• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.5
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• pp.607-614
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• 2018

Oryeong-san is a prescription widely used for diseases where water is stagnant because it has the effect of circulating the water in the body and releasing it into the urine. In order to investigate the mechanisms of oryeong-san, we in this paper construct and analysis the compound-target network of medicinal materials constituting oryeong-san based on a systems pharmacology approach. First, the targets related to the 475 chemical compounds of oryeong-san were searched in the STITCH database, and the search results for the interactions between compounds and targets were downloaded as XML files. The compound-target network of oryeong-san is visualized and explored using Gephi 0.8.2, which is an open-source software for graphs and networks. In the network, nodes are compounds and targets, and edges are interactions between the nodes. The edge is weighted according to the reliability of the interaction. In order to analysis the compound-target network, it is clustered using MCL algorithm, which is able to cluster the weighted network. A total of 130 clusters were created, and the number of nodes in the cluster with the largest number of nodes was 32. In the clustered network, it was revealed that the active compounds of medicinal materials were associated with the targets for regulating the blood pressure in the kidney. In the future, we will clarify the mechanisms of oryeong-san by linking the information on disease databases and the network of this research.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.459-471
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• 2023

This study identified the characteristics of changes in forest areas of North Korea's major regions (Gaesong, Goseong, Pyongyang, and Hyesan·Samsu) using data on degraded lands collected via monitoring by the National Institute of Forest Science. The data, spanning 1999 to 2018, were cross-analyzed to determine trends in land cover change, and hotspot analysis was conducted to confirm evident changes in the forest areas. The results showed that the areas of interest substantially transitioned to other land use types from 1999 to 2008. Contrastingly, the range of changes decreased from 2008 to 2018, with some areas regenerating into forests. Nevertheless, the hotspot analysis indicated that hotspots occurred more intensively in the outskirts of cities and forest edges from 2008 to 2018 than from 1999 to 2008. The analysis also showed that the aforementioned changes were caused by various aspects, depending on regional characteristics and social factors. This study can be used as a basic reference for decision-making on the selection of basic forest restoration targets and restoration methods in inter-Korean forest cooperation initiatives.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.394-399
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• 2024

An irradiator is developed using two UVA wavelength ranges of SMD LEDs as a curing light source. This module has dimensions of 545×111×300 mm³ and is equipped with a TIR bar-shaped lens made of PDMS silicone resin. The developed irradiator offers high uniformity, with 89% in the centerline of the horizontal axis direction, for two different wavelength ranges of 365 nm and 385 nm. The radiation intensity from the light source module shows highly directional characteristics, and the irradiator provides a maximum irradiance of 1,634 mW/cm² at a working distance of 50 mm. During the initial 5 minutes of operation, the irradiance experiences a rapid decrease. However, this issue is addressed by optimizing the LED's current reduction characteristics and managing the Transistor's temperature rise in the constant current circuit. After continuous operation for approximately 60 minutes. The highest temperature, near the central part of the irradiating surface, reaches 69.7℃, while the lowest temperature, near the edges, is 41.1℃.

• Korean Journal of Materials Research
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• v.34 no.4
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• pp.185-193
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• 2024

In this study, NASICON-type Li_1+XGa_XTi_2-X(PO₄)₃ (x = 0.1, 0.3 and 0.4) solid-state electrolytes for all-solid-state batteries were synthesized through the sol-gel method. In addition, the influence on the ion conductivity of solid-state electrolytes when partially substituted for Ti⁴⁺ (0.61Å) site to Ga³⁺ (0.62Å) of trivalent cations was investigated. The obtained precursor was heat treated at 450 ℃, and a single crystalline phase of Li_1+XGa_XTi_2-X(PO₄)₃ systems was obtained at a calcination temperature above 650 ℃. Additionally, the calcinated powders were pelletized and sintered at temperatures from 800 ℃ to 1,000 ℃ at 100 ℃ intervals. The synthesized powder and sintered bodies of Li_1+XGa_XTi_2-X(PO₄)₃ were characterized using TG-DTA, XRD, XPS and FE-SEM. The ionic conduction properties as solid-state electrolytes were investigated by AC impedance. As a result, Li_1+XGa_XTi_2-X(PO₄)₃ was successfully produced in all cases. However, a GaPO₄ impurity was formed due to the high sintering temperatures and high Ga content. The crystallinity of Li_1+XGa_XTi_2-X(PO₄)₃ increased with the sintering temperature as evidenced by FE-SEM observations, which demonstrated that the edges of the larger cube-shaped grains become sharper with increases in the sintering temperature. In samples with high sintering temperatures at 1,000 ℃ and high Ga content above 0.3, coarsening of grains occurred. This resulted in the formation of many grain boundaries, leading to low sinterability. These two factors, the impurity and grain boundary, have an enormous impact on the properties of Li_1+XGa_XTi_2-X(PO₄)₃. The Li_1.3Ga_0.3Ti_1.7(PO₄)₃ pellet sintered at 900 ℃ was denser than those sintered at other conditions, showing the highest total ion conductivity of 7.66 × 10^-5 S/cm at room temperature. The total activation energy of Li-ion transport for the Li_1.3Ga_0.3Ti_1.7(PO₄)₃ solid-state electrolyte was estimated to be as low as 0.36 eV. Although the Li_1+XGa_XTi_2-X(PO₄)₃ sintered at 1,000 ℃ had a relatively high apparent density, it had less total ionic conductivity due to an increase in the grain-boundary resistance with coarse grains.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.29-40
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• 2024

This study aimed to evaluate the swelling behavior characteristics of KJ-II buffer blocks by performing numerical analysis of swelling pressure measurement experiments using the nonlinear elasticity model of COMSOL Multiphysics. The analysis was conducted under boundary conditions that included isotropic constraints and water injection pressure, mirroring the experimental settings. Validation of the numerical model was achieved by comparing its outputs with experimental results. The validated model was then used to simulate swelling deformations under unconfined conditions and to analyze swelling pressure as influenced by dry density and the geometric shape of the buffer material. The results accurately represented the swelling deformation observed during the saturation process and demonstrated that swelling pressure increases with higher dry density. Moreover, simulations concerning the geometric shape of the buffer material indicated a markedly faster rate of pressure increase in U-shaped samples compared to cylindrical ones. Analysis suggested that stress manifested preemptively near the internal edges of U-shaped samples during saturation. To enhance the simulation's fidelity to actual buffer material behavior, further refinement of the analysis model using a nonlinear elasticity model is recommended.

• Advances in aircraft and spacecraft science
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• v.11 no.1
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• pp.83-103
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• 2024

Adhesive bonding is currently widely used in many industrial fields, particularly in the aeronautics sector. Despite its advantages over mechanical joints such as riveting and welding, adhesive bonding is mostly used for secondary structures due to its low peel strength; especially if it is simultaneously exposed to temperature and humidity; and often presence of bonding defects. In fact, during joint preparation, several types of defects can be introduced into the adhesive layer such as air bubbles, cavities, or cracks, which induce stress concentrations potentially leading to premature failure. Indeed, the presence of defects in the adhesive joint has a significant effect on adhesive stresses, which emphasizes the need for a good surface treatment. The research in this field is aimed at minimizing the stresses in the adhesive joint at its free edges by geometric modifications of the ovelapping part and/or by changing the nature of the substrates. In this study, the finite element method is used to describe the mechanical behavior of bonded joints. Thus, a three-dimensional model is made to analyze the effect of defects in the adhesive joint at areas of high stress concentrations. The analysis consists of estimating the different stresses in an adhesive joint between two 2024-T3 aluminum plates. Two types of single lap joints(SLJ) were analyzed: a standard SLJ and another modified by removing 0.2 mm of material from the thickness of one plate along the overlap length, taking into account several factors such as the applied load, shape, size and position of the defect. The obtained results clearly show that the presence of a bonding defect significantly affects stresses in the adhesive joint, which become important if the joint is subjected to a higher applied load. On the other hand, the geometric modification made to the plate considerably reduces the various stresses in the adhesive joint even in the presence of a bonding defect.

• Geophysics and Geophysical Exploration
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• v.27 no.1
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• pp.23-36
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• 2024

In this study, we analyze the structure of the Korea-Japan Joint Development Zone (JDZ) using gravity, magnetic, and seismic data. Gravity and magnetic data analysis confirmed that the Jeju Basin exhibits low anomalies compared to adjacent areas. We applied the total gradient to the Bouguer anomaly to identify basin boundaries, and computed the analytic signal from the total magnetic anomaly data to enhance the edges of the magnetic anomalies. The Taiwan-Sinzi Belt, exhibits high magnetic anomalies and crosses the center of the JDZ in the northeast-southwest direction; we presume that intrusive rocks are sporadic in the JDZ. The 3D inversion results of the gravity and magnetic data show a strong correlation between magnetic susceptibility and density (i.e. a low-density zone in the Jeju Basin and the Ho Basin, and a high magnetic susceptibility distribution in the Taiwan-Sinzi Belt). Comparison of the density and seismic profiles of the Jeju Basin shows that high densities are associated with sill, horst, and basement highs, whereas low densities are associated with basement low and grabens. These results suggest that interpretations based on seismic, gravity and magnetic data can effectively reveal the subsurface structure of the JDZ.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.51-65
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• 2024

Phyto-sociological methods were used in this study to assess the vegetation structure of a forest stand at Mt. Goehwa in Sejong-Si with the aim of providing vegetation information for urban forest utilization and management plans. The actual forest vegetation was classified into two types of community groups (Quercus serrata-Lindera obtusiloba and Coreopsis lanceolata community groups) at the highest hierarchical level. The Q. serrata-L. obtusiloba community group was classified into six units, which included artificial forest and natural forest vegetation. Artificial forests were classified into three communities (Pinus rigida, Castanea crenata, and Robinia pseudoacacia), whereas natural forests were classified into three communities (Quercus variabilis, Quercus acutissimaa, and Pinus densiflora). The Coreopsis lanceolata community group, which exhibited vegetative characteristics of urban forest edge areas, was categorized into four units. The urban forest edges were classified into four communities (Indigofera bungeana, Lespedeza bicolor, Amorpha fruticosa, and Lespedeza cuneata). Accordingly, the vegetation structure of Mt. Goehwa was categorized into 10 vegetation unit systems. An importance value analysis showed the highest importance value for C. crenata at 6.7%, followed by P. rigida at 6.4%, and R. pseudoacacia at 6.3%, indicating that the ecological impact of plantation species can be significant on Mt. Goehwa. A community coefficient of similarity analysis revealed that the artificial and natural forests had similar species compositions; however, both forests differed from the urban forest edge. This variation was further confirmed by Detrended correspondence analysis(DCA), with similar results. Canonical correspondence analysis(CCA) showed that the artificial forest and natural forest community types were positively correlated with altitude, bare rock, and the present species. By contrast, the urban forest edge community types were negatively correlated with these factors.