• Korea Trade Review
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• v.48 no.3
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• pp.69-88
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• 2023

This study analyzes the dynamic characteristics of cargo volume (demand), ship fleet (supply), and freight rate (price) of container, dry bulk, and tanker shipping markets by using the VAR and VECM models. This analysis is expected to enhance the statistical understanding of market dynamics, which is perceived by the actual experiences of market participants. The common statistical patterns, which are all shown in the three shipping markets, are as follows: 1) The Granger-causality test reveals that the past increase of fleet variable induces the present decrease of freight rate variable. 2) The impulse-response analysis shows that cargo shock increases the freight rate but fleet shock decreases the freight rate. 3) Among the three cargo, fleet, and freight rate shocks, the freight rate shock is overwhelmingly largest. 4) The comparison of adjR² reveals that the fleet variable is most explained by the endogenous variables, i.e., cargo, fleet, and freight rate in each of shipping markets. 5) The estimation of co-integrating vectors shows that the increase of cargo increases the freight rate but the increase of fleet decreases the freight rate. 6) The estimation of adjustment speed demonstrates that the past-period positive deviation from the long-run equilibrium freight rate induces the decrease of present freight rate.

• Journal of Preventive Medicine and Public Health
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• v.56 no.5
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• pp.467-474
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• 2023

Objectives: Diabetes mellitus (DM) is a serious public health issue that places a heavy financial, social, and health-related burden on individuals, families, and healthcare systems. Self-reported health-related quality of life (HRQoL) is extensively used for monitoring the general population's health conditions and measuring the effectiveness of interventions. Therefore, this study investigated HRQoL and associated factors among patients with type 2 DM at a primary healthcare center in Indonesia. Methods: A cross-sectional study was conducted in Klaten District, Central Java, Indonesia, from May 2019 to July 2019. In total, 260 patients with DM registered with National Health Insurance were interviewed. HRQoL was measured with the EuroQol Group's validated Bahasa Indonesia version of the EuroQoL 5-Dimension 5-Level (EQ-5D-5L) with the Indonesian value set. Multivariate regression models were used to identify factors influencing HRQoL. Results: Data from 24 patients were excluded due to incomplete information. Most participants were men (60.6%), were aged above 50 years (91.5%), had less than a senior high school education (75.0%), and were unemployed (85.6%). The most frequent health problems were reported for the pain/discomfort dimension (64.0%) followed by anxiety (28.4%), mobility (17.8%), usual activities (10.6%), and self-care (6.8%). The average EuroQoL 5-Dimension (EQ-5D) index score was 0.86 (95% confidence interval [CI], 0.83 to 0.88). In the multivariate ordinal regression model, a higher education level (coefficient, 0.08; 95% CI, 0.02 to 0.14) was a significant predictor of the EQ-5D-5L utility score. Conclusions: Patients with diabetes had poorer EQ-5D-5L utility values than the general population. DM patients experienced pain/discomfort and anxiety. There was a substantial positive relationship between education level and HRQoL.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.168-178
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• 2021

Objective: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD). Materials and Methods: Aortic computed tomography angiographic images from 139 patients with TBAD were consecutively collected. We implemented a deep learning method based on a three-dimensional (3D) deep convolutional neural (CNN) network, which realizes automatic segmentation and measurement of the entire aorta (EA), true lumen (TL), and false lumen (FL). The accuracy, stability, and measurement time were compared between deep learning and manual methods. The intra- and inter-observer reproducibility of the manual method was also evaluated. Results: The mean dice coefficient scores were 0.958, 0.961, and 0.932 for EA, TL, and FL, respectively. There was a linear relationship between the reference standard and measurement by the manual and deep learning method (r = 0.964 and 0.991, respectively). The average measurement error of the deep learning method was less than that of the manual method (EA, 1.64% vs. 4.13%; TL, 2.46% vs. 11.67%; FL, 2.50% vs. 8.02%). Bland-Altman plots revealed that the deviations of the diameters between the deep learning method and the reference standard were -0.042 mm (-3.412 to 3.330 mm), -0.376 mm (-3.328 to 2.577 mm), and 0.026 mm (-3.040 to 3.092 mm) for EA, TL, and FL, respectively. For the manual method, the corresponding deviations were -0.166 mm (-1.419 to 1.086 mm), -0.050 mm (-0.970 to 1.070 mm), and -0.085 mm (-1.010 to 0.084 mm). Intra- and inter-observer differences were found in measurements with the manual method, but not with the deep learning method. The measurement time with the deep learning method was markedly shorter than with the manual method (21.7 ± 1.1 vs. 82.5 ± 16.1 minutes, p < 0.001). Conclusion: The performance of efficient segmentation and diameter measurement of TBADs based on the 3D deep CNN was both accurate and stable. This method is promising for evaluating aortic morphology automatically and alleviating the workload of radiologists in the near future.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.47-57
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• 2024

The purpose of this study was to analyze the Correlation Analysis between Awareness of the Serious Disaster and Safety Consciousness of Construction Workers under the Act on the Punishment of Serious. A survey was conducted on construction workers, construction managers, and safety managers. The results of this study were as follows; The correlation analysis conducted among the three groups indicated a significant correlation, with safety managers demonstrating the highest correlation, followed by construction managers and construction workers, and all three groups exhibited a moderate correlation. The correlation analysis conducted for the entire group also revealed a significant correlation, and as the number of participants increased, higher correlation coefficients were observed. Furthermore, to ascertain the significance of the correlation coefficients, a comparison was made between the p-value and the significance level (α). Consequently, a p-value smaller than the significance level of 0.05 was obtained, leading to the rejection of the null hypothesis and the acceptance of the alternative hypothesis. Therefore, it can be concluded that there is a relationship between the level of awareness of the serious Accidents Punishment Act and the level of Safety Consciousness of Construction. One limitation of this study is that it relied on a subjective indicator through a survey, which may introduce variability in the difficulty level of the questionnaire items.

• Journal of Oriental Neuropsychiatry
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• v.35 no.2
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• pp.163-175
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• 2024

Objectives: To investigate the relationship between rehabilitation treatment, mental state and resilience of stroke patients undergoing rehabilitation by examining the correlation between The Core Seven Emotions Inventory-Short Form (CSEI-s) and the Korean version of the Connor-Davidson Resilience Scale (K-CD-RISC). Methods: All 104 participants (44 diagnosed with stroke who were receiving rehabilitation and 60 without stroke or psychiatric history) completed the CSEI-s, K-CD-RISC, and Questionnaire for stroke symptoms. All data were analyzed using by Statistical Package for the Social Sciences (SPSS) ver. 27.0. Descriptive statistics, chi-square test, t-test, Mann-Whitney U test, Kruskal-Wallis H test, and Pearson correlation coefficient were used for data analysis. Results: As a result of the CSEI-s, compared to the control group, the stroke group showed significantly lower Joy (喜) scores and significantly higher scores for Depression (憂) and Sorrow (悲). With a morbidity period of 12 months or less, the Thought (思) score was significantly higher. The Fear (恐) score was significantly higher when the rehabilitation was initiation more than 4~8 weeks after than that when the treatment was started immediately. Meanwhile, the K-CD-RISC score was significantly higher when rehabilitation was started immediately. In the stroke group, the K-CD-RISC score was positively correlated with Joy (喜) but negatively correlated with Depression (憂) and Fear (恐). In the control group, K-CD-RSIC showed a positive correlation with Joy (喜) but negative correlations with Depression (憂), Sorrow (悲), and Fear (恐). Conclusions: In addition to early rehabilitation treatment, mental approach through Korean medicine psychotherapy is crucial for enhancing the resilience of stroke patients.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.632-643
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• 2020

Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008-0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.662-670
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• 2019

Objective: A developmental venous anomaly (DVA) is a vascular malformation of ambiguous clinical significance. We aimed to quantify the susceptibility of draining veins (χ_vein) in DVA and determine its significance with respect to oxygen metabolism using quantitative susceptibility mapping (QSM). Materials and Methods: Brain magnetic resonance imaging of 27 consecutive patients with incidentally detected DVAs were retrospectively reviewed. Based on the presence of abnormal hyperintensity on T2-weighted images (T2WI) in the brain parenchyma adjacent to DVA, the patients were grouped into edema (E+, n = 9) and non-edema (E-, n = 18) groups. A 3T MR scanner was used to obtain fully flow-compensated gradient echo images for susceptibility-weighted imaging with source images used for QSM processing. The χ_vein was measured semi-automatically using QSM. The normalized χ_vein was also estimated. Clinical and MR measurements were compared between the E+ and E- groups using Student's t-test or Mann-Whitney U test. Correlations between the χ_vein and area of hyperintensity on T2WI and between χ_vein and diameter of the collecting veins were assessed. The correlation coefficient was also calculated using normalized veins. Results: The DVAs of the E+ group had significantly higher χ_vein (196.5 ± 27.9 vs. 167.7 ± 33.6, p = 0.036) and larger diameter of the draining veins (p = 0.006), and patients were older (p = 0.006) than those in the E- group. The χ_vein was also linearly correlated with the hyperintense area on T2WI (r = 0.633, 95% confidence interval 0.333-0.817, p < 0.001). Conclusion: DVAs with abnormal hyperintensity on T2WI have higher susceptibility values for draining veins, indicating an increased oxygen extraction fraction that might be associated with venous congestion.

• Journal of Cardiovascular Imaging
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• v.31 no.3
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• pp.145-149
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• 2023

BACKGROUND: ¹⁸F-sodium fluoride positron emission tomography/computed tomography (¹⁸F-NaF PET/CT) has been proven to be useful in identification of microcalcifications, which are stimulated by inflammation. Blood speckle imaging (BSI) is a new imaging technology used for tracking the flow of blood cells using transesophageal echocardiography (TEE). We evaluated the relationship between turbulent flow identified by BSI and inflammatory activity of the aortic valve (AV) as indicated by the ¹⁸F-NaF uptake index in moderate aortic stenosis (AS) patients. METHODS: This study enrolled 18 moderate AS patients diagnosed within the past 6 months. BSI within the aortic root was acquired using long-axis view TEE. The duration of laminar flow and the turbulent flow area ratio were calculated by BSI to demonstrate the degree of turbulence. The maximum and mean standardized uptake values (SUVmax, SUVmean) and the total microcalcification burden (TMB) as measured by ¹⁸F-NaF PET/CT were used to demonstrate the degree of inflammatory activity in the AV region. RESULTS: The mean SUVmean, SUVmax, and TMB were 1.90 ± 0.79, 2.60 ± 0.98, and 4.20 ± 2.18 mL, respectively. The mean laminar flow period and the turbulent area ratio were 116.1 ± 61.5 msec and 0.48 ± 0.32. The correlation between SUVmax and turbulent flow area ratio showed the most positive and statistically significant correlation, with a Pearson's correlation coefficient (R²) of 0.658 and a p-value of 0.014. CONCLUSIONS: The high degree of trans-aortic turbulence measured by BSI was correlated with severe AV inflammation.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.739-747
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• 2024

The purpose of this study was to identify the relationship between nursing students' COVID-19-related knowledge, perception of infection risk, and health beliefs and infection prevention behaviors, and to identify the factors influencing COVID-19 prevention behaviors, and to provide the necessary basic data for the preparation of measures to improve the infection prevention behaviors of nursing students. Data were collected from 161 nursing students 4th in G city. Data analysis was analyzed by descriptive statistics, Independant t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis using the SPSS 21.0 program.. AS a result of this study, Preventive Behaviors was found to have significant positive correlations with COVID-19 Risk Perception(r=.217, p=.006), Health Belief Model of Perceived benefit(r=.206, p=.009) and negative correlations with Perceived barriers(r=-.219, p=.005). The most influential factors the Preventive Behaviors of nursing students were the Perceived benefit (β=.17, p<.001), mental health status after COVID-19(β=.188, p=.014), and these factors explained 58% in Preventive Behaviors(F=9.686, p=.000). In conclusion, it is expected that nursing students' health belief promotion programs, infection-related curriculum, and emotional support programs can be developed and applied to improve the degree of infection prevention behaviors.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.299-307
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• 2023

Given that toxic substances are diffused by the various movements of the atmosphere, it is very important to evaluate the risks associated with this phenomenon. When analyzing the behavioral characteristics of these atmospheric diffusion models, the main input data are the wind speed and wind direction among the meteorological data. In particular, it is known that a certain wind direction occurs in summer and winter in Korea under the influence of westerlies and monsoons. In this study, synoptic meteorological observation data provided by the Korea Meteorological Administration were analyzed from January 1, 2012 to the end of August of 2022 to understand the regional wind characteristics of nuclear power plants and surrounding areas. The selected target areas consisted of 16 weather stations around the Hanbit, Kori, Wolsong, Hanul, and Saeul nuclear power plants that are currently in operation. The analysis was based on the temperature, wind direction, and wind speed data at those locations. Average, maximum, minimum, median, and mode values were analyzed using long-term annual temperature, wind speed, and wind direction data. Correlation coefficient values were also analyzed to determine the linear relationships among the temperature, wind direction, and wind speed. Among the 16 districts, Uljin had the highest wind speed. The median wind speed values for each region were lower than the average wind speed values. For regions where the average wind speed exceeds the median wind speed, Yeongju, Gochang, Gyeongju, Yeonggwang, and Gimhae were calculated as 0.69 m s^-1, 0.54m s^-1, 0.45m s^-1, 0.4m s^-1, and 0.36m s^-1, respectively. The average temperature in the 16 regions was 13.52 degrees Celsius; the median temperature was 14.31 degrees and the mode temperature was 20.69 degrees. The average regional temperature standard deviation was calculated and found to be 9.83 degrees. The maximum summer temperatures were 39.7, 39.5, and 39.3 in Yeongdeok, Pohang, and Yeongcheon, respectively. The wind directions and speeds in the 16 regions were plotted as a wind rose graph, and the characteristics of the wind direction and speed of each region were investigated. It was found that there is a dominant wind direction correlated with the topographical characteristics in each region. However, the linear relationship between the wind speed and direction by region varied from 0.53 to 0.07. Through this study, by evaluating meteorological observation data on a long-term synoptic scale of ten years, regional characteristics were found.