Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.
Gyoo Gun Lim;Hai Yan Jin;Hye min Hwang;Hye won Cho;Jae Ik Ahn
Journal of Service Research and Studies
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v.12
no.1
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pp.36-48
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2022
As the use of smartphones has rapidly increased due to the development of digital technology, the expansion of smartphones, and the COVID-19 incident, dependence on smartphones and the Internet is emerging as a serious social problem. As one of the solutions to the smartphone overdependence problem, the government and companies are releasing smartphone overdependence prevention applications. However, research on the effectiveness of smartphone overdependence prevention applications is insufficient. Therefore, this study selects 25 applications serviced in Korea as analysis targets and evaluates smartphone overdependence prevention applications in terms of function and service using the FGI survey method to identify problems and propose improvements. In the function evaluation, the functions of blocking illegal/harmful apps/websites, limiting smartphone usage time, and monitoring smartphone usage status are provided in most applications, so satisfaction scores are also highly evaluated. However, functions such as location check, smombie prevention, and body camphishing prevention served by some applications are evaluated low due to poor performance and poor accuracy. Classified by service provider, government-providing applications need to accurately perform functions and improve convenience of use. Mobile-Carrier-providing applications need to improve connectivity with other carriers and compatibility with other smart devices like smartphone, tablet, etc. Other private enterprise-providing applications need to open AS channels such as customer service centre and chatbot to improve service.
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.
Internationally different food safety regulation and standards could cause troubles in trade unless those are built on scientific knowledge. In this research, we monitored the microbial population and analyzed the results to determine the level of microbial contamination in foodstuffs using relatively new statistical analysis (microbiological sampling plan, International Commission on Microbiological Specification for Foods). The goal of this research falls on establishing entirely new standards for various food categories addressed in the Korean "Food Code". Targets for monitoring were indicator organisms (i.e. total aerobic count, coliform and Escherichia coli) and foodborne pathogens (i.e. Bacillus cereus, Staphylococcus aureus and Clostridium perfringens) in ready-to-eat (RTE) products. As the result of the monitoring, total aerobic count, coliform, E. coli, and B. cereus in RTE products were found at the mean values of 2.10 log CFU/g, -0.60 log CFU/g, -1.33 log CFU/g and -1.23 log CFU/g, respectively. S. aureus was detected with the level of -1.35 log CFU/g only in fresh-cut food, while C. perfringens was -1.37 log CFU/g only in ready-to-cook food. Other samples did not have any food borne pathogens. Total aerobic count, B. cereus, S. aureus and C. perfringens satisfied the Food Code (the MFDS). On the basis of the analysis, we proposed a draft of microbial criteria for RTE products.
Kim, Won Jin;Kim, Chang Jae;Cho, Yeon Ju;Kim, Ji Sun;Kim, Hee Jeong;Lee, Dong Hoon;Lee, On Yu;Meng, Ju Pil
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.35
no.6
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pp.553-562
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2017
GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.
Kim, Hoe Woong;Kim, Sang Hwal;Han, Jae Won;Joo, Young Sang;Park, Chang Gyu;Kim, Jong Bum
Transactions of the Korean Society for Noise and Vibration Engineering
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v.25
no.1
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pp.48-57
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2015
In a sodium-cooled fast reactor, which is a Generation-IV reactor, refueling is conducted by rotating, but not opening, the reactor head to prevent a reaction between the sodium, water and air. Therefore, an inspection technique that checks for the presence of any obstacles between the reactor core and the upper internal structure, which could disturb the rotation of the reactor head, is essential prior to the refueling of a sodium-cooled fast reactor. To this end, an ultrasound-based inspection technique should be employed because the opacity of the sodium prevents conventional optical inspection techniques from being applied to the monitoring of obstacles. In this study, a ranging inspection technique using a plate-type ultrasonic waveguide sensor was developed to monitor the presence of any obstacles between the reactor core and the upper internal structure in the opaque sodium. Because the waveguide sensor installs an ultrasonic transducer in a relatively cold region and transmits the ultrasonic waves into the hot radioactive liquid sodium through a long waveguide, it offers better reliability and is less susceptible to thermal or radiation damage. A 10 m horizontal beam waveguide sensor capable of radiating an ultrasonic wave horizontally was developed, and beam profile measurements and basic experiments were carried out to investigate the characteristics of the developed sensor. The beam width and propagation distance of the ultrasonic wave radiated from the sensor were assessed based on the experimental results. Finally, a feasibility test using cylindrical targets (corresponding to the shape of possible obstacles) was also conducted to evaluate the applicability of the developed ranging inspection technique to actual applications.
Kim, Tae-Ho;Yoon, Jai-Woong;Kang, Seong-Hee;Suh, Tae-Suk
Progress in Medical Physics
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v.23
no.3
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pp.145-153
/
2012
In this study, we quantify the residual motion artifact in 4D-CT scan using the dynamic lung phantom which could simulate respiratory target motion and suggest a simple one-dimension theoretical model to explain and characterize the source of motion artifacts in 4DCT scanning. We set-up regular 1D sine motion and adjusted three level of amplitude (10, 20, 30 mm) with fixed period (4s). The 4DCT scans are acquired in helical mode and phase information provided by the belt type respiratory monitoring system. The images were sorted into ten phase bins ranging from 0% to 90%. The reconstructed images were subsequently imported into the Treatment Planning System (CorePLAN, SC&J) for target delineation using a fixed contour window and dimensions of the three targets are measured along the direction of motion. Target dimension of each phase image have same changing trend. The error is minimum at 50% phase in all case (10, 20, 30 mm) and we found that ${\Delta}S$ (target dimension change) of 10, 20 and 30 mm amplitude were 0 (0%), 0.1 (5%), 0.1 (5%) cm respectively compare to the static image of target diameter (2 cm). while the error is maximum at 30% and 80% phase ${\Delta}S$ of 10, 20 and 30 mm amplitude were 0.2 (10%), 0.7 (35%), 0.9 (45%) cm respectively. Based on these result, we try to analysis the residual motion artifact in 4D-CT scan using a simple one-dimension theoretical model and also we developed a simulation program. Our results explain the effect of residual motion on each phase target displacement and also shown that residual motion artifact was affected that the target velocity at each phase. In this study, we focus on provides a more intuitive understanding about the residual motion artifact and try to explain the relationship motion parameters of the scanner, treatment couch and tumor. In conclusion, our results could help to decide the appropriate reconstruction phase and CT parameters which reduce the residual motion artifact in 4DCT.
Kim, Jung-Sun;Nam, Ki-Pyo;Park, Seung-Yong;Ryu, Jae-Kwang;Cha, Min-Kyeong
The Korean Journal of Nuclear Medicine Technology
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v.14
no.1
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pp.3-7
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2010
Purpose: The usefulness of Positron Emission Tomography (PET) images in diagnosis, staging, recurrent and treatment response evaluation has already been known. However, tumors which are small size, located in lower lobe of lung or upper lobe of liver are shown misalignment, distortion and different Standard Uptake Value (SUV) by respiration in PET images. Therefore, if radiotherapy based on normal respiration, it may cause low treatment response or more side effects because targets which had to treat, out of treat range or over dose to normal tissue. The purpose of this study is to evaluate attenuation-correction with Average CT (ACT) for more accuracy SUV measurement and minimize artifact by respiration. Materials and Methods: 13 patients, who had tumors which are around the diaphragm, underwent ACT scan after Helical CT (HCT) scan with PET/CT (Discovery DSTE 8; GE Healthcare). We quantified the differences between attenuation corrected image with HCT and attenuation corrected image with ACT in artifact size and maximum SUV ($SUV_{max}$). Artifacts were evaluated by measurement of the curved photogenic area in the lower thorax of the PET images for all patients. $SUV_{max}$ was measured separately at the primary tumors. Analysis program was Advantage Workstation v4.3 (GE Healthcare). Patients were injected with 7.4 MBq (0.2 $mC_i$) per kg of $^{18}F$-FDG and scanned 1 hour after injection. The PET acquisition was 3 minute per bed. Results: Significantly lower artifact were observed in PET/ACT images than in PET/HCT images (below-thoracic artifacts caused by under corrected $1.5{\pm}3.5$ cm vs. $13.4{\pm}4.2$ cm). Significantly higher $SUV_{max}$ were noted in PET/ACT images than in PET/HCT images in the primary tumor. Compared with PET/HCT images, $SUV_{max}$ in PET/ACT images were higher by $5.3{\pm}3.9%$ (mean value) tumor. The highest difference was observed in Lower lobe of lung (7.7 to 8.7; 13%). Conclusion: Due to its significantly reduced artifacts in lower thoracic, attenuation corrected image with ACT images provided more reliable $SUV_{max}$ and may be helpful in monitoring treatment response. Moreover, ACT can separate upper lobe of liver and lower lobe of lung, it may be helpful in interpretation. ACT will be clinically useful, considering increased dose caused by ACT scan and adapt.
Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.
In the utilization of optical satellite imagery, which is greatly affected by clouds, periodic composite technique is a useful method to minimize the influence of clouds. Recently, a technique for selecting the optimal pixel that is least affected by the cloud and shadow during a certain period by directly inputting cloud and cloud shadow information during period compositing has been proposed. Accurate extraction of clouds and cloud shadowsis essential in order to derive optimal composite results. Also, in the case of an surface targets where spectral information is important, such as crops, the loss of spectral information should be minimized during cloud-free compositing. In thisstudy, clouds using two spectral indicators (Haze Optimized Tranformation and MeanVis) were used to derive a detection technique with low loss ofspectral information while maintaining high detection accuracy of clouds and cloud shadowsfor cabbage fieldsin the highlands of Gangwon-do. These detection results were compared and analyzed with cloud and cloud shadow information provided by Sentinel-2A/B. As a result of analyzing data from 2019 to 2021, cloud information from Sentinel-2A/B satellites showed detection accuracy with an F1 value of 0.91, but bright artifacts were falsely detected as clouds. On the other hand, the cloud detection result obtained by applying the threshold (=0.05) to the HOT showed relatively low detection accuracy (F1=0.72), but the loss ofspectral information was minimized due to the small number of false positives. In the case of cloud shadows, only minimal shadows were detected in the Sentinel-2A/B additional layer, but when a threshold (= 0.015) was applied to MeanVis, cloud shadowsthat could be distinguished from the topographically generated shadows could be detected. By inputting spectral indicators-based cloud and shadow information,stable monthly cloud-free composited vegetation index results were obtained, and in the future, high-accuracy cloud information of Sentinel-2A/B will be input to periodic cloud-free composite for comparison.
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