• Animal Bioscience
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• v.36 no.9
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• pp.1435-1444
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• 2023

Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R² = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm^-1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.8-16
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• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• Applied Biological Chemistry
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• v.27 no.3
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• pp.146-150
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• 1984

Changes of weight loss and quality in 3 different apple cultivars and four storage conditions were investigated for 6 month storage. Weight loss changes in the pilot scale low temperature storage $(^{\circ}C)$ could be predicted with linear equations. Quality defects were remarkably increased at 5% of weight loss in all cultivars and storage conditions. It was possible to predict by linear equations the quality of apples by measuring acidity and texture highly correlated to the sensory scores.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.186-203
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• 2020

Image-based Virtual Try-On Systems are among the most potential solution for virtual fitting which tries on a target clothes into a model person image and thus have attracted considerable research efforts. In many cases, current solutions for those fails in achieving naturally looking virtual fitted image where a target clothes is transferred into the body area of a model person of any shape and pose while keeping clothes context like texture, text, logo without distortion and artifacts. In this paper, we propose a new improved image-based virtual try-on network system based on keypoints, which we name as KP-VTON. The proposed KP-VTON first detects keypoints in the target clothes and reliably predicts keypoints in the clothes of a model person image by utilizing a dense human pose estimation. Then, through TPS transformation calculated by utilizing the keypoints as control points, the warped target clothes image, which is matched into the body area for wearing the target clothes, is obtained. Finally, a new try-on module adopting Attention U-Net is applied to handle more detailed synthesis of virtual fitted image. Extensive experiments on a well-known dataset show that the proposed KP-VTON performs better the state-of-the-art virtual try-on systems.

• Korean Journal of Food Science and Technology
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• v.27 no.2
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• pp.193-198
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• 1995

The changes in the rheological properties of soybean curd upon the various storage temperatures ($5{\sim}25^{\circ}C$) were measured by the stress-relaxation test and analysed by time-temperature superposition theory. As the storage temperature was lower, higher initial and equilibrium stress of soybean curd were observed. When the stress-relaxation curves were moved horizontally by using the shift-factor on the basis of reference temperature, the master curve was obtained. By applying master curve and shift-factor to the WLF (Williams-Landel-Ferry) equation, activation energy (30kcal/mol) was calculated and storage time at the specific temperature could be predicted, suggesting the equivalent shelf-life of soybean curd texture.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.83-93
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• 2006

The purpose of this study is to analyze the relationship among subjective textures, sensibilities and objective handle of knit fabrics and to provide useful information in planning and designing knit fabrics. We made 20 plain knit fabrics, as specimens, with a combination of 5 kinds of wool/rayon fiber contents and 4 kinds of stitch loop length. For the subjective evaluation, we used 29 questions of subjective textures and sensibilities and employed statistical analysis tools such as factor, Pearson's correlation analysis. An objective handle was measured by Kawabata evaluation system and HV and THV was calculated by KN-402-KT and KN-301-winter. The analysis of a Pearson's correlation with objective properties and handles and structural properties of knit fabrics demonstrated a highly linear relationship. Especially, wool/rayon contents and WT of tensile properties and loop stitch length and G of shear properties showed a correlation coefficient over 0.9. But a relationship of objective properties and subjective textures and sensibilities was non-linear and a linear multi-regression analysis showed that a objective handle had a lower prediction power in the area of subjective textures and sensibilities.

• Korean Journal of Radiology
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• v.24 no.12
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• pp.1190-1199
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• 2023

Objective: This study aimed to investigate the feasibility of ultrafast magnetic resonance imaging (MRI) and radiomic features derived from breast MRI for predicting the upstaging of ductal carcinoma in situ (DCIS) diagnosed using percutaneous needle biopsy. Materials and Methods: Between August 2018 and June 2020, 95 patients with 98 DCIS lesions who underwent preoperative breast MRI, including an ultrafast sequence, and subsequent surgery were included. Four ultrafast MRI parameters were analyzed: time-to-enhancement, maximum slope (MS), area under the curve for 60 s after enhancement, and time-to-peak enhancement. One hundred and seven radiomic features were extracted for the whole tumor on the first post-contrast T1WI and T2WI using PyRadiomics. Clinicopathological characteristics, ultrafast MRI findings, and radiomic features were compared between the pure DCIS and DCIS with invasion groups. Prediction models, incorporating clinicopathological, ultrafast MRI, and radiomic features, were developed. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to evaluate model performance in distinguishing between the two groups using leave-one-out cross-validation. Results: Thirty-six of the 98 lesions (36.7%) were confirmed to have invasive components after surgery. Compared to the pure DCIS group, the DCIS with invasion group had a higher nuclear grade (P < 0.001), larger mean lesion size (P = 0.038), larger mean MS (P = 0.002), and different radiomic-related characteristics, including a more extensive tumor volume; higher maximum gray-level intensity; coarser, more complex, and heterogeneous texture; and a greater concentration of high gray-level intensity. No significant differences in AUCs were found between the model incorporating nuclear grade and lesion size (0.687) and the models integrating additional ultrafast MRI and radiomic features (0.680-0.732). Conclusion: High nuclear grade, larger lesion size, larger MS, and multiple radiomic features were associated with DCIS upstaging. However, the addition of MS and radiomic features to the prediction model did not significantly improve the prediction performance.

• Korean Journal of Soil Science and Fertilizer
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• v.12 no.1
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• pp.15-23
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• 1979

In the first paper of the series the five soil fertility factors were evaluated by means of principal component analysis and varimax method. They are interpreted as representing, 1) skeletal available phosporus status, 2) organnic matter status, 3) salt status 4) base status, and 5) free oxide status. In order to resynthesize such fragmented information for the overall soil fertility evaluation, the method of multiple regression analysis was adopted, using the five factor scores and yield data for Korean paddy soils as independent and dependent variables respectively. As test of linear models with different combinations of independent variables the results of t-test of regression coefficient were revealed that the organic matter status (FII) has no relevance to the yield of paddy and that the free oxides and salt supply has by it self only an insignificant contribution to the yield. The multiple correlation coefficient (R) revealed its multiple regression analysis was as low as 0.43. Introduction of quadratic terms to the linear model bettered the result. Thus multiple correlation coefficient (R) was increased as 0.59. Therefore, a coefficient of determination 0.35 was obtained by a quadratic model with interaction terms among the five fertility constituents. Generally we think that the fertility factor has more contribution to raise the rice yield in paddy and that the failure of yield prediction by fertility factor scores was caused by one of follows; 1) the roughness of the yield inspection, and 2) missextraction of fertility constituents. The second step in this study, assuming that the residuals by multiple regression analysis were due to factors other than soil fertility, we can now proceed to predicting the yield from the field characters with the classified fertility groups by means of Hayashi's theory of quantification No. 1. Such variables as fertility groups (FTYG), water availability (WATER), soil drainage (DRNG), climatic zone (CLIZ), surface soil's stickiness (STCKT), surface soil's dry consistence (DCNST), and surface soil's texture (FTEXT) are taken up as the explanatory variables. The quantification appears reasonable; the well to extremely well in soil drainage, very sticky of surface soil, inefficiency in water availability, coarse texture, and very hard to extremely hard dry consistence in soil are detrimental to the rice yield. The R was as high as 0.90 for the set of variables. But the given explanatory variables in this study were not quite effective in explaining rice yield. The method developed seems to be promising only if properly collected data are available. Conditions that should be satisfied in the yield inspection obtained from common cultivator for the purpose of deriving a prediction equation were put forward.

• Journal of the Korean Society of Radiology
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• v.82 no.2
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• pp.406-416
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• 2021

Purpose To evaluate the association between magnetic resonance imaging (MRI)-based texture parameters and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in patients with non-mucinous rectal cancer. Materials and Methods Seventy-nine patients who had pathologically confirmed rectal non-mucinous adenocarcinoma with or without KRAS-mutation and had undergone rectal MRI were divided into a training (n = 46) and validation dataset (n = 33). A texture analysis was performed on the axial T2-weighted images. The association was statistically analyzed using the Mann-Whitney U test. To extract an optimal cut-off value for the prediction of KRAS mutation, a receiver operating characteristic curve analysis was performed. The cut-off value was verified using the validation dataset. Results In the training dataset, skewness in the mutant group (n = 22) was significantly higher than in the wild-type group (n = 24) (0.221 ± 0.283; -0.006 ± 0.178, respectively, p = 0.003). The area under the curve of the skewness was 0.757 (95% confidence interval, 0.606 to 0.872) with a maximum accuracy of 71%, a sensitivity of 64%, and a specificity of 78%. None of the other texture parameters were associated with KRAS mutation (p > 0.05). When a cut-off value of 0.078 was applied to the validation dataset, this had an accuracy of 76%, a sensitivity of 86%, and a specificity of 68%. Conclusion Skewness was associated with KRAS mutation in patients with non-mucinous rectal cancer.

• Korean Journal of Soil Science and Fertilizer
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• v.31 no.2
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• pp.120-127
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• 1998

This study was performed to produce basic data for developing prediction techniques of desalinization through analyzing soil properties of reclaimed tidal lands, using soil samples collected in 11 units of tidal land reclamation projects. The average apparent specific gravity (bulk density), real specific gravity (particle density), porosity, and saturation percentage were measured to be 1.33, 2.64, 49.6%, and 56.3%, respectively. It was estimated that the soil texture class of reclaimed tidal lands would be silt or silt loam. The electrical conductivity and exchangeable sodium percentage were estimated to be $20{\sim}40dS\;m^{-1}$ and 30~50% in the beginning of tidal land reclamation, and the value of pH was measured to be 6.5~7.9. In conclusion, the soil properties of reclaimed tidal lands could be descrived to be saline-sodic soils with the high electrical conductivity and exchangeable sodium percentage.