• Physical Therapy Rehabilitation Science
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• v.11 no.4
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• pp.478-487
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• 2022

Objective: This study was conducted to analyze the effect of wearable complex muscle support system on energy efficiency during walking in elderly. Design: Cross sectional study Methods: Twenty healthy elderly participated in this study. All subjects performed a 6 minuteswalk test(6MWT) and stair climbing test in dual, slack and no suit conditions. In each condition, oxygen consumption(VO₂), metabolic equivalents(METs), energy expenditure measures(EEm), physiological cost index(PCI), walking velocity and heartrate were measured. Through repeated measured ANOVA, it was investigated whether there was a statistically significant difference in the measurement results between the three conditions. Results: In over-ground walking, VO₂, METs and EEm showed significant differences between no suit and slack conditions(p<0.05). In stair climbing, VO₂ showed significant difference between slack and dual conditions(p<0.05). Also, METs and EEm showed significant differences between no suit and slack, and between slack and dual conditions(p<0.05). Conclusions: Wearing the wearable complex muscle support system for elderly does not have much benefit in energy metabolism efficiency in over-ground, but there is a benefit in stair walking.

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Clinical Nutrition Research
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• v.12 no.2
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• pp.138-153
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• 2023

The prevalence of metabolic syndrome (MetS) and its cost are increasing due to lifestyle changes and aging. This study aimed to develop a deep neural network model for prediction and classification of MetS according to nutrient intake and other MetS-related factors. This study included 17,848 individuals aged 40-69 years from the Korea National Health and Nutrition Examination Survey (2013-2018). We set MetS (3-5 risk factors present) as the dependent variable and 52 MetS-related factors and nutrient intake variables as independent variables in a regression analysis. The analysis compared and analyzed model accuracy, precision and recall by conventional logistic regression, machine learning-based logistic regression and deep learning. The accuracy of train data was 81.2089, and the accuracy of test data was 81.1485 in a MetS classification and prediction model developed in this study. These accuracies were higher than those obtained by conventional logistic regression or machine learning-based logistic regression. Precision, recall, and F1-score also showed the high accuracy in the deep learning model. Blood alanine aminotransferase (β = 12.2035) level showed the highest regression coefficient followed by blood aspartate aminotransferase (β = 11.771) level, waist circumference (β = 10.8555), body mass index (β = 10.3842), and blood glycated hemoglobin (β = 10.1802) level. Fats (cholesterol [β = -2.0545] and saturated fatty acid [β = -2.0483]) showed high regression coefficients among nutrient intakes. The deep learning model for classification and prediction on MetS showed a higher accuracy than conventional logistic regression or machine learning-based logistic regression.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.589-599
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• 2024

Dispersion occurs when clay soil disperses under specific conditions and is rapidly washed away. While there are numerous methods for rectifying it, they are neither cost nor time-effective. The current study used metakaolin and zeolite to improve heavily dispersive clay soil either separately or in combination at 0%, 2%, 4%, 6%, and 8% of the soil weight. After 7 days of curing, the samples were tested to determine the extent of change in the dispersion potential, as well as the improvement of the geotechnical properties of the soil. The results indicated that the addition of 2% zeolite with 6% to 8% metakaolin decreased the dispersion potential considerably. Double hydrometry test findings revealed that the dispersion potential decreased by almost 70% and entered the non-dispersive group; the crumb test also revealed this. Atterberg limits testing indicated a decrease in the plasticity index which reduced the flexibility of the samples. The greatest decrease in PI (67.5%) was achieved with the addition of 8% zeolite plus 8% metakaolin to the soil. The results of density tests revealed that a decrease in the optimal moisture content increased the maximum dry density of soil. This increase in density was a response to the high reactivity of metakaolin with calcium hydroxide and the formation of calcium hydroxide hydrate gel. This eventually caused an increase in the unconfined compressive strength, the greatest increase in strength of about 1.8-fold was observed with a combination of 2% zeolite and 6% metakaolin compared to the unmodified sample.

• Steel and Composite Structures
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• v.52 no.2
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• pp.145-163
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• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.

• Elastomers and Composites
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• v.59 no.2
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• pp.51-63
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• 2024

Polypropylene (PP) is a commodity plastic that is widely used owing to its cost-effectiveness, lightweight nature, easy processability, and outstanding chemical and thermomechanical characteristics. However, the imperative to address energy and environmental crises has spurred global initiatives toward a circular economy, necessitating sustainable alternatives to traditional fossil-fuel-derived plastics. In this study, we conducted a series of comparative investigations of bio-based polypropylene (bio-PP) blends with current PP of the same and different grades. An extrusion-based processing methodology was employed for the bio-PP composites. Talc was used as an active filler for the preparation of the composites. A comparative analysis with the current petroleum-based PP indicated that the thermal properties and tensile characteristics of the bio-PP blends and composites remained largely unaltered, signifying the feasibility of bio-PP as a potential substitute for the current PP. To achieve a higher Young's modulus, elongation at break (EAB), and melt flow index (MFI), we prepared different composites of PP of different grades and bio-PP with varying talc contents. Interestingly, at higher biomass contents, the composites exhibited higher MFI and EAB values with comparable Young's moduli. Notably, the impact strengths of the composites with various biomass and talc contents remained unaltered. In-depth investigations through surface analysis confirmed the uniform dispersion of talc within the composite matrix. Furthermore, the moldability of the bio-PP composites was substantiated by comprehensive rheological property assessments encompassing shear rate and shear viscosity. Thus, from these outcomes, the fabricated bio-PP-based composites could be an alternative to petroleum-based PP composites for sustainable automobile applications.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.171-180
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• 2007

Reliability analysis of prestressed steel and concrete(PSSC) girders is conducted for deflection, stress and moment strength limit state. PSSC girder has strong advantages in terms of construction cost and vertical clearance for the span length of over 40 meters. In this paper, example PSSC girders with different span lengths, section dimensions and design stress levels are designed and analyzed to calculate the midspan deflection, stress and the section moment strength. Deflection limit state, stress limit state and strength limit state functions are assumed and the reliability indexes are obtained by Monte-Carlo simulation and Rackwitz-Fiessler procedure. The results show that the reliability of PSSC girder for deflection limit state is appropriately higher than the stress limit state and the reliability for moment strength is significantly conservative.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.409-420
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• 2012

Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately $6.47km^2$ from $9.01km^2$ to $2.54km^2$, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately $0.342km^2$ in the dry season and $0.421km^2$ overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.

• Journal of Aquaculture
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• v.16 no.3
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• pp.190-195
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• 2003

Dietary optimum ratio of frozen raw fish and commercial compound meal (CCM) in moist pellet (MP) were investigated to improve the growth rate, and feed and economical efficiency in the flounder, Paralichthys olivaceus. Experimental fish (average body weight, about 48 g) were divided into 6 groups and each group was fed with raw fish (FRF), and MPs (ratio of raw fish and CCM=9:1, 8:2, 7:3, 6:4 and 5:5) for 10 weeks. The 9:1, 8:2, 7:3, 6:4, 5:5 groups showed no significant difference in weight gain as 203.5~217.3%, while the FRF group showed significantly low growth rate as 183.1%(P<0.05). The feed efficiency gradually increased with the increase in the ratio of CCM and was the highest in the 5:5 group as 89.7%. As a result of analysis of body composition after the experiment, moisture was significantly low in the 7:3 group (P<0.05) and crude protein was significantly low in the 9:1 group (P<0.05). The crude lipid increased as the ratio of raw fish increased, and it was the highest in the raw fish group (8.3%) and the lowest in the 5:5 group (4.6%). There were no significant difference in hepatosomatic index (HSI) and condition factor(CF) among the experimental groups. Visceralsomatic index (VSI) increased with the increase in the ratio of raw fish and was significantly high in the raw fish group as 5.49 (P<0.05). For the unit cost of feed, it was found that raw fish was economical when mackerel, a source of raw feed, was 400 won/kg, while the ratio of 5:5 was economical when it was more than 500 won/kg. Results of this study concluded that sole use of raw feed is not desirable in view of growth, environment and economy, and the 5:5 group showed highest effect under the least use of raw feed.

• Health Policy and Management
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• v.34 no.1
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• pp.78-86
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• 2024

Background: The purpose of this study was to determine the effectiveness of the specialty hospital system by comparing the medical use of inpatients who had artificial joint replacement surgery in specialty hospitals and non-specialty hospitals. Methods: This study utilized 2021-2022 healthcare benefit claims data provided by the Health Insurance Review and Assessment Service. The dependent variable is inpatient medical use which is measured in terms of charges per case and length of stay. The independent variable was whether the hospital was designated as a specialty hospital, and the control variables were patient-level variables (age, gender, insurer type, surgery type, and Charlson comorbidity index) and medical institution-level variables (establishment type, classification, location, number of orthopedic surgeons, and number of nurses). Results: The results of the multiple regression analysis between charges per case and whether a hospital is designated as a specialty hospital showed a statistically significant negative relationship between charges per case and whether a hospital is designated as a specialty hospital. This suggests a significant low in charges per case when a hospital is designated as a specialty hospital compared to a non-specialty hospital, indicating that there is a difference in medical use outcomes between specialty hospitals and non-specialty hospitals inpatients. Conclusion: The practical implications of this study are as follows. First, the criteria for designating specialty hospitals should be alleviated. In our study, the results show that specialty hospitals have significantly lower per-case costs than non-specialty hospitals. Despite the cost-effectiveness of specialty hospitals, the high barriers to be designated for specialty hospitals have gathered the specialty hospitals in metropolitan and major cities. To address the regional imbalance of specialty hospitals, it is believed that ease the criteria for designating specialty hospitals in non-metropolitan areas, such as introducing "semi-specialty hospitals (tentative name)," will lead to a reduction in health disparities between regions and reduce medical costs. Second, it is necessary to determine the appropriateness of the size of hospitals' medical staff. The study found that the number of orthopedic surgeons and nurses varied in charges per case. Therefore, it is believed that appropriately allocating hospital medical staff can maximize the cost-effectiveness of medical services and ultimately reduce medical costs.