• Journal of Adhesion and Interface
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• v.7 no.2
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• pp.1-11
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• 2006

Interfacial evaluation of the untreated and treated Jute and Hemp fibers reinforced different matrix polypropylene-maleic anhydride polypropylene copolymer (PP-MAPP) composites were investigated by micromechanical technique and dynamic contact angle measurement. For the statistical tensile strength of Jute and Hemp fibers, bimodal Weibull distribution was fitted better than the unimodal distribution. The acid-base parameter on the interfacial shear strength (IFSS) of the natural fiber composites was characterized by calculating the work adhesion, $W_a$. The effect of alkaline, silane coupling agent on natural fibers were obtained with changing MAPP content in PP-MAPP matrices. Alkaline treated fibers made the surface energy to be higher due to removing the weak boundary layers and thus increasing surface area, whereas surface energy of silane treated Jute and Hemp fibers decreased due to blocked high energy sites. MAPP in the PP-MAPP matrix caused the surface energy to increase due to introduced acid-base sites. Microfailure modes of two natural fiber composites were observed clearly differently due to different tensile strength of natural fibers.

• Magazine of the Korea Concrete Institute
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• v.8 no.5
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• pp.111-122
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• 1996

The effects of external restraint on the thermal stresses i n mass concrete are investigated through a series of parametric study. Two major factors affecting the degree of external restraint such as the ratio of length to height of the placed structure (L/H) and the elastic modulus of base structure ($E_r$) are employed as the parameters in a condition which a placing height H is 1.0m. Various conditions of I,/H and E, are analysed by a FEM program and the relationship between these two parameters is examined. The shape of stress distribution due to the external restraint is shown as linearity on the height direction of the section, and is influenced by L/H, $E_r$, and strength development of placed concrete. The external restraint can be devided by two part. One is an axial restraint and the other is a flexural restraint. When the level of external restraint is low, the structure behavior is mainly governed by flexural restraint, otherwise it is dependent on axial restraint. Comparing the calculated stress by the method of the ACI 207 committee with a finite element analysis, the fbrmer overestimates the external restraint stress when the degree of external restraint is weak, and underestimates when it is strong.

• Asian Spine Journal
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• v.12 no.6
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• pp.1085-1091
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• 2018

Study Design: Case-control. Purpose: To determine optimal cut-off value for body mass index (BMI) in predicting surgical success in patients with lumbar spinal canal stenosis (LSCS). Overview of Literature: BMI is an essential variable in the assessment of patients with LSCS. Methods: We conducted a prospective study with obese and non-obese LSCS surgical patients and analyzed data on age, sex, duration of symptoms, walking distance, morphologic grade of stenosis, BMI, postoperative complications, and functional disability. Obesity was defined as BMI of ${\geq}30kg/m^2$. Patients completed the Oswestry Disability Index (ODI) questionnaire before surgery and 2 years after surgery. Surgical success was defined as ${\geq}30%$ improvement from the baseline ODI score. Receiver operating characteristic (ROC) analysis was used to estimate the optimal cut-off values of BMI to predict surgical success. In addition, correlation was assessed between BMI and stenosis grade based on morphology as defined by Schizas and colleague in total, 189 patients were eligible to enter the study. Results: Mean age of patients was $61.5{\pm}9.6years$. Mean follow-up was $36{\pm}12months$. Most patients (88.4%) were classified with grades C (severe stenosis) and D (extreme stenosis). Post-surgical success was 85.7% at the 2-year follow-up. A weak correlation was observed between morphologic grade of stenosis and BMI. Rates of postoperative complications were similar between patients who were obese and those who were non-obese. Both cohorts had similar degree of improvement in the ODI at the 2-year followup. However, patients who were non-obese presented significantly higher surgical success than those who were obese. In ROC curve analysis, a cut-off value of ${\leq}29.1kg/m^2$ for BMI in patients with LSCS was suggestive of surgical success, with 81.1% sensitivity and 82.2% specificity (area under the curve, 0.857; 95% confidence interval, 0.788-0.927). Conclusion: This study showed that the BMI can be considered a parameter for predicting surgical success in patients with LSCS and can be useful in clinical practice.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korean Geotechnical Society
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• v.24 no.11
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• pp.111-120
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• 2008

The characteristic of induced anisotropy is investigated in this study for the Pohang mudstone involving the cut plane discontinuity. The uniaxial and triaxial compression tests are performed for anisotropic rocks with artificial joint to look into anisotropic strength characteristics. Both the uniaxial compressive strength and triaxial compressive strength show the lowest value at the angle of cut plane, ${\beta}=30^{\circ}$ and the shoulder type of anisotropy is obtained. Anisotropy ratio (Rc) in uniaxial compression measures 9.0, whereas Rc=1.29-1.98 in triaxial compression is appeared. A series of analyses are made with the test results to derive the suitable parameter values when it is applied to the Ramamurthy (1985) failure criterion. The result of uniaxial compression test is analyzed by introducing the n-index into Ramamurthy failure criterion. The result shows that, n=l is suitable for ${\beta}=0^{\circ}{\sim}30^{\circ}$ and n=3 is suitable for ${\beta}=30^{\circ}{\sim}90^{\circ}$. To analyze the result of triaxial compression test by Ramamurthy failure criterion, anisotropy ratio in uniaxial compression test is added to Ramamurthy's equation and material constants are estimated by modified Ramamurthy's equation. When these values are applied back to Ramamurthy failure criterion, the predicted values are well fitted to the test results. And strength anisotropy for failure criteria of Jaeger (1960), McLamore & Gray (1967) and Hoek & Brown (1980) are also investigated.

• Korean Journal of Optics and Photonics
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• v.34 no.3
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• pp.99-105
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• 2023

The performance of astronomical telescopes can be negatively affected by atmospheric turbulence. To address this issue, techniques for atmospheric turbulence correction have been developed, requiring the simulation of atmospheric turbulence in the laboratory. The most practical way to simulate atmospheric turbulence is to use a phase plate. When measuring a phase plate that simulates strong turbulence, a Shack-Hartmann wave-front sensor is commonly used. However, the laser power decreases as it passes through the phase plate, potentially leading to a weak laser signal at the sensor. This paper investigates the need to control the laser power when measuring a phase plate that simulates strong atmospheric turbulence, and examines the effects of the laser power on the measured wavefront. For phase plates with relatively high Fried parameter r₀, the laser power causes a variation of over 10% in r₀. For phase plates with relatively low r₀, the laser power causes a variation of less than 5%, which means that the influence of the laser power is negligible for phase plates that simulate strong atmospheric turbulence. Based on the system described in this paper, a phase plate simulating strong atmospheric turbulence can be measured at a laser power of 5 mW or higher. Therefore, controlling the laser's output power is necessary when measuring a phase plate for simulating atmospheric turbulence, especially for phase plates with low r₀ values.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.643-651
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• 2008

In the present paper, turbulent open-channel flows over longitudinal bedforms are numerically simulated. The Reynolds- averaged Navier-Stokes equations in curvilinear coordinates are solved with the non-linear $k-{\varepsilon}$ model by Speziale( 1987). First, the developed model is applied to rectangular open channel flows for purposes of model validation and parameter sensitivity studies. It is found that the parameters $C_D$ and $C_E$ are important to the intensity of secondary currents and the level of turbulent anisotropy, respectively. It is found that the non-linear $k-{\varepsilon}$ model can hardly reproduce the turbulence anisotropy near the free surface. However, the overall pattern of the secondary currents by the present model is seen to coincide with measured data. Then, numerical simulations of turbulent flows over longitudinal bedforms are performed, and the simulated results are compared with the experimental data in the literature. The simulated secondary currents clearly show upflows and downflows over the ridges and troughs, respectively. The numerical results of secondary currents, streamwise mean velocity, and turbulence structures compare favorably with the measured data. However, it is observed that the secondary currents towards the troughs were significantly weak compared with the measured data.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.29-43
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• 2019

This paper empirically analyzed the relationship between the characteristics of venture business founders and management performance, setting the management strategy as a parameter to provide a suggestion for the survival and development of venture companies that play an important role in the national economy and job creation. Previous studies in Korea have analyzed the relationship between the characteristics of business founders, management strategies and management performance in a single dimension. This paper, however, explained the business performance of a company from a multi-dimensional perspective while setting the characteristics of business founders as independent variables and setting the business strategy of the enterprise as a parameter. The first result of the analysis shows that the characteristics of venture business founders have a positive effect on business performance. In particular, among the characteristics of venture business founders, a progressive spirit has had the greatest impact on business performance. On the other hand, the influence of risk sensitivity was very weak. Second, the characteristics of venture business founders were found to have a positive effect on business strategy. In particular, innovation was an important variable that affected the technological innovation differentiation strategy, and a progressive spirit was the most influential factor in the marketing differentiation strategy. Third, management strategies of venture firms were found to have a positive effect on business performance. In particular, the technology innovation differentiation strategy has a greater impact on business performance than the marketing differentiation strategy. Fourth, it was revealed that management strategy partially has a mediated effect on the relationship between the characteristics of venture business founders and management performance. In other words, it was found that the characteristics of the founders have a direct impact on business performance but if it is linked to management strategy it has an indirect effect on business performance. The results of this study show that business performance improves when venture business founders' personal characteristics and the firms' management strategy are combined.