• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.111-118
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• 2016

This paper presents an X-band (9.375 GHz) $1{\times}2$ array microstrip antenna which is capable of active beam compensation for installation of an unmanned aerial vehicle (UAV). First of all, a basic $1{\times}2$ array microstrip antenna incorporated with wilkinson power divider was designed and performance of the array antenna was verified. Next, to verify beam steering performance of the designed array microstrip antenna, we fabricated a phase shifter, and the wilkinson power divider as module structure and measured characteristics of beam steering according to phase shifting. The main lobe is 0.6 dBi at $0^{\circ}$, and the side lobe decreased 18.8 dB. The reliable radiation pattern was achieved. Finally, an active beam steering microstrip array antenna attached with the phase shifter and the power divider on the back side of the antenna was designed and fabricated to install wing of UAV for compactness. The maximum gain is 0.1 dBi. Therefore, we obtained a basic antenna technology for compensating beam error according to wing deformation of an UAV installed array antennas.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.95-106
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• 2005

Road accidents are considered as the result of a complex interplay between road, vehicle, environments, and human factors. Little study, however, has been carried out on the attributes of human factor compared to the road geometric conditions and traffic conditions. The previous researches focused on mainly both traffic and geometric conditions on specific location. Therefore, it's hard to explain phenomenon of the high traffic accident rates where road and traffic conditions are good. Because of these reasons, accident analysis has contributed on geometric improvement and has not contributed on traffic management such as selection of attention section, driver napping alert, etc. The freeway incident management is also associated with reliable prediction of incident occurrences on freeway sections. This paper presents a method for estimating the effect of trip length on freeway accident rate. A PAR (Potential Accident Ratio), the new concept of accident analysis, considering TLFDs (Trip Length Frequency Distributions) is suggested in this paper. This approach can help to strengthen freeway management and to reduce the likelihood of accidents.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.819-829
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• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.657-665
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• 2019

The domestic railway parts and equipment manufacturing industry is mainly focused on SMEs, and the majority of them are suffering from profitability because they cannot build economies of scale. Besides, they have survived in the form of importing technology products from overseas advanced countries and delivering them to domestic railway operators rather than having in-house technology. Therefore it is necessary to study whether the problems of the current railway industry can be identified and improved and at the same time, whether the government's railway industry development policy is properly reflected. literature studies related to technology commercialization, and conduct surveys of AHP questionnaires on the experts of the manufacturing industry of SMEs, academics / research institutes of the railway industry. After that, the Level 3 activation method AHP analysis was additionally performed on the important factors of Level 2 that have the highest importance and priority in Level 1. As a result of the AHP analysis, 'Technical Connectivity' was the most important method in the technical factor, and SME experts and academic and research institute experts were highly evaluated for 'commercialization ability' Competence in terms of importance. As for external support factors, it was analyzed that SME experts "support for manpower development" was important, while the other two group experts research and development support was important. In this study, the priority of the government support and policy priorities are suggested according to the capabilities of the railway manufacturing SMEs before the future R&D support.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Nutrition Research and Practice
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• v.15 no.6
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• pp.673-685
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• 2021

BACKGROUND/OBJECTIVES: Obesity is associated with the impaired regulation of T cells characterized by increased numbers of Th1 and Th17 cells and the dysregulation of vitamin D metabolism. Both obesity and vitamin D have been reported to affect autophagy; however, a limited number of studies have investigated the effects of vitamin D on T cell autophagy in obese mice. Therefore, we aimed to determine whether in vitro treatment with vitamin D affects the proliferation, function, and autophagy of T cells from obese and control mice. MATERIALS/METHODS: Five-week-old male C57BL/6 mice were fed control or high-fat diets (10% or 45% kcal fat: CON or HFDs, respectively) for 12 weeks. Purified T cells were stimulated with anti-CD3 and anti-CD28 monoclonal antibodies and cultured with either 10 nM 1,25(OH)₂D₃ or 0.1% ethanol (vehicle control). The proliferative response; expression of CD25, Foxp3, RORγt, and autophagy-related proteins (LC3A/B, SQSTM1/P62, BECLIN-1, ATG12); and the production of interferon (IFN)-γ, interleukin (IL)-4, IL-17A, and IL-10 by T cells were measured. RESULTS: Compared with the CON group, T cell proliferation tended to be lower, and the production of IFN-γ was higher in the HFD group. IL-17A production was reduced by 1,25(OH)2D₃ treatment in both groups. The LC3 II/I ratio was higher in the HFD group than the CON group, but P62 did not differ. We observed no effect of vitamin D treatment on T cell autophagy. CONCLUSIONS: Our findings suggest that diet-induced obesity may impair the function and inhibit autophagy of T cells, possibly leading to the dysregulation of T cell homeostasis, which may be behind the aggravation of inflammation commonly observed in obesity.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.439-449
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• 2021

The recent reduction in greenhouse gases, interest in environmental pollution such as low-carbon emission policies is increasing. Accordingly, the penetration rate of eco-friendly vehicles, including hydrogen battery vehicles capable of reducing carbon emission, is increasing, and thus it is required for disaster prevention and safety-related measures. In this study, the degree of risk for the concentration distribution of hydrogen when leaking hydrogen fuel vehicles according to ventilation conditions was analyzed through numerical analysis, limited to places in parking lots. As a result, when only one hydrogen tank was released, the combustible volume ratio of hydrogen in the underground parking lot was up to 8.6%, and as ventilation continued, the volume ratio of combustible hydrogen decreased to less than 1% after 150 seconds, indicating that mechanical ventilation is essential. In the case of simultaneous release or stage release of three hydrogen tanks, the final combustible volume ratio of hydrogen is similar, but the increase in the combustible volume ratio of hydrogen in the early stage of release is low, and further research is expected.

• Journal of Korean Philosophical Society
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• no.114
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• pp.305-335
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• 2016

In the eighteenth century, the scottish philosophers Francis Hutcheson, David Hume and Adam Smith share the idea that morality comes from moral sense, which is a feeling of approval or disapproval of agent's motive and action. However, they have the different views in explaining the mechanism that generates the moral sentiments. Hutcheson takes a moral sense to be a unique mental faculty that is innate to all humans, and regards it as being guaranteed by supernatural apparatus like divine Providence. Hume and Smith reject Hutcheson's concept of internal moral sense and take a stage further Hutcheson's projects of internalisation by naturalizing morality in terms of the principle of sympathy. It is widely held that Hume's moral sentimentalism is essentially similar to Adam Smith's. Though there are important points of contact between Smith's account of sympathy and Hume's, the differences are considerable. The chief of them lies in the fact that Hume grounds our approval of virtue on our recognition of its utility and convention, and Smith does not. Smith grounds our approval of virtue on the impartial spectator's judgment, i.e., conscience. Hence for Smith, the impartial spectator is the one that bridges the gap between particularity and universality and works the vehicle of practical reason. Given this, in this paper, first, I will clarify the difference between Hume's and Adam Smith's understandings of sympathy. Second, I will elucidate how they explain the process to produce the moral sentiments based on their understandings of sympathy. I shall finally explicate in what way Hume's and Smith's theories on sympathy work as moral normativity.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.941-951
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• 2018

Utilization and demand of UAV (unmanned aerial vehicle) for the generation of 3D city model are increasing. In this study, we performed an experiment to adjustment position/orientation of UAV with incomplete attitude information and to extract point cloud data. In order to correct the attitude of the UAV, the rotation angle was calculated by using the continuous position information of UAV movements. Based on this, the corrected position/orientation information was obtained by applying IBA (Incremental Bundle Adjustment) based on photogrammetry. Each pair was transformed into an epipolar image, and the MDR (Multi-Dimensional Relaxation) technique was applied to obtain high precision DSM. Each extracted pair is aggregated and output in the form of a single point cloud or DSM. Using the DJI inspire1 and Phantom4 images, we can confirm that the point cloud can be extracted which expresses the railing of the building clearly. In the future, research will be conducted on improving the matching performance and establishing sensor models of oblique images. After that, we will continue the image processing technology for the generation of the 3D city model through the study of the extraction of 3D cloud It should be developed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.