding scheme selects prominent edge directions accumulated from more samples (e.g., surrounding neighboring pixels), which, in turn, minimizes the effect of noise by suppressing the noisy accumulations of single or fewer samples. In this way, the presented encoding strategy provides the more discriminative shape of local structures while ensuring robustness to subtle changes such as local noise. We conduct extensive experiments on gender recognition datasets containing a wide range of challenges such as illumination, expression, age, and pose variations as well as sketch images, and observe the better performance of LPDP descriptor against existing local descriptors.

• Applied Biological Chemistry
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• v.48 no.1
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• pp.82-88
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• 2005

3D QSAR studies for the fungicidal activities against resistive phytophthora blight (RPC; 95CC7303) and sensitive phytophthora blight (Phytopthora capsici) (SPC; 95CC7105) by a series of new 2-alkoxyphenyl-3-phenylthioisoindoline-1-one derivatives (X: A=propynyl & B=2-chloropropenyl) were studied using comparative molecular field analyses (CoMFA) methodology. The CoMFA models were generated from the two different alignment, atom based fit (AF) alignment and field fit (FF) alignment. The atom based alignment exhibited a higher statistical results than that of field fit alignment. The best models, A3 and A7 using combination fields of H-bond field, standard field, LUMO and HOMO molecular orbital field as additional descriptors were selected to improve the statistic of the present CoMFA models. The statistical results of the two models showed the best predictability of the fungicidal activities based on the cross-validated value $q^2\;(r^2_{cv.}=RPC:\;0.625\;&\;SPC:\;0.834)$, non cross-validated value $(r^2_{ncv.}=RPC:\;0.894\;&\;SPC:\;0.915)$ and PRESS value (RPC: 0.105 & SPC: 0.103), respectively. Based on the findings, the predictive ability and fitness of the model for SPC was better than that of the model for RPC. The fugicidal activities exhibited a strong correlation with steric $(66.8{\sim}82.8%)$, electrostatic $(10.3{\sim}4.6%)$ and molecular orbital field (SPC: HOMO, 12.6% and RPC: LUMO, 22.9%) factors of the molecules. The novel selective character for fungicidal activity between two fungi depend on the positive charge of ortho, meta-positions on the N-phenyl ring and size of hydrophilicity of a substituents on the S-phenyl ring.

• Applied Biological Chemistry
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• v.47 no.4
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• pp.414-421
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• 2004

3D QSAR studies for protox inhibition activities against root and shoot of the rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene derivatives were conducted based on the results (Sung, N. D. et al.'s, (2004) J. Korean Soc. Appl. Biol. Chem. 47(3), 351-356) using comparative molecular similarity indices analysis (CoMSIA) methodology. Four CoMSIA models, without hydrogen bond donor field for the protox inhibition activities against root and shoot of the two plants, were derived from the combination of several fields using steric field, hydrophobic field, hydrogen bond acceptor field, LUMO molecular orbital field, dipole moment (DM) and molar refractivity (MR) as additional descriptors. The predictabilities and fitness of CoMSIA models for protox inhibition activities against barnyard-grass were higher than that of rice plant. The statistical results of these models showed the best predictability of the protox inhibition activities against barnyard-grass based on the cross-validated value $r^2\;_{cv}\;(q^2=0.635{\sim}0.924)$, non cross-validated, conventional coefficient $r^2\;_{ncv.}$ value $(r^2=0.928{\sim}0.977)$ and PRESS value $(0.255{\sim}0.273)$. The protox inhibition activities exhibited a strong correlation with the steric $(5.4{\sim}15.7%)$ and hydrophobic $(68.0{\sim}84.3%)$ factors of the molecules. Particularly, the CoMSIA models indicated that the groups of increasing steric bulk at ortho-position on the C-phenyl ring will enhance the protox inhibition activities against barnyard-grass and subsequently increase the selectivity.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.