KSCE Journal of Civil and Environmental Engineering Research
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v.42
no.2
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pp.291-298
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2022
Recently developed drones are inexpensive and very convenient to operate. As a result, the production and utilization of spatial information using drones are increasing. However, most drones acquire images with a low-cost global navigation satellite system (GNSS) and an inertial measurement unit (IMU). Accordingly, the accuracy of the initial location and rotation angle elements of the image is low. In addition, because these drones are small and light, they can be greatly affected by wind, making it difficult to maintain a certain overlap, which degrades the positioning accuracy. Therefore, in this study, images are taken at different times in order to analyze the positioning accuracy according to changes in certain exterior orientation parameters. To do this, image processing was performed with Pix4D Mapper and the accuracy of the results was analyzed. In order to analyze the variation of the accuracy according to the exterior orientation parameters in detail, the exterior orientation parameters of the first processing result were used as meta-data for the second processing. Subsequently, the amount of change in the exterior orientation parameters was analyzed by in a strip-by-strip manner. As a result, it was proved that the changes of the Omega and Phi values among the rotation elements were related to a decrease in the height accuracy, while changes in Kappa were linked to the horizontal accuracy.
Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.
Jong Hyuk Lee;Kyung Woong Kang;Seungil Baek;Wonkook Kim
Korean Journal of Remote Sensing
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v.39
no.3
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pp.355-361
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2023
Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.
The purpose of this study is to investigate the utilization of major learning tools among radiology science students and assess the accuracy of a conversational artificial intelligence service program, specifically a chatbot, in the context of the national radiologic technologist licensing exam. The survey revealed that 84.3% of radiology science students actively utilize electronic devices during their learning process. In addition, 104 out of 140 respondents said they use search engines as a top priority for efficient data collection while studying. When asked about their awareness of chatbots, 80% of participants responded affirmatively, and 22.9% reported having used chatbots for academic purposes at least once. From 2018 to 2022, exam questions from the first and second periods were presented to the chatbot for answers. The results showed that ChatGPT's accuracy in answering first period questions increased from 48.28% to 60%, while for second period questions, it increased from 50% to 62.22%. Bing's accuracy in answering first period questions improved from 55% to 64.55%, and for second period questions, it increased from 48% to 52.22%. The study confirmed the general trend of radiology science students utilizing electronic devices for learning and obtaining information through the internet. However, conversational artificial intelligence service programs in the field of radiation science face challenges related to accuracy and reliability, and providing perfect solutions remains difficult, highlighting the need for continuous development and improvement.
Recently, the government has emphasized the importance of establishing an innovation system for SMEs as part of an innovative growth strategy for national economic development. SMEs in Korea are experiencing many difficulties due to the loss of industrial competitiveness due to the powerful wave of the 4th industrial revolution along with the pandemic of COVID-19 that started in 2020. In relation to environmental changes, it is emerging as an important issue for SMEs to pursue open innovation for survival and growth, as well as to possess excellent technological innovation capabilities. In accordance with the need for such research, this study analyzed the factors that affect business performance or technological performance of small and medium-sized manufacturers, and identified the relationship between these influencing factors and corporate performance. The results of this study suggest that it is important for SMEs to effectively utilize R&D services and technology innovation capabilities and resources possessed by SMEs to secure a competitive advantage. The results of this stu dy are considered to be able to provide basic data and information necessary for SMEs to secu re a competitive edge and enhance industrial competitiveness through government support systems and open innovation.
Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.
Melvin B. Diaz;Sang Seob Kim;Gyung Won Lee;Kwang Yeom Kim;Changsoo Lee;Jin-Seop Kim;Minseop Kim
Geomechanics and Engineering
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v.34
no.4
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pp.449-459
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2023
The design and development of underground nuclear waste repositories should cover the performance evaluation of the different components such as the construction materials because the long term stability will depend on their response to the surrounding conditions. In South Korea, Gyeonju bentonite has been proposed as a candidate to be used as buffer and backfilling material, especially in the form of blocks to speed up the construction process. In this study, various cylindrical samples were prepared with different dry density and water content, and their physical and mechanical properties were analyzed and correlated with X-ray CT observations. The main objective was to characterize the samples and establish correlations for non-destructive estimation of physical and mechanical properties through the utilization of X-ray CT images. The results showed that the Uniaxial Compression Strength and the P-wave velocity have an increasing relationship with the dry density. Also, a higher water content increased the values of the measure parameters, especially for the P-wave velocity. The X-ray CT analysis indicated a clear relation between the mean CT value and the dry density, Uniaxial Compression Strength, and P-wave velocity. The effect of the higher water content was also captured by the mean CT value. Also, the relationship between the mean CT value and the dry density was used to plot CT dry densities using CT images only. Moreover, the histograms also provided information about the samples heterogeneity through the histograms' full width at half maximum values. Finally, the particle size and heterogeneity were also analyzed using the Madogram function. This function identified small particles in uniform samples and large particles in some samples as a result of poor mixing during preparation. Also, the μmax value correlated with the heterogeneity, and higher values represented samples with larger ranges of CT values or particle densities. These image-based tools have been shown to be useful on the non-destructive characterization of bentonite samples, and the establishment of correlations to obtain physical and mechanical parameters solely from CT images.
Young-Nam Kim;Jun Hyeok Choi;Song Yeob Kim;Hyeonji Choe;Yerim Shin;Young-Eun Yoon;Keum-Ah Lee;Min-Jeong Kim;Yong Bok Lee
Korean Journal of Environmental Agriculture
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v.41
no.4
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pp.282-287
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2022
BACKGROUND: Green algae (Chlorella spp.) has been widely used as a biofertilizer to improve the crop yield and quality. However, available information is not enough to verify the mechanism of green algae's beneficial impact on strawberry. This study was conducted to investigate the effect of Chlorella fusca CHK005 application on the growth and nutrient status of strawberry plant and fruit characteristics. METHODS AND RESULTS: A total of 800 seedlings of strawberry variety 'Kuemsil' were planted. Once a week, C. fusca culture solution (1.0 × 107 cells mL-1) was applied into soil via irrigation in four different concentrations: no application (control), 1/1000 times (× 0.5), 1/500 times (× 1), and 1/250 times (× 2). Result showed that growth of strawberry plant was enhanced by Chlorella application and the highest impact on fresh weight (FW) and chlorophyll content of the plants were observed in × 2 treatment, followed by × 1, × 0.5, and control treatments. The phosphorus (P) concentration in the plant was significantly higher in × 1 and × 2 treatments compared to control. In case of fruit quality, sugar content (°Brix), hardness, and FW were lowest in control, but these values increased as application levels of Chlorella were higher. Also, P and K contents in the fruits increased with increasing the application levels and significant correlation between P content and oBrix in the fruits was found. CONCLUSION(S): Overall, Chlorella application seemed to improve plant growth and fruit quality by increasing the utilization efficiency of P and K in strawberries.
KIPS Transactions on Software and Data Engineering
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v.12
no.7
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pp.325-332
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2023
Currently, the world's population has already entered a super-aging era, and the rate is expected to increase rapidly to about 40% by 2050. However, the rapid development of automation technology and the online service sector, the main technologies of the Fourth Industrial Revolution, are still further isolating them in a world where many inconveniences and development technologies are applied. As such, alienation in daily life is widely expanded in various fields, but the financial service sector is one of the must-use areas regardless of age because of its strong nature in the public service sector, and is a very important factor in the period when branches are rapidly decreasing. However, the current utilization rate of mobile banking services is not around 5%, so users over 60 are rarely able to use them. The UX design of the most frequently used remittance service screen in mobile banking services was proposed, and the difficulty of trying to find the preferred bank among 56 or more banks was solved by analyzing the usage rate of each bank and dividing it into three stages by age group from 50 or older. In addition, it was designed to strengthen customized services by showing their recently used banks as the top priority. The design proposed in this study obtained an average of 4.8 points or more out of 5 points as a result of usability satisfaction through interviews with less than 50 senior groups. This study is believed to help each bank upgrade its different mobile banking designs in a unified manner.
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.4
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pp.245-257
/
2023
The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.
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