• Journal of The Korean Society of Grassland and Forage Science
• /
• v.42 no.1
• /
• pp.1-9
• /
• 2022

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.3
• /
• pp.73-82
• /
• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Journal of the Korea Convergence Society
• /
• v.13 no.1
• /
• pp.399-408
• /
• 2022

The purpose of this study was to compare the usefulness of the lipid ratio indicators for the diagnosis of metabolic syndrome in the elderly aged 65 years or older. From January 2018 to December 2020, 1,464 people aged 65 years or older who underwent a health checkup at a general hospital in Seoul were included. Lipid ratio indicators were measured through blood tests. The prevalence of metabolic syndrome according to the quartiles of the lipid ratio index was confirmed by logistic regression analysis. In addition, the metabolic syndrome predictive ability and cutoff value of the lipid ratio indices were estimated with the receiver operating characteristic(ROC) curve. The correlation between atherogenic index of plasma(AIP) and waist circumference was the highest in both men and women(r=0.278, p<0.001 vs r=0.252, p<0.001). As for the lipid ratio indices, the incidence of metabolic syndrome was higher in the fourth quartile than in the first quartile. The area under the ROC curve(AUC) value of AIP was higher at 0.826(95% CI=0.799-0.850) and 0.852(95% CI=0.820-0.881) for men and women, respectively, compared to other lipid ratio indicators, and the optimal cutoff values for both men and women was 0.44(p<0.001). Therefore, the AIP among the lipid ratio indicators was found to be the most useful index for diagnosing metabolic syndrome in the elderly aged 65 years or older.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.2
• /
• pp.211-231
• /
• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of the Korean Applied Science and Technology
• /
• v.40 no.2
• /
• pp.199-209
• /
• 2023

This study is a descriptive research to identify the factors that influence blood donation intentions of the middle-aged firefighters and prison officer based on Ajzen's (1991) planned behavior theory. The subjects of the study were 223 middle-aged firefighters and prison officer at a fire station and prison located in G City and District B. The Data were analyzed by descriptive statistics and t-test, one-way ANOVA, Pearson's correlation coefficient, Turkey, and multiple regression with the SPSS 21.0 program. There were statistically significant differences in blood donation intention according to the blood donation experience, attempted blood donation within a year, participate plan in blood donation within 3 months. The blood donation intention of middle aged showed significant positive correlations with attitude, subjective norms, and perceived behavioral control towards blood donation. Multiple regression analysis for blood donation intention revealed that the significant predictors were participate plan in blood donation within 3 months, perceived behavior control, subjective norms, attitude towards blood donation, and attempted blood donation within a year. These factors explained 69% of the variance. In order to enhance the middle aged's intention to blood donation, we need a program that can improve middle aged's attitude, subjective norms, perceived behavior control.

• The Journal of Engineering Geology
• /
• v.32 no.1
• /
• pp.27-40
• /
• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.

• Journal of the Korean Orthopaedic Association
• /
• v.54 no.2
• /
• pp.150-156
• /
• 2019

Purpose: This study examined the diagnostic accuracy of an imaging study to find the factors that affect the presence of residual tumors after an unplanned excision of sarcomas. Materials and Methods: Ninety-eight patients, who underwent a re-excision after unplanned surgery between January 2008 and December 2014, were enrolled in this study. Magnetic resonance imaging (MRI) was performed before reoperation in all patients. Positron emission tomography (PET)-computed tomography was performed on 54 patients. A wide re-excision and histology diagnosis were performed in all cases. The clinical variables were evaluated using univariate logistic regression and multivariate logistic regression. Results: The presence of a deep-seated tumor increases the risk of remnant tumors (odds ratio: 3.21, p=0.02, 95% confidence interval: 1.25-8.30). The sensitivity for detecting residual tumors is high in MRI (sensitivity 0.79). Conclusion: Deep-seated tumors have a significantly higher risk of remnant tumors. Because the negative predictive value of MRI and PET scans is very low, reoperation should be performed regardless of a negative result.

• Journal of the Korean Orthopaedic Association
• /
• v.52 no.1
• /
• pp.73-82
• /
• 2017

Purpose: To assess the chronological changes of disease-related kyphosis after chemotherapy alone. Materials and Methods: A total of 101 children aged 2 to 15 years with spinal tuberculosis, accompanied by various stages of disease processes were enrolled for analysis. By utilizing the images in them, the growth plate condition and chronological changes of kyphosis after chemotherapy were analyzed at two points in time; the first assessment was at post-chemotherapy one-year and second at the final discharge. Results: Complete disc destruction in the cervical, dorsal and lumbosacral spines was observed in 2 out of 40 children (5.0%), 8 out of 30 children (26.7%), and 6 out of 31 children (19.4%), respectively. In those cases, the residual kyphosis inevitably developed. In the remaining children, the discs were intact or partially damaged. Among the 101 children kyphotic deformity was maintained without change in 20 children (19.8%). Kyphosis decreased in 14 children (13.9%), while it increased in 67 children (66.3%) with non-recoverably damaged growth plate. Conclusion: Although it is tentatively possible to predict the deformity progress or non-progress and spontaneous correction at the time of the initial treatment, its predictive accuracy is low. Therefore, assessment of the chronological changes should be performed at the end of chemotherapy. In children with progressive curve change, assessment of deformity should be continued until maturity.

• Journal of Life Science
• /
• v.33 no.6
• /
• pp.490-497
• /
• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Biomolecules & Therapeutics
• /
• v.31 no.4
• /
• pp.446-455
• /
• 2023

The mechanistic functions of 3-deoxysappanchalcone (3-DSC), a chalcone compound known to have many pharmacological effects on lung cancer, have not yet been elucidated. In this study, we identified the comprehensive anti-cancer mechanism of 3-DSC, which targets EGFR and MET kinase in drug-resistant lung cancer cells. 3-DSC directly targets both EGFR and MET, thereby inhibiting the growth of drug-resistant lung cancer cells. Mechanistically, 3-DSC induced cell cycle arrest by modulating cell cycle regulatory proteins, including cyclin B1, cdc2, and p27. In addition, concomitant EGFR downstream signaling proteins such as MET, AKT, and ERK were affected by 3-DSC and contributed to the inhibition of cancer cell growth. Furthermore, our results show that 3-DSC increased redox homeostasis disruption, ER stress, mitochondrial depolarization, and caspase activation in gefitinib-resistant lung cancer cells, thereby abrogating cancer cell growth. 3-DSC induced apoptotic cell death which is regulated by Mcl-1, Bax, Apaf-1, and PARP in gefitinib-resistant lung cancer cells. 3-DSC also initiated the activation of caspases, and the pan-caspase inhibitor, Z-VAD-FMK, abrogated 3-DSC induced-apoptosis in lung cancer cells. These data imply that 3-DSC mainly increased mitochondria-associated intrinsic apoptosis in lung cancer cells to reduce lung cancer cell growth. Overall, 3-DSC inhibited the growth of drug-resistant lung cancer cells by simultaneously targeting EGFR and MET, which exerted anti-cancer effects through cell cycle arrest, mitochondrial homeostasis collapse, and increased ROS generation, eventually triggering anti-cancer mechanisms. 3-DSC could potentially be used as an effective anti-cancer strategy to overcome EGFR and MET target drug-resistant lung cancer.