• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1025-1031
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• 2023

We aimed to evaluate the radiation dose and image quality by changing the Scout view voltage in low-dose chest CT (LDCT) and applying scan parameters such as AEC (auto exposure control) and ASIR (adaptive statistical iterative reconstruction) to find the optimal protocol. Scout view voltage was varied at 80, 100, 120, 140 kV and after measuring the dose 5 times using the existing low-dose chest CT protocol, the appropriate kV was selected for the study using the Dose report provided by the equipment. After taking a basic LDCT shot at 120 kV, 30 mAs, ASIR 50% was applied to this condition. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed by measuring Background noise (B/N). For dose comparison, CTDI_vol and DLP provided by the equipment were compared and analyzed using the formulas. The results indicated that the protocol of scout 140 + LDCT + ASIR 50 + AEC reduced radiation exposure and improved image quality compared to traditional LDCT, providing an optimal protocol. As demonstrated in the experiment, LDCT screenings for asymptomatic normal individuals are crucial, as they involve concerns over excessive radiation exposure per examination. Therefore, applying appropriate parameters is important, and it is expected to contribute positively to the public health in future LDCT based health screenings.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.9-17
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• 2024

When constructing on soft ground, managing ground settlement and safety is crucial. However, there often exists a significant disparity between the actual behavior of the ground and the design plans. In this study, we aimed to compare and analyze the difference between the predicted settlement based on theoretical formulas and the measured settlement during construction, in order to predict settlement. For this purpose, we analyzed settlement data from 18 construction sites. The results indicated that the back analysis settlement values were similar to the measured settlement values, whereas the design settlement values were significantly higher compared to the measured settlement values. Specifically, the design settlement values were 1.2 to 1.4 times higher than those derived from back analysis using measured values. The RMSE analysis revealed a value of 0.6212m for the design settlement and 0.1697m for the back analysis settlement. The difference between the back analysis settlement and the measured settlement was more than 70% lower than the difference between the design settlement and the measured settlement. This indicates that the back analysis settlement values exhibit lower error rates compared to the design settlement values.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.263-276
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• 2024

Since the first introduction of one-dimensional transient storage modeling in the field of solute transport analysis in rivers, its application has notably expanded for various purposes, including for hydrology and geobiology over the past few decades. Despite strides in refining transient storage models, there remain unresolved challenges in simplifying complex river transport dynamics into concise formulas and a limited set of parameters. This review paper is dedicated to cataloging and assessing existing transient storage models, outlining the difficulties associated with model structures, parameters, and data, and suggesting directions for future research. We seek to enhance understanding of transient storage by highlighting the importance of continuously evaluating residence time distribution modeling, integrating hydrodynamic models, and using data with minimal assumptions. This paper would contribute to advance our comprehension of the transient storage process, offering insights into sophisticated modeling techniques, pinpointing uncertainty in parameters, and suggesting the necessary avenues for further study.

• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• Earthquakes and Structures
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• v.26 no.2
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• pp.97-115
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• 2024

In this paper, a database consisting of the dynamic shear modulus ratio and damping ratio test data of clay obtained from 406 groups of triaxial tests is constructed with the starting area of Xiong'an New Area as the research background. The aim is to study the nonlinear dynamic properties of clay in this area under cyclic loading. The study found that the effective confining pressure and plasticity index have certain influences on the dynamic shear modulus ratio and damping ratio of clay in this area. Through data analysis, it was found that there was a certain correlation between effective confining pressure and plasticity index and dynamic shear modulus ratio and damping ratio, with fitting degree values greater than 0.1263 for both. However, other physical indices such as the void ratio, natural density, water content and specific gravity have only a small effect on the dynamic shear modulus ratio and the damping ratio, with fitting degree values of less than 0.1 for all of them. This indicates that it is important to consider the influence of effective confining pressure and plasticity index when studying the nonlinear dynamic properties of clays in this area. Based on the above, prediction models for the dynamic shear modulus ratio and damping ratio in this area were constructed separately. The results showed that the model that considered the combined effect of effective confining pressure and plasticity index performed best. The predicted dynamic shear modulus ratio and damping ratio closely matched the actual curves, with approximately 88% of the data falling within ±1.3 times the measured dynamic shear modulus ratio and approximately 85.1% of the data falling within ±1.3 times the measured damping ratio. In contrast, the prediction models that considered only a single influence deviated from the actual values, particularly the model that considered only the plasticity index, which predicted the dynamic shear modulus ratio and the damping ratio within a small distribution range close to the average of the test values. When compared with existing prediction models, it was found that the predicted dynamic shear modulus ratio in this paper was slightly higher, which was due to the overall hardness of the clay in this area, leading to a slightly higher determination of the dynamic shear modulus ratio by the prediction model. Finally, for the dynamic shear modulus ratio and damping ratio of the engineering site in the starting area of Xiong'an New Area, we confirm that the prediction formulas established in this paper have high reliability and provide the applicable range of the prediction model.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.3
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• pp.76-88
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• 2024

A significant cause of fall or overturning accidents in the construction industry, including landscaping construction and management, is work at heights using portable ladders. Portable ladders are classified as A-type or triangular support ladders depending on the number of supporting leg and support conditions. The tripod mobile ladder, which supports itself with only three supporting legs, is unstable and more prone to overturning compared to the A type ladders. Therefore, using the specifications of the tripod mobile ladder and the stability regulations of EN131-Part 7, overturning and resistance moment calculation formulas were derived for all directions in which overturning could occur. The moments calculated using these equations, and the overturning stability in each direction were evaluated. According to the calculation results, although there are differences depending on the direction, most are unstable for overturning at 8 or more steps. Based on these results, this study proposed measures to increase the moment of resistance by changing the weight, depth, and width, and using outriggers to ensure stability against the overturning of ladder. However, when changing the specifications of these measures, the size increases are excessive and the applicability is insufficient. On the other hand, outriggers are an applicable measure as they can ensure stability against overturning with only a minimum expansion length.

• The Journal of Internal Korean Medicine
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• v.44 no.6
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• pp.1212-1242
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• 2023

Objectives: This study aims to explore the current usage status of orally administered Korean herbal medicine in randomized controlled trials (RCTs) published in the Journal of Korean Medicine and member journals using the CONSORT-Chinese Herbal Medicine Formulas 2017 (CONSORT-CHM 2017) checklist. Methods: We searched the OASIS, RISS, and KMBASE archives as well as the websites of the Journal of Korean Medicine and 45 member journals to identify RCTs that used herbal interventions. Two independent researchers searched and categorized the RCTs and performed a quantitative evaluation by journal, study design, and target disease, as well as qualitative evaluation of the literature using CONSORT-CHM 2017. Results: After the search, 66 articles were selected. The quantitative evaluation resulted in 13 articles (19.6%) that were published in the Journal of Korean Medicine and 12 articles (18.1%) in the Journal of Internal Korean Medicine. In terms of study design, 62 articles (93.9%) were parallel, 4 articles (6%) were crossover, and 2-arm parallel study designs were the most common in 45 articles (68.2%). In terms of the study participants, physiological characteristics and mechanisms in healthy individuals were the most common in 21 studies (31.8%) and obesity in 9 studies (13.6%). In terms of assessing completeness in the CONSORT-CHM 2017 items, 29 articles were rated high, 31 were rated moderate, and 6 were rated low. Items 4a, 6a, and 7a had low reporting rates (≤ 30%), while items 2a, 2b, and 12a were completely reported in all studies. Conclusion: Future RCTs using orally administered Korean herbal medicine need to be reported completely, and the CONSORT-CHM 2017 checklist can be a helpful tool for this purpose.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.32-38
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• 2024

In the case of apartment building, it is difficult to conduct non-destructive testing due to the actual presence of people and the dust and noise generated during the core test, so inspections are performed each time in the common area and underground parking lot, and the tests are conducted on the finishing material rather than on the concrete surface due to low-cost orders. As the process progresses, poor inspection is inevitable. In addition, the proposed formulas for strength estimation have large fluctuations depending on the differences in test conditions and environments, and even if they show the same measured value, the deviation between each proposed formula is large, making it difficult to accurately estimate strength, making it difficult to use. Accordingly, we would like to select finishing materials mainly used in apartment complexes and compare and evaluate the compressive strength of concrete according to the type of finishing material by using non-destructive testing methods directly on the finishing materials without removing the finishing materials. The reliability evaluation results of the estimated compressive strength of concrete using the ultrasonic velocity method according to the type of finishing material are as follows. The error rate between the estimated compressive strength and compressive strength derived through the ultrasonic velocity method shows a wide range of variation, ranging from 21.83% to 58.89%. The effect of the presence or absence of finishing materials on the estimated compressive strength was found to be insignificant. Accordingly, it is necessary to select more types of finishing materials and study ultrasonic velocity methods according to the presence or absence of finishing materials, and to study estimation techniques that can increase reliability.

• 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.