• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Food Science and Preservation
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• v.31 no.4
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• pp.633-644
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• 2024

This study investigated the fermentation characteristics and quality attributes of ale beer brewed with MBA grapes to enhance the diversity of Korean domestic ale beers. The grapes were added to the wort in two forms: must and juice, at ratios of 10% and 20%. The results showed that while ale beer with 20% grape addition began fermentation a day later, all samples completed fermentation well on the sixth day. Increasing MBA grape content lowered the pH and increased total acidity and malic acid content without significantly affecting the sour taste. Higher grape addition also decreased the beer's IBU and bitterness scores in sensory evaluation. The addition of must addition enhanced redness due to anthocyanins, significantly increasing color intensity and EBC value of ale beer. Ale beer with the addition of must exhibited higher antioxidant capacities in total phenolic compound content, DPPH radical scavenging, and FRAP activities compared to that with the addition of juice. Sensory evaluation indicated that ale beer with 20% juice addition was preferred for its color, aroma, sweetness, body, and overall preference. The addition of MBA must improved antioxidant capacity, but ale beer with 20% juice had superior sensory qualities.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.377-384
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• 2024

In chronic stroke patients, respiratory muscle weakness leads to decreased pulmonary function and balance ability. Therefore, this study was conducted to investigate the effects of respiratory training using a device and training methods that apply resistance to respiratory muscles on pulmonary function, thoracic cage expansion, and balance. A total of 20 participants were included in the study, divided into two groups: Respiratory Training Group 1 (n:10) using a resistive inspiratory device and Respiratory Training Group 2 (n:10) undergoing chest expansion resistance training. Lung function, the Korean Version of the Trunk Impairment Scale (K-TIS), Chest Expansion Measurement (CEM), and the Functional Reach Test (FRT) were assessed before and after the respiratory training. The training was conducted five times a week for a total of six weeks. Both Respiratory Training Group 1 and Group 2 showed significant improvements in lung function, K-TIS, CEM, and FRT scores, with no significant differences between the groups. The results of this study showed that breathing training using a device and breathing training that applied resistance to respiratory muscles were effective for pulmonary function, thoracic cage expansion, and balance, and that breathing training that applied direct resistance to respiratory muscles had a positive effect on strengthening respiratory muscles and improving balance ability, and that it was judged important to perform it in conjunction with general rehabilitation treatment for chronic stroke patients for functional recovery.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.35-46
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• 2024

This study aimed to examine the effects of an art rehabilitation program developed based on the fine motor skills component of the Korean Bayley Scales of Infant and Toddler Development(K-Bayley-III) on the fine motor development of children with developmental delays. Early intervention programs for children with developmental delays are crucial, as they can significantly enhance motor skills during formative stages. The study focused on a 36-month-old boy with delayed fine motor development, and the program was implemented twice a week for a total of 40 sessions. The program included the following areas: Eye Movement Control, Early Stage Hand Movements, Reaching in Space, Object Grasping and Manipulation, Bilateral Coordination, Pre-writing Skills and Pencil Grasp, Finger and Hand Movement Control, Tool Use and Motor Planning. Pre- and post-program assessments were conducted to evaluate the effectiveness of the program, and the changes in the child were qualitatively analyzed. The results confirmed that the child's scores in the fine motor domain improved and his hand and finger manipulation skills improved. This study suggests the use of an art rehabilitation program to promote fine motor development in children, and serves as a foundation for their further developmental progress.

• Journal of Nutrition and Health
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• v.57 no.5
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• pp.496-507
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• 2024

Purpose: This study examined the nutritional status and Korean Healthy Eating Index (KHEI) scores pre- and post-coronavirus disease 2019 (COVID-19) outbreak in elderly men and women living in rural areas. Methods: The participants were 1,747 rural elderly people aged 65 or older who participated in the nutritional survey of the 2018-2021 Korea National Health and Nutrition Survey. The nutrient intake was estimated from a 24-hour recall. Results: Following the COVID pandemic, the intake of fat, saturated fatty acids, and sodium increased in elderly men and women, whereas the intake of thiamine decreased. In elderly men, the intake of protein, niacin, and vitamin D decreased, but the sugar intake increased. In elderly women, the cholesterol intake increased. The KHEI score was significantly lower in rural elderly men and women after the pandemic than before (male: 62.60 ± 0.56 for the post-COVID-19 and 64.76 ± 0.75 for the pre-COVID-19, p < 0.05; female: 64.07 ± 0.80 for the post-COVID-19 and 64.47 ± 0.62 for the post-COVID-19, p < 0.001). Regarding the KHEI component, in men, the intake of meat, fish, and legumes, all sources of protein, decreased significantly after the COVID-19 pandemic. In women, the total food intake and the intake of breakfast decreased significantly after the pandemic. In the moderation components, men were unable to limit their total sugar and sodium intake, while women were unable to control their saturated fatty acids and sodium intake. Furthermore, considering the total KHEI score, both elderly men and women had decreased values in the moderation and adequacy components following COVID-19. Conclusion: These results provide foundational data for elderly nutrition policies or educational programs targeting the elderly population in rural areas in similar pandemic situations in the future.

• Korean Journal of Community Nutrition
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• v.29 no.5
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• pp.406-417
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• 2024

Objectives: Recently, food insecurity has been a major public health issue along with the food crisis caused by COVID-19, climate change, and the polarization of food supply due to socioeconomic disparities. Food insecurity is known to be related to the food choices and environment of the consumer. Therefore, this study aimed to evaluate the food security statuses of adults in Jeju and investigate their food purchase patterns, food policy recognition, and food environment satisfaction. Methods: Based on data from the 2022 Jeju Food Survey, 346 adults aged ≥ 19 years in Jeju were classified into food security and insecurity groups (quantitatively and qualitatively) using the questionnaire. Food purchase patterns, including purchasing frequency, items, and reasons, were surveyed for local and eco-friendly foods. The recognition and necessity of several food policies and satisfaction with diet and food environment (availability, accessibility, affordability, accommodation, and acceptability) were measured using the Likert scale. Results: Among the total participants, 47.4% were in the food insecurity group. The frequency of purchasing local and eco-friendly foods did not significantly differ by food security status. The insecurity group exhibited a higher recognition rate of basic rights to food (36.0%) than the security group (24.7%, P = 0.023). The recognition and necessity of specific food policies did not significantly differ by food security status, except for the policy of promoting food communities, for which the food security group exhibited higher recognition than the food insecurity group did (P = 0.004). The food insecurity group exhibited significantly lower scores regarding satisfaction toward diet and food environment factors (P < 0.05 for all). Conclusion: Overall, the food security group reported higher satisfaction with their diet and food environment than the food insecurity group. Further in-depth studies to investigate the determinants of food insecurity and effective promotional strategies for food policies are needed.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.4
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• pp.45-55
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• 2024

This study aims to distinguish between utilitarian walking and leisure walking activities and analyze the correlation between these types of walking and the walking environment. To measure the walking environment, we utilized Google Street View (GSV) and employed semantic segmentation deep learning techniques to quantitatively assess urban walking environment elements as perceived by pedestrians. A survey was conducted to measure utilitarian walking, leisure walking, and perceived walking environment satisfaction, collecting valid responses from 192 participants. Using the survey data, we visualized utilitarian walking, leisure walking, and perceived walking environment satisfaction, and analyzed the correlation between these variables and the walkability scores. The results indicated that leisure walking had a significant positive correlation with walkability (Pearson's r = 0.121, p-value = 0.012), while there was no significant correlation between utilitarian walking and walkability (Pearson's r = 0.093, p-value = 0.055). These findings suggest that people prioritize mobility efficiency over the walking environment for utilitarian walking, whereas the quality of the walking environment significantly influences the frequency of leisure walking. Based on these results, the study proposes specific strategies to improve the walking environment around residential areas to promote leisure walking. These strategies include creating vertical gardens or various forms of three-dimensional gardens on narrow walkways and improving sidewalk design. The findings of this study can contribute to promoting leisure walking by creating walk-friendly environments, ultimately enhancing urban sustainability and the quality of life for residents.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.4
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• pp.1-17
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• 2024

This study analyzed the behaviors and satisfaction of park users in nine parks representing first and second-generation new towns, aiming to propose directions for planning new town parks. According to the analysis, park users in new towns mainly visit parks for purposes such as relaxation, strolling, and exercise, often with family, alone, or with friends. They typically spend 1-2 hours in the park and mostly access it on foot. Additionally, satisfaction with park accessibility is high, particularly among pedestrians. Satisfaction survey results indicate that pedestrian pathways, trees and vegetation, water features, rest areas, and cultural facilities have the greatest impact on overall park satisfaction. Playgrounds and sports facilities show relatively lower satisfaction levels, indicating a need for improvement. Furthermore, according to NPS analysis, park users are highly willing to recommend parks, especially with Gwanggyo Lake Park and Dongtan Central Park receiving high recommendation scores. IPA analysis shows that pathways and vegetation are perceived as highly important and satisfactory, while playgrounds and sports facilities are categorized as areas needing improvement. Thus, there is a need to consider improvement strategies for each. Additionally, identifying park users' grievances can lead to creating a better park environment. Finally, concerning the planning direction for new town parks, linear-shaped parks facilitating walking are preferred, with parks preserving natural terrain and forests deemed the most desirable. Based on these results, future city parks, including those in the third-generation new towns, should harmonize with nature and prioritize pedestrian access.

• The Mathematical Education
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• v.63 no.3
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• pp.485-503
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• 2024

The purpose of this study is to analyze elementary school teachers' mindsets about students' mathematical ability. For this purpose, we developed a 20-item scale to measure teachers' mindset through a review of the literature. In order to verify the developed scale, a survey was conducted among 158 elementary school teachers, and the structure of the items was analyzed by exploratory factor analysis. As a result, three factors were identified: "growth mindset toward change in mathematical ability", "fixed mindset toward change in mathematical ability", and "mindset toward innate mathematical ability". Four groups were distinguished by latent profile analysis, using the scores on these three factors as variables, to characterize the different groups of teachers based on their mindset. The groups with the most participants in the study were, in order, growth mindset teachers, neutral mindset teachers, strong growth mindset teachers, and fixed mindset teachers. Interviews were also conducted with representative participants from each group to learn more about the characteristics of teachers in each profile. Based on the results of the study, we discussed the implications of mindset in terms of the classification of teachers' mindset about students' mathematical ability, the popularity of growth mindset among elementary school teachers in Korea, and research on teachers' mindset about innate mathematical ability.