• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.735-743
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• 2010

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

• The Journal of Engineering Geology
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• v.25 no.4
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• pp.577-585
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• 2015

Contamination of soil due to an oil spill influences its subsequent behavior. An investigation was conducted to study the effect of oil viscosity on compaction characteristics, coefficient of permeability, and shear strength. Water permeability was also determined by using Kerosene, Engine oil, and Crude-oil as contaminants. The test results indicate that the compaction characteristics are influenced by oil contamination. Direct shear test was conducted to investigate the effect of oil in the pore space in sandy ground. angle of internal friction of sand (based on total stress condition) decreases due to presence of oil within the pore spaces in sand.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.197-211
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• 2024

This research studies the effect of geotechnical factors on EPB-TBM performance parameters. The modeling was performed using simple and multivariate linear regression methods, artificial neural networks (ANNs), and Sugeno fuzzy logic (SFL) algorithm. In ANN, 80% of the data were randomly allocated to training and 20% to network testing. Meanwhile, in the SFL algorithm, 75% of the data were used for training and 25% for testing. The coefficient of determination (R²) obtained between the observed and estimated values in this model for the thrust force and cutterhead torque was 0.19 and 0.52, respectively. The results showed that the SFL outperformed the other models in predicting the target parameters. In this method, the R² obtained between observed and predicted values for thrust force and cutterhead torque is 0.73 and 0.63, respectively. The sensitivity analysis results show that the internal friction angle (φ) and standard penetration number (SPT) have the greatest impact on thrust force. Also, earth pressure and overburden thickness have the highest effect on cutterhead torque.

• Korean Journal of Agricultural Science
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• v.45 no.1
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• pp.120-127
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• 2018

The rural labor force has gradually been decreasing due to the decrement of the farm population and the increment of the aging population. To solve these problems, it is necessary to develop and study autonomous agricultural machinery. Therefore, analyzing the dynamic behavior of vehicles in an autonomous agricultural environment is important. Until now, most studies on agricultural machinery, especially on ground vehicle dynamics, have been done by field tests. However, these field test methods are time consuming and costly with seasonal restrictions. A research method that can replace existing field test methods by using simulations is needed. In this study, we did basic research analyzing the effect of the travelling speed of a tractor on tire slip using simulation software. A tractor simulation model was developed based on field conditions following a straight path. The simulation was done for three ranges of speed: 20 - 30 km/h (considered the normal travelling speed range), 6 - 8 km/h (considered the plow tillage speed range) and 2 - 4 km/h (considered the rotary tillage speed range). The results of the simulation show that the slip ratio and slip angle values tended to increase as the traveling speed range of the tractor decreased. From the simulation results, it can be concluded that at low tractor speeds, it becomes more difficult to control the vehicle path. In future research, simulations will be done with various work environments such as a curved path as well as with various friction coefficient conditions, and the simulation results will be experimentally verified by applying them to an agricultural tractor.

• Journal of Biosystems Engineering
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• v.30 no.4 s.111
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• pp.220-228
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• 2005

This study was conducted to investigate the main factors that contain a rotating velocity ratio between wheel and conveyor belt, a tilt angle of conveyor belt and a rotating velocity of a dick cutter for mechanization of Chinese leek harvest. In the survey on the cultivation of Chinese leek, row spacing of 350 m and cutting height of 10 mm from the ground were set up for field tests. Test equipment was designed to cut, pick up and convey Chinese leek one row by one row. From the results of material tests, pick-up height of conveyor belt was set up at $60\~90m$ from the bottom, and the strain and stress at rupture of Chinese leek was 0.487 m/m and 0.01078 MPa. An elastic coefficient of the rubber (Neoprene) of conveyor belts was 1.1077 under the strain of 0.3 nym. from the results of field tests, the tilt angle of conveyor belt was the range of $25^{\circ}\~30^{\circ}$ under consideration far space of container, the velocity ratio between vehicle and conveying belt was 1 to 2.4~1.7 at 0.1~0.3 m/s of vehicle, and optimum rotating velocity of the disk cutter was 34.8 m/s or more under consideration for soil friction.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.1-13
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• 2019

The purpose of this study is to examine the effect of soft ground improvement by dynamic replacement with utilizing crushed rock. In order to understand the ground improvement effect when applying dynamic replacement method with crushed rock, the laboratory test and field test were performed. The internal friction angle and apparent cohesion were derived through direct shear test. The dynamic replacement characteristics were identified by analyzing the weight, drop, and number of blows needed for dynamic replacement. Through the field plate bearing test and density test, the bearing capacity and settlement of the improved ground were measured, and the numerical analysis were conducted to analyze the behavior of the improved ground. In this study, it proposes modified soil experimental coefficient(C_DR) to 0.3~0.5 in the dynamic replacement method with crushed rock. Also when applying the dynamic replacement method using crushed rock, the particle size range is less than 100 mm, D₉₀ is less than 80 mm and D₁₅ is more than 30 mm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.626-633
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• 2020

This study examined the behavior of the ground by comparing the methods using the results of the Terzaghi formula and the ground investigation data and method considering the dilatancy effect for a circular tunnel using the finite element method. In the case of the Terzaghi formula, the tunnel load can be overestimated and cause overdesign. The method using the results of the ground investigation data cannot be applied when a reasonable coefficient of earth pressure is not determined. This is because it behaves completely differently from the actual behavior, and unexpected problems can occur. In the case of the method considering the dilatancy effect, however, both the strength enhancement effect can be considered through the dilatancy angle and relative density. Therefore, the tunnel load was calculated most reasonably using the method considering dilatancy. Finite element analysis using the geotechnical survey results showed that the tensile stress acts at the top of the tunnel when the upper soil of the tunnel is shallow. On the other hand, additional verification is necessary, such as a comparison with the field measurement results. Through additional research, if normalized, the tunnel load can be calculated reasonably at the time of tunnel design, and safe and economical design is possible.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.59-66
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• 2018

The utilized coefficient of friction (UCOF) as a ratio of the shear force to the normal force on the ground during walking is used to identify the point at which slip is likely to occur. Shoe walking will change the utilized coefficient of friction by shoe design such as sole thickness and hardness, heel shape, and outsole pattern. In this study, subjects are 21 adults (10 female, 11 male, age: $25.2{\pm}2.3yrs$, height: $165.6{\pm}7.2cm$), analysis variables were walking speed, GRF, when the UCOF is maximal, and Tangent of CoP-CoM angle, and correlation analysis with the utilized friction coefficient (UCOF). As a result, First, for the shod walking the time point which UCOF is maximum about heel strike was faster and the magnitude was larger than for barefoot walking. Second, the correlation between the tangent of CoP-CoM and UCOF of right foot was higher at the left heel striking point (UCOF2_h) which occurred in the post propulsion phase than at the right heel striking point (UCOF1_h). This suggests that the right foot UCOF is related to the braking phase of left foot( which is the propulsion phase of right foot) rather than the braking phase of right foot.