• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.79-88
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• 2024

The study aim was to investigate the relationship between adolescents' physical activity and subjective health perceptions and determine whether body mass index (BMI), an obesity-related indicator, had a mediating or moderating effect on this relationship. To achieve the purpose of this study, raw data from the 18th Youth Health Behavior Online Survey (2022) were used, and data from 23,612 people were ultimately selected for the research analysis. A confirmatory factor analysis and structural equation modeling were applied to the data, and bootstrapping techniques were used to verify the mediating effect. To verify the moderating effect, a multigroup analysis of the structural equation model was applied to calculate pairwise parameter comparison values. All statistical significance levels were set at .05. The results of this study follow. First, the greater the amount of physical activity among adolescents, the more positive was the effect on subjective health perception. Second, subjective body type perception had a partial mediating effect on the relationship between physical activity and subjective health perception. Third, subjective body type had a moderating effect on physical activity and subjective health perception. Specifically, people who perceived their subjective body types as average viewed their subjective health more positively when they engaged in more physical activity than those who perceived their body types as slightly or very overweight. In conclusion, preventing obesity and positively changing the subjective health status through sufficient physical activity during adolescence are important.

• The korean journal of orthodontics
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• v.54 no.1
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• pp.48-58
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• 2024

Objective: To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs. 1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANS-mid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions: The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.

• Advances in nano research
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• v.16 no.2
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• pp.127-140
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• 2024

Upon direct/indirect exposure to flame or heat, composite structures may burn or thermally buckle. This issue becomes more important in the natural fiber-based composite structures with higher flammability and lower mechanical properties. The main goal of the present study was to obtain an optimal eco-friendly composite system with low flammability and high thermal buckling resistance. The studied composite consisted of polypropylene (PP) and short abaca fiber (AF) with eggshell powder (ESP) and halloysite clay nanotubes (HNTs) additives. An optimal base composite, consisting of 30 wt.% AF and 70 wt.% PP, abbreviated as OAP, was initially introduced based on burning rate (BR) and the Young's modulus determined by horizontal burning test (HBT) and tensile test, respectively. The effects of adding ESP to the base composite were then investigated with the same experimental tests. The results indicated that though the BR significantly decreased with the increase of ESP content up to 6 wt.%, it had a very destructive influence on the stiffness of the composite. To compensate for the damaging effect of ESP, small amount of HNT was used. The performance of OAP composite with 6 wt.% ESP and 3 wt.% HNT (OAPEH) was explored by conducting HBT, cone calorimeter test (CCT) and tensile test. The experimental results indicated a 9~23 % reduction in almost all flammability parameters such as heat release rate (HRR), total heat released (THR), maximum average rate of heat emission (MARHE), total smoke released (TSR), total smoke production (TSP), and mass loss (ML) during combustion. Furthermore, the combination of 6 wt.% ESP and 3 wt.% HNT reduced the stiffness of OAP to an insignificant amount by maximum 3%. Moreover, the char residue analysis revealed the distinct differences in the formation of char between AF/PP and AF/PP/ESP/HNT composites. Afterward, dilatometry test was carried out to examine the coefficient of thermal expansion (CTE) of OAP and OAPEH samples. The obtained results showed that the CTE of OAPEH composite was about 18% less than that of OAP. Finally, a theoretical model was used based on first-order shear deformation theory (FSDT) to predict the critical bucking temperatures of the OAP and OAPEH composite plates. It was shown that in the absence of mechanical load, the critical buckling temperatures of OAPEH composite plates were higher than those of OAP composites, such that the difference between the buckling temperatures increased with the increase of thickness. On the contrary, the positive effect of CTE reduction on the buckling temperature decreased by raising the axial compressive mechanical load on the composite plates which can be assigned to the reduction of stiffness after the incorporation of ESP. The results of present study generally stated that a suitable combination of AF, PP, ESP, and HNT can result in a relatively optimal and environmentally friendly composite with proper flame and thermal buckling resistance with no significant decline in the stiffness.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.3
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• pp.13-26
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• 2023

Objective : The purpose of this study is to examine the impact of maternal risk factors for adverse childhood experiences on children's emotional and physical abuse and neglect as well as parenting stress. Methods : This is a secondary data analysis study utilizing raw data from the 2017 National Survey of Child and Family Life Experiences. A total of 1,937 mothers with at least one adverse childhood experience were categorized into low-risk (1-3), moderate-risk (4-6), and high-risk (7 or more) groups to examine the differences in children's emotional and physical abuse and neglect and parenting stress and identify the influencing factors through regression analysis. Results : Maternal adverse childhood experiences were 50.4% in the low-risk group, 39.8% in the medium-risk group, and 9.7% in the high-risk group. Child emotional abuse was 45.0%, child physical abuse was 13.2%, child neglect was 3.5%, and parenting stress was 2.13 (±0.61) on average. Adverse childhood experiences were significantly more likely to be associated with emotional and physical abuse, neglect, and parenting stress in the medium- and high-risk groups than in the low-risk group. The regression analysis showed that the model explained 35% of child emotional abuse, 25% of child physical abuse, 19% of child neglect, and 16% of parenting stress. Conclusion : The higher the risk of adverse childhood experiences of parents, the more their children experience emotional abuse, physical abuse, child neglect, and parenting stress.

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• Imaging Science in Dentistry
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• v.54 no.1
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• pp.81-91
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• 2024

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion: This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.

• Particle and aerosol research
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• v.19 no.4
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• Industry Promotion Research
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• v.9 no.3
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• pp.295-309
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• 2024

With the implementation of the Northeast Revitalization Strategy, the tourism industry in Heilongjiang Province had an increasingly greater impact on regional economic development. Based on the tourism panel data of Heilongjiang Province from 2005 to 2021, this paper used DEA-BCC and Malmquist Index to analyze the static and dynamic changes of the tourism industry.The results of the study were as follows: (1) Static: The OE value reached strong DEA effectiveness in 2010, 2013, and 2019, indicated that tourism resources had been fully utilized. The SE value changed dramatically between 0.354 and 1, and the PTE value approached 1. OE was mainly affected by SE changes. (2) Dynamic: The total factor productivity (TFP) was overall greater than 1 and grew at an average annual rate of 13.8%. The variation in TFP was primarily influenced by the index of technological progress, indicated that the tourism industry in Heilongjiang Province made full use of technology for resource development, with a relatively high level of development efficiency. Therefore, the future focus of Heilongjiang Province's tourism industry will be on adjustments in industrial scale, technological innovation, and policy optimization.

• Journal of Family Resource Management and Policy Review
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• v.28 no.2
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• pp.27-38
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• 2024

The purpose of this study was to identify issues in the family support center evaluation project by analyzing the differences in perception between evaluators and the family Support center using a meta-evaluation analysis model and seeking improvement alternatives. The results revealed a significant difference in group average: the evaluator group scored 4.21 out of 5 points, and the family center group scored 3.20 points. The improvement alternatives for each meta-evaluation item are as follows. In the evaluation environment, it is necessary to specify the purpose and utilization of evaluation within the guidelines of the Ministry of Gender Equality and Family. Evaluation input required the establishment of an evaluation support organization within the Korean Institute for Healthy Family. During the evaluation process, it was necessary to improve the use of the integrated family support information system and diversify communication channels. The evaluation results required the strengthening of follow-up education for family centers. In terms of evaluation utilization, it was necessary to strengthen support for various incentives and subcenters. This study provides implications for improving the evaluation system for various policy service delivery systems.