• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.336-341
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• 2018

In this paper, we designed and implemented an ultra wideband (UWB) antenna with 5G mobile communication and WLAN bands rejection characteristics. The proposed antenna consists of a planar radiation patch with two slots, parasitic elements on both sides of the strip line and ground plane on back side. The upper n-type slot contributes for 5G mobile communication band (3.42~3.70 GHz) rejection and the lower n-type slot contributes for wireless local area network (WLAN) band (5.15~5.825 GHz) rejection. Parasitic elements were used in order to satisfy the voltage standing wave ratio (VSWR) less than or equal to 2.0 for UWB band (3.10~10.60 GHz) except two rejection bands. The Ansoft's high frequency structure simulator (HFSS) was used for antenna design and simulations. The simulated antenna showed dual rejection bands of 3.36~3.71 GHz and 5.13 ~ 5.92 GHz in UWB band, and measured result for the implemented antenna showed dual rejection bands of 3.40~3.72 GHz and 5.08~5.858 GHz. Simulated and measured VSWRs are less than or equal to 2.0 for all UWB band except dual rejection bands.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.90-104
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• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1013-1027
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• 2021

Images taken with KOMPSAT-3 have additional NIR and PAN bands, as well as RGB regions of the visible ray band, compared to imagestaken with a standard camera. Furthermore, electrical and optical properties must be considered because a wide radius area of approximately 17 km or more is photographed at an altitude of 685 km above the ground. In other words, the camera sensor of KOMPSAT-3 is distorted by each CCD pixel, characteristics of each band,sensitivity and time-dependent change, CCD geometry. In order to solve the distortion, correction of the sensors is essential. In this paper, we propose a method for detecting uniform regions in side-slider-based KOMPSAT-3 images using segment-based noise analysis. After detecting a uniform area with the corresponding algorithm, a correction table was created for each sensor to apply the non-uniformity correction algorithm, and satellite image correction was performed using the created correction table. As a result, the proposed method reduced the distortion of the satellite image,such as vertical noise, compared to the conventional method. The relative radiation accuracy index, which is an index based on mean square error (RA) and an index based on absolute error (RE), wasfound to have a comparative advantage of 0.3 percent and 0.15 percent, respectively, over the conventional method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.121-132
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• 2021

Green facade has a significant impact on building's energy performance by controlling the absorption of solar radiation and improving outdoor thermal comfort through shading and evapotranspiration. In particular, since high-density building does not enough green space, green facade, and rooftop greening using artificial ground plants are highly utilized. However, the level of cooling effect according to plant traits and irrigation control is different. Therefore, in this study, the cooling effect analyzed for a total of 4 cases by controlling the irrigation condition based on hedera and spurge. Although hedera under sufficient water had the highest cooling effect(-2℃~-4℃), had the lowest cooling effect under non-irrigation(+1.1℃~+4.4℃). In addition, hedera under sufficient water had cooling effect than hedera under non-irrigation(-1℃~-8.1℃) and in the case of spurge, it had cooling effect(-0.3℃~-7.8℃) more than non-irrigation. As a result of measuring the amount of transpiration according to the light intensity (PAR) and carbon dioxide concentration conditions, transpiration of hedera was higher than the spurge (respectively 0.63204mmolm^-2s^-1, 0.674367mmolm^-2s^-1). The difference in the cooling effect of the green facade under irrigation condition was significant. But the potential cooling effect of green facade according to plants species was different. Therefore, in order to maximize and continuously provide the cooling effect of green facade in urban areas, it is necessary to consider the characteristics of plants and the control of water supply through the irrigation system.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.345-354
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• 2024

In this paper, we propose a triple band WLAN antenna for Wi-Fi 6E band with DGS. The proposed antenna has the characteristics required frequency band and bandwidth by considering the interconnection of two strip lines and three areas on the ground place. The total substrate size is 31 mm (W) × 50 mm (L), thickness (h) 1.6 mm, and the dielectric constant is 4.4, which is made of 22 mm (W₆ + W₄ + W₅) × 43mm (L₁ + L₂ + L₃ + L₅) antenna size on the FR-4 substrate. From the fabrication and measurement results, bandwidths of 340 MHz (1.465 to 1.805 GHz) for 900 MHz band, 480 MHz (2.155 to 2.635 GHz) for 2.4 GHz band and 1950 MHz (4.975 to 6.925 GHz) for 5.0/6.0 GHz band were obtained on the basis of -10 dB. Also, gain and radiation pattern characteristics are measured and shown in the frequency triple band as required.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.714-726
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• 2024

Researchers have developed various algorithms utilizing artificial intelligence (AI) to automatically and objectively diagnose patterns and extent of pulmonary emphysema or interstitial lung diseases on chest CT scans. Studies show that AI-based quantification of emphysema on chest CT scans reveals a connection between an increase in the relative percentage of emphysema and a decline in lung function. Notably, quantifying centrilobular emphysema has proven helpful in predicting clinical symptoms or mortality rates of chronic obstructive pulmonary disease. In the context of interstitial lung diseases, AI can classify the usual interstitial pneumonia pattern on CT scans into categories like normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation. This classification accuracy is comparable to chest radiologists (70%-80%). However, the results generated by AI are influenced by factors such as scan parameters, reconstruction algorithms, radiation doses, and the training data used to develop the AI. These limitations currently restrict the widespread adoption of AI for quantifying pulmonary emphysema and interstitial lung diseases in daily clinical practice. This paper will showcase the authors' experience using AI for diagnosing and quantifying emphysema and interstitial lung diseases through case studies. We will primarily focus on the advantages and limitations of AI for these two diseases.

• Journal of Radiation Protection and Research
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• v.39 no.3
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• pp.127-133
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• 2014

North Korea's uranium enrichment facility is a matter of international concern. It is of particular alarming to South Korea with regard to the security and safety of the country. This situation requires continuous monitoring of the DPRK and emergency preparedness on the part of the ROK. To assess the detectability of an undeclared uranium enrichment plant in North Korea, uranium concentrations in the air at both a short and a long distance from the enrichment facility were estimated. $UF_6$ source terms were determined by using existing information on North Korean facility and data from the operation experience of enrichment plants from other countries. Using the calculated source terms, two atmospheric dispersion models (Gaussian Plume Model and HYSPLIT models) and meteorological data were used to estimate the uranium particle concentrations from the Yongbyon enrichment facility. A maximum uranium concentration and its location are dependent upon the meteorological conditions and the height of the UF6 release point. This study showed that the maximum uranium concentration around the enrichment facility was about $1.0{\times}10^{-7}g{\cdot}m^{-3}$. The location of the maximum concentration was within about 0.4 km of the facility. It has been assumed that the uranium sample of about a few micrograms (${\mu}g$) could be obtained; and that few micrograms of uranium can be easily measured with current measurement instruments. On the contrary, a uranium concentration at a distance of more than 100 kilometers from the enrichment facility was estimated to be about $1.0{\times}10^{-13}{\sim}1.0{\times}10^{-15}g{\cdot}m^{-3}$, which is less than back-ground level. Therefore, based on the results of our paper, an air sample taken within the vicinity of the Yongbyon enrichment facility could be used to determine as to whether or not North Korea is carrying out an undeclared nuclear program. However, the air samples taken at a longer distance of a few hundred kilometers would prove difficult in detecting a clandestine nuclear activities.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

• Journal of Bio-Environment Control
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• v.11 no.4
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• pp.151-156
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• 2002

Root zone cooling, such as soil or nutrient solution cooling, is less expensive than air cooling in the whole greenhouse and is effective in promoting root activity, improving water absorption rate, decreasing plant temperature, and reducing high temperature stress. The heat transfer of a soil cooling system in a plastic greenhouse was analyzed to estimate cooling loads. The thermal conductivity of soil, calculated by measured heat fluxes in the soil, showed the positive correlation with the soil water content. It ranged from 0.83 to 0.96 W.m$^{[-10]}$ .$^{\circ}C$$^{[-10]}$ at 19 to 36％ of soil water contents. As the indoor solar radiation increased, the temperature difference between soil surface and indoor air linearly increased. At 300 to 800 W.m$^{-2}$ of indoor solar radiations, the soil surface temperature rose from 3.5 to 7.$0^{\circ}C$ in bare ground and 1.0 to 2.5$^{\circ}C$ under the canopy. Cooling loads in the root zone soil were estimated with solar radiation, soil water content, and temperature difference between air and soil. At 300 to 600 W.m$^{-2}$ of indoor solar radiations and 20 to 40％ of soil water contents,46 to 59 W.m$^{-2}$ of soil cooling loads are required to maintain the temperature difference of 1$0^{\circ}C$ between indoor air and root zone soil.