• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.151-162
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• 2019

Surface temperature has been derived from the MODIS/ASTER airborne simulator (MASTER) mid-wave infrared single channel data using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model with input data including the University of Wisconsin (UW) emissivity, the National Centers for Environmental Prediction (NCEP) atmospheric profiles, and solar and line-of-sight geometry. We have selected the study area that covers some surface types such as water, sand, agricultural (vegetated) land, and clouds. Results of the current study show the reasonable geographical distribution of surface temperature over land and water similar to the pattern of the MASTER L2 surface temperature. The thorough quantitative validation of surface temperature retrieved from this study is somehow limited due to the lack of in-situ measurements. One point comparison at the Salton Sea buoy shows that the present estimate is 1.8 K higher than the field data. Further comparison with the MASTER L2 surface temperature over the study area reveals statistically good agreement with mean differences of 4.6 K between two estimates. We further analyze the surface temperature differences between two estimates and find primary factors to be emissivity and atmospheric correction.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.196-202
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• 2024

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease prediction. Due to breast cancer's favorable prognosis at an early stage, a model is created to utilize the Dataset on Wisconsin Diagnostic Breast Cancer (WDBC). Conversely, this model's overarching axiom is to compare the effectiveness of five well-known ML classifiers, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), and Naive Bayes (NB) with the conventional method. To counterbalance the effect with conventional methods, the overarching tactic we utilized was hyperparameter tuning utilizing the grid search method, which improved accuracy, secondary precision, third recall, and finally the F1 score. In this study hyperparameter tuning model, the rate of accuracy increased from 94.15% to 98.83% whereas the accuracy of the conventional method increased from 93.56% to 97.08%. According to this investigation, KNN outperformed all other classifiers in terms of accuracy, achieving a score of 98.83%. In conclusion, our study shows that KNN works well with the hyper-tuning method. These analyses show that this study prediction approach is useful in prognosticating women with breast cancer with a viable performance and more accurate findings when compared to the conventional approach.

• Korea journal of population studies
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• v.33 no.2
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• pp.33-59
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• 2010

This paper intends to find the determinants of the occupational aspirations of college students in Korea. According to Wisconsin model, the occupational aspiration of youth has a statistically significant influence on his or her actual education level and occupation choice implying that the more motivated with high-level occupational aspiration will obtain the higher level of occupation. The analysis for this study is based on the survey of undergraduate students' perception, attitude and lifestyle in Korea 2004, which was conducted against 1,947 respondents, and multiple regression model was utilized. The dependent variable for occupational aspirations was measured by the Standard International Occupational Prestige Scale (SIOPS) of Donald J. Treiman. Independent variables include social capital and cultural capital as well as demographic variables, socio-economic status, and human capital variables. Social capital variable was measured by the position generator scale of Nan Lin and Mary Dumin, and cultural capital variable was done to our original index. This study shows that social and cultural capitals are factors having significant influence on occupational aspiration, in addition to the well-known factors such as gender, human capital and the occupation of father.

• Journal of Fashion Business
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• v.9 no.3
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• pp.1-7
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• 2005

The aim at this paper is to provide how to adopt statistical technique like Lisrel, one at the software programs, to secondary data tram Lee Yong-Ju(1998). We develop three research questions and analyze the data at women in their twenties to their fifties simultaneously rather than each age group so that we compare the results at each age group within one model in this study. At each age group the relationships between the satisfaction at the weight and women's lower body parts regarding waist girth, hip girth and thigh girth are investigated. The results reveal that women are satisfied with different lower body parts according to the satisfaction of their weight in terms of their age range and imply the satisfaction of their lower body parts by analyzing the satisfaction of their weight does not correspond with increases in their age.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.9
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• pp.1127-1136
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• 2010

Yogurt gels are a type of soft solid, and these networks are relatively dynamic systems that are prone to structural rearrangements. The physical properties of yogurt gels can be qualitatively explained using a model for casein interactions that emphasizes a balance between attractive (e.g., hydrophobic attractions, casein cross-links contributed by calcium phosphate nanoclusters and covalent disulfide cross-links between caseins and denatured whey proteins) and repulsive (e.g., electrostatic or charge repulsions, mostly negative at the start of fermentation) forces. Various methods are discussed to investigate the physical and structural attributes of yogurts. Various processing variables are discussed which influence the textural properties of yogurts, such as total solids content, heat treatment, and incubation temperatures. A better understanding of factors contributing to the physical and structural attributes may allow manufacturers to improve the quality of yogurt.

• Structural Engineering and Mechanics
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• v.16 no.1
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• pp.101-114
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• 2003

A base isolation system is proposed for earthquake protection of structures. The system incorporates spherical supports for the base, a specially designed spring-cam system to keep the base rigidly supported under normal condition and to allow it to move for the duration of the earthquake under the constraint of a spring with optimized non-linear characteristics. A single-story model is constructed to investigate the feasibility of the concept. Numerical simulations of the system as well as experimental results show that 95% reduction of the transmitted force to the structure can be achieved. To demonstrate the effectiveness of this isolation mechanism, the maximum dynamic bending stress developed at predetermined critical points within the frame of the structure is measured. Significant reduction of the dynamic stresses is obtained.

• ETRI Journal
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• v.34 no.5
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.60.1-60.1
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• 2014

The star ${\zeta}$ Ophiuchi (HD 149757) is one of the brightest massive stars in the northern hemisphere and was widely studied in various wavelength domains. We report the analysis results of far ultraviolet (FUV) observations with other wavelengths for around ${\zeta}$ Ophiuchi. We study the correlation of between multi wavelength observations. We have developed a Monte Carlo code that simulates dust scattering of light including multiple encounters. The code is applied to the present Oph HII region to obtain the geometrical information of dust such as distance and thickness. Also We apply three-dimensional photoionization code to model Wisconsin $H{\alpha}$ Mapper observations of the H II region surrounding the star.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.80-88
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• 2024

Breast cancer remains a significant global health burden, necessitating accurate and timely detection for improved patient outcomes. Machine learning techniques have demonstrated remarkable potential in assisting breast cancer diagnosis by learning complex patterns from multi-modal patient data. This study comprehensively evaluates several popular machine learning models, including logistic regression, decision trees, random forests, support vector machines (SVMs), naive Bayes, k-nearest neighbors (KNN), XGBoost, and ensemble methods for breast cancer prediction using the Wisconsin Breast Cancer Dataset (WBCD). Through rigorous benchmarking across metrics like accuracy, precision, recall, F1-score, and area under the ROC curve (AUC), we identify the naive Bayes classifier as the top-performing model, achieving an accuracy of 0.974, F1-score of 0.979, and highest AUC of 0.988. Other strong performers include logistic regression, random forests, and XGBoost, with AUC values exceeding 0.95. Our findings showcase the significant potential of machine learning, particularly the robust naive Bayes algorithm, to provide highly accurate and reliable breast cancer screening from fine needle aspirate (FNA) samples, ultimately enabling earlier intervention and optimized treatment strategies.

• Journal of the korean society of oceanography
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• v.33 no.4
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• pp.137-145
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• 1998

In order to investigate the paleotidal structure and current pattern in the Yellow and East China seas (YECS) since the late Wisconsin, which is the last glacial maximum period, a two-dimensional version of the Princeton ocean model is used. We assume that subtracting the sea-level differences from the present one can produce paleobasins and that the paleotide did not differ greatly from the present one in the adjacent deep seas, the northwestern Pacific Ocean and the East Sea. We could successfully simulate the paleo-M$_2$ tides and tidal currents of 9000, 11000 and 13000 yr B.P. The result of the model shows considerable differences in the tidal pattern in each period. As the eustatic sea level rose, the amplitudes of the paleotides and the number of the amphidromic points generally increased, but the tidal currents in each paleobasin were strong and about the same order as the present day's. Based on these paleotide calculations, we suggest that there should have been active erosion in the paleobasin as in the present YECS, and the erosion should have played an important role on widening the paleobasin to the present shape, YECS.