• Korean Journal of Radiology
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• v.23 no.7
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• pp.720-731
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• 2022

Objective: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging (MRI) and to evaluate the clinical utility of DLA-assisted assessment of functional liver capacity. Materials and Methods: The DLA was developed using HBP-MRI data from 1014 patients. Using an independent test dataset (110 internal and 90 external MRI data), the segmentation performance of the DLA was measured using the Dice similarity score (DSS), and the agreement between the DLA and the ground truth for the volume and SI measurements was assessed with a Bland-Altman 95% limit of agreement (LOA). In 276 separate patients (male:female, 191:85; mean age ± standard deviation, 40 ± 15 years) who underwent hepatic resection, we evaluated the correlations between various DLA-based MRI indices, including liver volume normalized by body surface area (LV_BSA), liver-to-spleen SI ratio (LSSR), MRI parameter-adjusted LSSR (aLSSR), LSSR × LV_BSA, and aLSSR × LV_BSA, and the indocyanine green retention rate at 15 minutes (ICG-R15), and determined the diagnostic performance of the DLA-based MRI indices to detect ICG-R15 ≥ 20%. Results: In the test dataset, the mean DSS was 0.977 for liver segmentation and 0.946 for spleen segmentation. The Bland-Altman 95% LOAs were 0.08% ± 3.70% for the liver volume, 0.20% ± 7.89% for the spleen volume, -0.02% ± 1.28% for the liver SI, and -0.01% ± 1.70% for the spleen SI. Among DLA-based MRI indices, aLSSR × LV_BSA showed the strongest correlation with ICG-R15 (r = -0.54, p < 0.001), with area under receiver operating characteristic curve of 0.932 (95% confidence interval, 0.895-0.959) to diagnose ICG-R15 ≥ 20%. Conclusion: Our DLA can accurately measure the volume and SI of the liver and spleen and may be useful for assessing functional liver capacity using gadoxetic acid-enhanced HBP-MRI.

• Journal of Animal Science and Technology
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• v.54 no.4
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• pp.275-282
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• 2012

The data including milk yields, fat and protein percent for 628,395 heads collected by National Agricultural Cooperative Federation, 15 type traits and final score for 62,262 heads collected by Korea Animal Improvement Association, which were born in 1998 to 2004, and net profits calculated from milk price and raising expenses of individuals were used to estimate genetic parameters. The highest positive genetic correlation, 0.81, was shown between body depth (BD) and loin strength (SR). Genetic correlations between body depth (BD) and udder depth (UD), front teat placement (TP) and front teat length (TL) were -0.23, which were lowest among the linear type traits. Furthermore, medium level of negative genetic correlations were shown the milk yield with milk contents rate traits. Mostly low level of positive genetic correlations were shown between the milk traits and linear score traits except milk yield and stature. Most of the genetic correlations of between the linear score traits and net profit were low level of positive or negative genetic correlations. Among the genetic correlations, body depth (BD), angularity (DF) and rear attachment width (UW), and final score (FS) with net profit were high as 0.17, 0.17, 0.18 and 0.18, respectively. Finally all of the genetic correlations between net profit and milk traits were positive and higher than the linear traits with positive genetic correlations. The results of this study suggest that net profit has been related with the linear traits, such as body depth (BD), angularity (DF) and rear attachment width (UW) traits, and furthermore, milk traits including yield and contents rates influence positively and greatly on net profit.

• International Journal of Human Ecology
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• v.6 no.2
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• pp.25-35
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• 2005

The purpose of this study was to examine the effects of family-school relations on children's school adjustment with divorced mothers. Subcategories of the family-school relations were family participation in decision making, family help for schools, learning activities at home, school help for families, and school-home communication adopted from Epstein's parent involvement theory. Sub categories of children's school adjustment were delinquent behavior and academic achievement. The sample of this study included 3,367 children from first to fifth grade who lived either in a two-parent or one-parent home. Among them, 411 children with divorced mothers were analyzed. Independent t-test, Pearson's correlations, stepwise regression analysis were all conducted. Findings suggested that children with divorced mothers showed higher delinquency and lower academic achievement than children in intact families. Sub categories of family involvement and school involvement were correlated in divorced families. Children's delinquency was predicted by three of the family-school relation factors, which were school-home communication, family help for schools, and school help for families. Children's academic achievement was predicted by ail factors.

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.606-611
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• 2016

Carbon dioxide injection is a widely known method of enhanced oil recovery (EOR). It is critical for the $CO_2$ EOR that the injected $CO_2$ to reach a condition fully miscible with oil. To reach the miscible point, a certain level of pressure is required, which is known as minimum miscibility pressure (MMP). In this study, a MMP prediction method using a process simulator is proposed. To validate the results of the simulation, those are compared to a slim tube experiment and several empirical correlations of previous literatures. Aspen HYSYS is utilized as the process simulator to create a model of $CO_2$/crude oil encounter. The results of the study show that the process simulator model is capable of predicting MMP and comparable to other published methods.

• Bulletin of the Korean Chemical Society
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• v.32 no.12
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• pp.4210-4214
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• 2011

Quasiclassical trajectory (QCT) calculations of Ne + ${H_2}^+$ reaction have been carried out on the adiabatic potential energy surface of the ground state $1^2$ A'. The reaction probability of the title reaction for J = 0 has been calculated, and the QCT result is consistent with the previous quantum mechanical wave packet result. Quasiclassical trajectory calculations of the four polarization-dependent differential cross sections have been carried out in the center of mass (CM) frame. The P(${\theta}_r$), P(${\phi}_r$) and P(${\theta}_r$, ${\phi}_r$) distributions, the k-k'-j' correlation and the angular distribution of product rotational vectors are presented in the form of polar plots. Due to the well in $1^2$ A' PES, the reagent vibrational excitation has greater influence on the polarization of the product rotational angular momentum vectors j' than the collision energy.

• Korean Journal of Child Studies
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• v.32 no.2
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• pp.35-52
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• 2011

The purpose of this study was to evaluate the validity and reliability of the Penn Interactive Peer Play Scale (PIPPS) for Korean young children, with a special confirmative factor analysis. The participants were composed of 435 5-to 6-year-old children and their parents, and 42 teachers. The instruments included the 32-item exploratory PIPPS (Choi & Shin, 2008), the Preschool Behavior Questionnaire (PBQ; Park, 1992), and the PIPPS on parental reporting. The PIPPS was confirmed, and supported the following constructs resulting in the investigation of 3 factors, 'play disruption', 'play interaction', and 'play disconnection', along with 30 items similar to the PIPPS (2008). Inter-correlations between the sub-factors of PIPPS with those of criterion measures were validated by ratings from the PBQ and the parent version of the PIPPS. The reliability coefficients of the sub-factors of the PIPPS ranged from .85 to .92. In conclusion, 3 factor structure of the PIPPS was appropriate to represent the interactive peer play of Korean young children.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.292-295
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• 2008

In a SCWR (SuperCritical pressure Water cooled Reactor), the coolant temperature initially at below the pseudo-critical temperature at the bottom of a reactor core increases as the coolant flows upward through the sub-channels of the fuel assemblies, and it finally becomes higher than the pseudo-critical temperature when it leaves the reactor core. At certain conditions, heat transfer deterioration occurs near the pseudo-critical temperature and it may cause a drastic rise of the fuel surface temperature resulting a fuel failure. Therefore, an accurate estimation of the heat transfer coefficient is very important for the thermal-hydraulic design of a reactor core. An experiment on heat transfer to the vertically upward flowing $CO_2$ at a supercritical pressure in a circular tube were performed at KAERI. The internal diameter of the test section is 6.32 mm, which corresponds to the hydraulic diameter of a sub-channel in the conceptional design proposed by KAERI. The test range of the mass flux is 285 to 1200 kg/m$^2$s and the maximum heat flux is 170 kW/m$^2$. The inlet pressure is maintained at 8.12 MPa, which is 1.1 times the critical pressure. A new correlation, which covers both the normal and deterioration heat transfer regimes was proposed and compared with the estimations by exiting correlations.

• Bulletin of the Korean Chemical Society
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• v.34 no.11
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• pp.3350-3356
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• 2013

Quasi-classical trajectory calculations have been carried out for the reaction H+HS by using the newest triplet 3A" potential energy surface (PES). The effects of the collision energy and reagent initial rotational excitation are studied. The cross sections and thermal rate constants for the title reaction are calculated. The results indicate that the integral cross sections (ICSs) are sensitive to the collision energy and almost independent to the initial rotational states. The ro-vibrational distributions for the product $H_2$ at different collision energies are presented. The investigations on the vector correlations are also performed. It is found that the collision energies play a postive role on the forward scatter of the product molecules. There is a negative influence on both the alignment and orientation of the product angular momentum for low collision energy at low energy region. Whereas the influence of collision energy is not obvious at high energy region.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.151-160
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• 2017

IIn this paper, I investigate the effect of special education teachers' self-leadership on job-satisfaction. The data was collected from 141 special education teachers to analyze the correlations between self-leadership, job and life satisfaction. In addition, another purpose is to analyze how self-leadership influence on job satisfaction (human relationship, assigned tasks) and life satisfaction. The results are shown as follows. First, self-expectation and goal setting, self-expectation and human relationship, human relationship and assigned tasks have meaningful correlation. Second, self-expectation and self-rewarding are sub-factors of self-leadership that have great influence on human relationship which is a subordinate factor of job satisfaction and assigned tasks. Third, self-expectation and self-rewarding are factors of self-leadership that have a great influence on life satisfaction. Finally, it shows that self-leadership has an effect on life satisfaction through assigned task, which is a factor of job satisfaction. However, through human relationship, self-leadership does not have a meaningful effect on life satisfaction. This study is significant by finding sub-factors which influence special education teacher's self leadership, job satisfaction and life satisfaction by using Bootstrap method.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.35-42
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• 2021

In the current context of digitalization of education, the use of modern methods and techniques of data analysis and processing in order to improve students' school results has a very important role. In our paper, we aimed to perform a comparative study of the classification performances of AdaBoost, SVM, Naive Bayes, Neural Network and kNN algorithms to classify the results obtained at the Baccalaureate by students from a college in Suceava, during 2012-2019. To evaluate the results we used the metrics: AUC, CA, F₁, Precision and Recall. The AdaBoost algorithm achieves incredible performance for classifying the results into two categories: promoted / rejected. Next in terms of performance is Naive Bayes with a score of 0.999 for the AUC metric. The Neural Network and kNN algorithms obtain scores of 0.998 and 0.996 for AUC, respectively. SVM shows poorer performance with the score 0.987 for AUC. With the help of the HeatMap and DataTable visualization tools we identified possible correlations between classification results and some characteristics of data.