• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.40-44
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• 2019

Purpose Glomerular filtration rate (GFR) is an important index for evaluation of renal function, renal disease diagnosis and progress monitoring. Therefore, accurate measurement of GFR is clinically important. Among the factors that affect the GFR result, there have been many discussions on the methods such as the correction of the kidney depth, net syringe count, and the method of setting the ROI. However there has been no consideration of counting in the most basic factors like height and weight measurement. In this study, we investigate how height and weight changes affects the result of GFR and review the importance of standardized body measurements. Materials and Methods Fifty patients who underwent GFR test were randomly sampled and examined for changes in height and body weight within one month. From the normal patients without renal disease to the patients with severely decreased GFR, we applied the GFR formula of Gate with varying height and weight. Results: The result showed variation of the height at maximum three centimeters and six kilograms of weight. The first calculation of GFR was done with fixed height value and control variable as weight. Weight was incremented by one kilogram each time up to six kilograms. The GFR showed increased result with increasing weight. The result of GFR showed ten percent increase with six kilograms of weight increase. On the other hand, when height value was incremented by one centimeter up to three centimeters showed decreased GFR result with fixed weight value. Up to three centimeters of height increase showed two percent of decreased GFR with fixed weight. Conclusion This study showed varying GFR result when height and weight changes. Therefore it is clinically crucial not only to maintain and manage body measuring instrument but also to have a standardized measurement methods to derive accurate measured values and to achieve reproducibility.

• Korean Journal of Child Education & Care
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• v.19 no.2
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• pp.19-33
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• 2019

Objective: The purpose of this study is to understand how the experience of studying mathematics education for young children based on picture books is affecting pre-service early childhood teachers with their attitude toward mathematics and mathematics teaching efficiency. Methods: For this, a total of 39 pre-service early childhood teachers majoring in early childhood education at S university located in G metropolitan city participated in the study. 20 of them are randomly assigned to the experimental group while the rest 19 were assigned to the control group. The experimental group participated in the classes of mathematics education for young children based on picture books for 15 weeks, while the control group attended the normal classes of mathematics education for young children for the same period of time. By using SPSS 18.0 Program for the collected data, t-test was conducted for differences in the results of attitude toward mathematics and mathematics teaching efficiency. Results: The results of this study are as follows. Firstly, the experience of studying mathematics education for young children based on picture books had a positive effects on pre-service early childhood teachers' attitude toward mathematics, improved values and interest in mathematics, and reduced anxiety about mathematics. Secondly, the experience of studying mathematics education for young children based on picture books had a positive effects on improving pre-service early childhood teachers' mathematics teaching efficiency. Also, both faith in ability and faith in results have improved significantly. Conclusion/Implications: These results imply that the experience of studying mathematics education for young children based on picture books is an effective teaching-learning method in improving pre-service early childhood teachers' attitude toward mathematics and mathematics teaching efficiency.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.199-204
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• 2019

This study aimed to generate a probability distribution model based on temperature data of frozen food storage facility as input variables for microbial risk assessment (MRA). We visited 8 food-handling businesses to collect temperature data from their cold storage warehouses. The overall mean temperature inside the storage facilities was $-20.48{\pm}3.08^{\circ}C$, with 20.4% of the facilities having above $-18^{\circ}C$, with minimum and maximum temperature values of -10.3 and $-25.80^{\circ}C$ respectively. Temperature distributions by space locations of natural and forced convection were $-22.57{\pm}0.84$ and $-17.81{\pm}1.47^{\circ}C$, $-22.49{\pm}1.05$ and $-17.94{\pm}1.44^{\circ}C$, and $-22.68{\pm}1.03$ and $-18.08{\pm}1.42^{\circ}C$ in the upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m) shelves, respectively. Probability distributions from the temperature data were obtained using the program @RISK. Statistical ranking was determined using goodness of fit to determine the probability distribution model. Our results show that a log-normal distribution [5.9731, 3.3483, shift (-26.4281)] is most appropriate for relative MRA conduction.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.1-9
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• 2021

Traditionally, most malicious codes have been analyzed using feature information extracted by domain experts. However, this feature-based analysis method depends on the analyst's capabilities and has limitations in detecting variant malicious codes that have modified existing malicious codes. In this study, we propose a ResNet-Variational AutoEncder-based variant malware classification method that can classify a family of variant malware without domain expert intervention. The Variational AutoEncoder network has the characteristics of creating new data within a normal distribution and understanding the characteristics of the data well in the learning process of training data provided as input values. In this study, important features of malicious code could be extracted by extracting latent variables in the learning process of Variational AutoEncoder. In addition, transfer learning was performed to better learn the characteristics of the training data and increase the efficiency of learning. The learning parameters of the ResNet-152 model pre-trained with the ImageNet Dataset were transferred to the learning parameters of the Encoder Network. The ResNet-Variational AutoEncoder that performed transfer learning showed higher performance than the existing Variational AutoEncoder and provided learning efficiency. Meanwhile, an ensemble model, Stacking Classifier, was used as a method for classifying variant malicious codes. As a result of learning the Stacking Classifier based on the characteristic data of the variant malware extracted by the Encoder Network of the ResNet-VAE model, an accuracy of 98.66% and an F1-Score of 98.68 were obtained.

• Animal Bioscience
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• v.34 no.12
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• pp.1879-1885
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• 2021

Objective: Owing to the lack of a breeding index for efficient and quick fertility evaluations of Holstein bulls when using traditional or genome-wide detection methods, this study aimed to determine whether in vitro fertilization (IVF) could be used as an indicator of conception rate of artificial insemination (AI). Methods: Conventional and sexed frozen semen from nine bulls were used for IVF and AI. Results: The IVF and AI conception rates of each bull were confirmed to be positively correlated between the conventional frozen and sexed frozen semen. The correlation coefficient R values of nine bulls between IVF and AI methods were 0.73 and 0.97 for the conventional frozen and sexed frozen semen, respectively. The average conception rate of three bulls undergoing AI was 69.5% and 64.2%, 61.8% and 58.8%, and 48.2% and 46.2% in first-, second-, and third-born cows when conventional frozen and sexed frozen semen were used, respectively, which showed a positive correlation with the fertilization rate in the same parity. We propose an evaluation standard to assess the fertilization ability of bulls based on their IVF test results, which is categorized into three grades: grade one, normal fertility bull with an AI conception rate of 40%±5% and IVF rate of 45% to 60%; grade two, higher fertility bull with an AI conception rate of 50%±5% and IVF rate of 61% to 80%; and grade three, highest fertility bull with an AI conception rate of 60%±5% and IVF rate of >80%. Conclusion: These findings reveal that IVF results can be used as a breeding index for bulls to evaluate their AI conception ability, which may shorten the time required to select bulls for breeding.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.981-989
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• 2020

In this study, a self-made customized phantom was used to quantitatively measure the change in CT number and noise according to the change of pitch. In order to acquire an image using the phantom, the inside of the phantom was filled with sterile distilled water. Inside the glass tube, a solution obtained by diluting the ratio of normal saline and contrast medium to 100%(NS), 400:1, 200:1, 100:1, 50:1, respectively, was placed and imaged. At this time, the pitch was divided into steps of 0, 0.35, 0.7, 1.05, and 1.4 for each dilution ratio of the solution and imaged, respectively. One-way ANOVA analysis were performed to verify whether the mean of the CT number and noise values measured in all ROIs by dilution ratio showed a significant difference according to the change in pitch. As a result of the experiment, there was no statistically significant difference in the change of the CT number according to the change in the pitch for each dilution ratio, but the noise value tended to increase with the increase of the pitch, and showed a statistically significant difference. In the spiral image acquisition of CT, noise can be changed to a significant level depending on the pitch. Therefore, it will be necessary to set the quality evaluation items and criteria for CT images using the spiral image acquisition method.

• Journal of Nutrition and Health
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• v.53 no.6
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• pp.570-582
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• 2020

Purpose: Obesity is a risk factor for various adult diseases such as type 2 diabetes, cardio-cerebrovascular disease, and cancer. With an increasing obesity population worldwide, the prevention of obesity with natural components has emerged as an alternative health care strategy. Ramulus mori (Sangzhi, RM) is widely used as a traditional herbal medicine in East Asia. It contains various phytochemicals, including stilbenes and 2-arylbenzofurans. In this study, we compared the anti-obesity effects of RM extracts and its major stilbene components (mulberroside A [MSA] and oxyresveratrol [ORT]) in high fat diet (HFD)-fed obese mice. Methods: Five week-old, male C57BL/6J mice were grouped into 7 experimental groups: normal diet (ND), HFD, HFD + 1% RM water extracts (MW), HFD + 0.1% MSA, HFD + 1% RM ethanol extracts (ME), HFD + 0.1% ORT, and HFD + 1% Garcinia cambogia extracts (GC) as a positive control. All mice were fed experimental diet for 13 weeks. Results: Compared to the HFD group, total body weight and weekly body weight gain were significantly decreased in the ME, ORT, and GC groups. Glucose tolerance level was significantly decreased in all experimental groups, whereas plasma insulin level was decreased in MSA, ME, ORT and GC groups. Plasma glucose, triglyceride (TG), and total cholesterol levels were significantly decreased, whereas high-density lipoprotein cholesterol levels were increased in the MSA, ORT, and GC groups. Hepatic TG accumulation was also significantly decreased in the MSA, ME, ORT, and GC groups. Adipose tissue weight and size of adipocytes were significantly decreased in the MSA, ME and ORT groups, and were comparable to values obtained in the GC group. The levels of adiponectin and SREBP1c mRNA expressions were increased in the ORT and GC groups. Conclusion: These results indicate that ME, ORT and MSA exert significant anti-obesity effect, and have the potential to be developed as a weight control ingredient of functional foods.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.1-10
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• 2021

Purpose: The purpose of this study is to evaluate the relationship between removable denture and depression. This study aims to investigate the relationship between depression and each group by dividing them into a group that were using removable dentures and a group that needed removable dentures but were not using removable dentures. Materials and methods: This study was conducted using raw data from the 7th Korea National Health and Nutrition Examination Survey (KNHNES). By using variables related to the state of the prosthesis and the need for prosthesis among oral examination data, the oral examination data were classified into two groups; group using removable denture and group in need of removable dentures. In addition, the variables of depression were classified into normal (0-4), mild depression (5-9), moderate depression (10-19), and severe depression (20-27) using the values of PHQ-9. For statistical analysis, logistic regression analysis was performed using SAS 9.4. Results: In the group in need of removable dentures, the risk of severe depression was statistically and significantly higher than the group using removable dentures. Conclusion: In patient who have lost multiple teeth, rehabilitation of the missing area with removable dental prosthesis is expected to decrease the occurrence of severe depression.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.71-79
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• 2021

Currently, the naked eyes-based diagnosis of bone metastases on CT images relies on qualitative assessment. For this reason, there is a great need for a state-of-the-art approach that can assess and follow-up the bone metastases with quantitative biomarker. Radiomics can be used as a biomarker for objective lesion assessment by extracting quantitative numerical values from digital medical images. In this study, therefore, we evaluated the clinical applicability of non-invasive and objective bone metastases computer-aided diagnosis using radiomics-based biomarkers in CT. We employed a total of 21 approaches consist of three-classifiers and seven-feature selection methods to predict bone metastases and select biomarkers. We extracted three-dimensional features from the CT that three groups consisted of osteoblastic, osteolytic, and normal-healthy vertebral bodies. For evaluation, we compared the prediction results of the classifiers with the medical staff's diagnosis results. As a result of the three-class-classification performance evaluation, we demonstrated that the combination of the random forest classifier and the sequential backward selection feature selection approach reached AUC of 0.74 on average. Moreover, we confirmed that 90-percentile, kurtosis, and energy were the features that contributed high in the classification of bone metastases in this approach. We expect that selected quantitative features will be helpful as biomarkers in improving the patient's survival and quality of life.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.248-261
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• 2021

The purpose of this study is that the blood nutrient indicator in adult women, is the depressive indicator. This study recruited 77 pre-menopausal women, and excluding missing values, 53 (mean age 44.2±6.5 years) blood indexes were statistically confirmed and then analyzed the effect of indexes on the Beck Depression Inventory. The Beck's Depression Inventory(BDI)'s average of the study subjects was 7.6±7.2, and most of the depression symptoms were within the normal range. Only two women were very serious and other two women were serious state. As a result of this study, 21 questions of BDI was classified into 5 sub-factors. Of these, 2 factors were considered physical depression, 1 factor was mood depression, 1 factor was cognitive depression, and 1 factor undecided. As a result of the correlation analysis, triglyceride, LDL(low density lipoprotein) cholesterol and potassium showed statistically significant positive relationship with depressive factors. On the other hand, HDL(high density lipoprotein) cholesterol, sodium and chloride ions showed negative relationship with depressive factors. When multiple regression analysis was performed. Considering the depression factors was dependent variable, and triglyceride, cholesterol, blood sugar, and ketone bodies was considered as independent variables. HDL(high density lipoprotein) cholesterol had a statistically significant negative effect on the depression factor 3. Considering the depression factors was dependent variable, and minerals were considered as independent variables. Potassium had a positive effect, and chloride ions had a negative effect on the depressive factor 3. This study was limited to 77 pre-menopausal women. In the future, post-menopausal women, men, and clinical neurological disorders group will be possible.