• Korean journal of food and cookery science
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• v.15 no.3
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• pp.203-209
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• 1999

The effect of several hydrocolloids on the rheological behavior of wheat flour was investigated. The influence of the selected hydrocolloids (alginate, carrageenan, CMC, guar, locustbean and xanthan) on wheat flour was tested by using two different techniques; amylograph and texture analyzer. In order to have a general overview of their effects hydrocolloids were chosen from different sources implying a broad diversity of chemical structures. The hydrocolloid addition decreased the brightness(L) but increased yellowness(b). The interaction between hydrocolloid and flour produces a slight modification of the amylogram parameters, being the most clearly affected parameter breakdown, which is increased by carrageenan, guar and xanthan. Hardness and cutting force were augmented by hydrocolloid addition, while springeness was decreased except guar and locustbean. In summary, when looking for the improvement of the noodle texture, guar, locustbean are the best candidate additives due to their effects on pasting and texture properties. These hydrocolloids increase the hardness, cutting force, gumness, chew-ness, so were thought to increase the eating quality. So, each tested hydrocolloid affected in a different way the rheological properties of wheat flour, the results obtained are important for the appropriate use of these hydrocolloid as ingredients in the noodle making process.

• Korean Journal of Food Science and Technology
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• v.50 no.5
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• pp.499-503
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• 2018

Transglutaminase (TGase), which forms linkages among proteins, has been used to improve food quality. In the current study, quality characteristics such as color values, texture profile parameters, and sensory profiles of the frozen surichwi (Synurus deltoids) rice cake made using transglutaminase (TGase) treated-rice flour were investigated, with a view to producing high-value rice products. The results indicate that Hunter color values (L and b) and TPA parameter values (hardness, gumminess and chewiness) of frozen surichwi rice cake made with TGase-treated rice flour were significantly changed, and that these properties may be applied to improve the sensory qualities of final products. Also, the sensory acceptability scores related to color, appearance, taste and texture, as well as overall acceptability of the TGase-treated frozen surichwi rice cake, were found to be significantly higher compared to controls. In conclusion, the results clearly indicate that TGase-treated rice flour carries the potential to improve the overall quality of frozen rice cake, and that surichwi is an effective ingredient for sensory profiles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.43-57
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• 2009

Integrating 3D data acquired in multiple views is one of the most important techniques in 3D modeling. However, the existing integration methods are sensitive to registration errors and surface scanning noise. In this paper, we propose a integration algorithm using the local surface topology. We first find all boundary vertex pairs satisfying a prescribed geometric condition in the areas between neighboring surfaces, and then separates areas to several regions by using boundary vertex pairs. We next compute best fitting planes suitable to each regions through PCA(Principal Component Analysis). They are used to produce triangles that be inserted into empty areas between neighboring surfaces. Since each regions between neighboring surfaces can be integrated by using local surface topology, a proposed method is robust to registration errors and surface scanning noise. We also propose a method integrating of textures by using parameterization technique. We first transforms integrated surface into initial viewpoints of each surfaces. We then project each textures to transformed integrated surface. They will be then assigned into parameter domain for integrated surface and be integrated according to the seaming lines for surfaces. Experimental results show that the proposed method is efficient to face modeling.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.179-191
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• 2016

In addition to the measurement of the concentration of soil contaminants, the new idea of indicative parameters was proposed to validate the remedial works through the monitoring for the changes of soil characteristics after applying the clean up technologies. The parameters like CFU (colony forming unit), pH and soil texture were recommended as indicative parameters for land farming. In case of soil washing, water content and the particle size distribution of the sludge were recommended as indicative parameters. The sludge is produced through the particle separation process in soil washing and it is usually treated as a waste. The parameters like water content, organic matter content, CEC (cation exchange capacity) and CFU were recommended as indicative parameters for the low temperature thermal desorption method. Besides the indicative parameter, sampling methods in stock pile and the optimal minimum amount of composite soil sample were proposed. The rates of sampling error in regular grid, zigzag, four bearing, random grid methods were 17.3%, 17.6%, 17.2% and 16.5% respectively. The random grid method showed the minimum sampling error among the 4 kinds of sampling methods although the differences in sampling errors were very little. Therefore the random grid method was recommended as an appropriate sampling method in stock pile. It was not possible to propose a value of optimal minimum amount of composite soil sample based on the real analytical data due to the dynamic variation of $CV_{fund{\cdot}error}$. Instead of this, 355 g of soil was recommended for the optimal minimum amount of composite soil sample under the assumption of ISO 10381-8.

• Journal of Periodontal and Implant Science
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• v.27 no.3
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• pp.495-514
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• 1997

The purpose of this study was to evaluate the in vitro effects of Nd:YAG laser irradiation on removal of a root surface smear layer after root planing in comparison with Tetracycline HCl. The 60 extracted human teeth due to severe periodontal disease were vigorously scaled and root planed with Gracey curet. Thirty specimen($5{\times}5{\times}2mm$) were obtained from root planed surface of 30 human teeth and assigned randomly to one of three groups : root planed group(5 specimen), Tetracycline HCI group(5 specimen, burnished for 5 minutes), and Nd:YAG laser group(25 specimen, German Dental Laser, Fotona Twinlight). Nd:YAG laser group was divided into 4 subgroups according to power of 1W, 1.5W, 2W, 3W at frequency to 10Hz. The specimen were then fixed, and examed by Scanning electron microscopic study. 30 of 60 human teeth used to measurement of the intrapulpal temperature rise during laser irradiation. Laser-irradiated surface exhibited various surface texture from relative flat surface to irregular surface with patent dentinal tubules of various shape and size. In some area, the root surface alteration which are carbonization, pit and crater formation and melting and resolidification were observed. The number of exposed dentinal tubules per unit($100_{\mu}m^2$) on tetracycline HCI group was more than that in the laser group below 1.5W of power(150mJ/pulse) and was significantly less than that in laser group above 2W of power(200mJ/pulse)(P<0.OOl). As power increased the intrapulpal temperature rise also increased. The result suggested that the parameter which effectively remove root surface smear layer than tetracycline HCI may cause thermal damage to pulp and root surface alteration result from laser exposure would indicate need for additional instrumentation. Thus, Nd:YAG laser irradiation in these parameter may not be appropriate for clinical use as adjunct to conventional periodontal therapy.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.147-158
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• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.

• Korean Journal of Materials Research
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• v.4 no.4
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• pp.445-452
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• 1994

Three-axial deformation behavior of the Zircaloy cladding tube under the irradiation condition of the fuel in pressurized water reactor can be analyzed by the anisotropy in the creep and the irra- diation growth, which depends on the texture parameter. A methodology to evaluate the impact of the anisotropic creep and irradiation growth on the strain in each axial direction of the cladding tube has been proposed. Based on the measured strains after irradiation and predicted ones with the help of a fuel performance analysis code, it is found that a tangential strain of the cladding tube is caused mainly by the creep, whereas a axial strain of the cladding is caused mainly by the irradiation growth but with a considerable contribution of the creep at low irradiation.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.17-33
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• 2005

This paper presents the proposed a classifier of liver cirrhotic step using MR(magnetic resonance) imaging and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were analysis in the number of data was 231. We extracted liver region and nodule region from T1-weight MR liver image. Then objective interpretation classifier of liver cirrhotic steps. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier learned through error back-propagation algorithm. A classifying result shows that recognition rate of normal is $100\%$, 1type is $82.8\%$, 2type is $87.1\%$, 3type is $84.2\%$. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.7
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• pp.414-420
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• 2004

Among the desirable properties of a piecewise linear parameterization, guaranteeing a one-to-one mapping (i.e., no triangle flips in the parameter plane) is often sought. A one-to-one mapping is accomplished by non-negative coefficients in the affine transformation. In the Floater's method, the coefficients were computed after the 3D mesh was flattened by geodesic polar-mapping. But using this geodesic polar map introduces unnecessary local distortion. In this paper, a simple variant of the original shape-preserving mapping technique by Floater is introduced. A new simple method for calculating barycentric coordinates by using straightest geodesics is proposed. With this method, the non-negative coefficients are computed directly on the mesh, reducing the shape distortion introduced by the previously-used polar mapping. The parameterization is then found by solving a sparse linear system, and it provides a simple and visually-smooth piecewise linear mapping, without foldovers.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.