• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1711-1717
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• 2020

X-ray of up to 9MeV are used for container inspection. X-ray intensity must be maintained stably regardless of changes in time. If dose is not constant, it may affect the image quality, and as a result, may affect the inspection of abnormal cargo. Therefore, to acquire high-quality images, continuous dose monitoring is required. In this study, the ion-chamber based device was developed for monitoring the dose change in high-energy x-ray. And to estimate the performance of signal-processing device change according to the environmental change, the output changing due to the change of temperature and humidity was observed. In addition, verification of the device was performed by measuring the output change. As a result of the measurement, there was no significant difference in performance due to changes in temperature and humidity, and the change in output according to the change in exposure was linear. Therefore, it was found that the developed device is suitable for the dose monitoring of high-energy x-ray.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.4
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• pp.215-220
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• 1999

Concrete micro-cracks that are grown while the structures are under construction or in service, propagate gradually or rapidly by external forces and environmental effects. As described above, almost concrete structures generally have cracks, so for the safety and durability of structures, studies to detect cracks using nondestructive tests have been treated in great deal. The purpose of this study is to evaluate characteristics of AE signals detected from notched concrete beams bending test with different loading using one of nondestructive test, Acoustic Emission (AE) method. Furthermore this study predicts the location of initial crack and measures direction of crack propagation for on-line monitoring before the crack really grows in structures by using two-dimensional AE source location based on rectangular method with three-point bending test. This will allow efficient maintenance of concrete structures through monitoring of internal cracking based on acoustic emission method.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.39 no.2
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• pp.78-84
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• 2006

A high performance liquid chromatography assay method for spiramycin in fish muscle was developed. The developed method was evaluated and validated by monitoring spiramycin in olive flounder (Paralichthys olivaceus), black rock fish (Sebastes schlegeli) and in live conger eel (Anguilla japonica) in fish farms and distribution centers. Using the developed method, the recovery rate was up to 82.4-88.8%, which was higher than that of conventional methods (77.6-87.1%). In particular, the proposed sample treatment protocol was suitable for use with fish samples to remove low molecular weight materials and pigments that could interfere an accurate analysis. The prepared stock solution was very stable, and it remained chemically stable for 5 weeks at $4^{\circ}C$. The performance limit of the developed method for spiramycin acid in fish muscle was 0.05 ppm. One hundred thirty-four fish samples including olive flounder, black rock fish and live conger eel were analyzed to evaluate the overall efficiency of the modified method and to monitor the actual condition of spiramycin usage in fish farms. Olive flounder and black rock fish were collected from fish farms in coastal areas of Korea, and live conger eels were purchased from a fish market in the Busan area from September 2001 to March 2002. According to the overall performance of the developed method, it was considered suitable for the monitoring of spiramycin in fish muscle. The suggested method of analysis for spiramycin in fish muscle is registered in the Korean Official Methods of Food Analysis and is currently tieing utilized for fishery products inspection by the Korea Food and Drug Administration and the National Fisheries Products Quality Inspection Service.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.405-410
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• 2016

Elevator industry is a field that is mechanical, electrical and electronic technology and constantly requires inspection and maintenance considering various applications and various types. Recently, various elevator control and monitoring technologies with IT are developing for elevators on land. But technologies with IT have been hardly done in marine elevator that is consistently assured safety and reliability of life cycle for its parts in poor environment. In this paper, we implemented embedded main controller, floor controller and car controller that meet the requirements and use NMEA network protocol by analyzing home and abroad integrated elevator operation and management systems. Especially, we secured reliability of maintenance by real-time fault diagnosis and control that was implemented with limit switch, gyro sensor, temperature/humidity/barometric pressure sensor and fire detection sensor thinking over the environmental conditions of terrestrial and marine elevator.

• Computers and Concrete
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• v.33 no.4
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.583-589
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• 2020

Recently, the utility of UAS (Unmanned Aerial System) for a smart farm using various sensors and ICT (Information & Communications Technology) is expected. In particular, it has proven its effectiveness as an outdoor crop monitoring method through various indices and is being studied in various fields. This study analyzes damage to crops caused by natural disasters and measures the damage area of rice plants. To this end, data is acquired using BG-NIR (Blue Green_Near Infrared Red) and RGB sensors, and image analysis and NDWI (Normalized Difference Water Index) index performed to review crop damage caused by in the rainy season. Also, point cloud data based on image analysis is generated, and damage is measured by comparing data before and after the typhoon through an inspection map. As a result of the study, the growth and rainy season damage of rice was examined through NDWI index analysis, and the damage area caused by typhoon was measured by analysis of the inspection map.

• Journal of Food Hygiene and Safety
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• v.36 no.3
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• pp.239-247
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• 2021

In order to confirm the impact of the Positive List System (PLS) being applied to all agricultural products from January 1, 2019, we analyzed 28,693 points of inspection-related data on agricultural products distributed in Gyeonggi-do from 2018 to 2020. The ratio of cases exceeding the standard for the total inspection performance was 1.0% in 2018, 1.2% in 2019, and 1.2% in 2020. Out of the 114 cases exceeding the standard in 2019, 55 were applied on a Maximum Residue Limit (MRL) of 0.01 mg/kg, and out of the 115 cases exceeding the standard in 2020, 66 were applied on a MRL of 0.01 mg/kg. To improve this, it seems necessary to manage unintentional pollution, conventional use for unregistered crops, and illegal pesticides. Fluquinconazole detection resulted from unintentional contamination, and diazinon, chlorothalonil, and methabenzthiazuron detection resulted from conventional use in unregistered crops. Chinomethionat is a pesticide component that was discarded in the past and its current use has been attributed to the smuggling of pesticides. This study and future monitoring data can be used as reference data for system supplementation and on-site management reinforcement.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.125-128
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• 2003

Low-velocity impact damage is a major concern in the design of structures made of composite materials, because impact damage is hidden inside and cannot be detected by visual inspection. The piezoelectric thin film sensor can be used to detect variations in structural and material properties for structural health monitoring. In this paper, the PVDF and PZT sensors were used for monitoring impact damage initiation in Gr/Ep composite panel to illustrate this potential benefit. A series of impact test at various impact energy by changing impact mass and height is performed on the instrumented drop weight impact tester. The wavelet transform(WT) is used to decompose the piezoelectric sensor signals in this study. Test results show that the particular waveform of sensor signals implying the damage initiation and development are detected above the damage initiation impact energy. And it is found that both PZT and PVDF sensors can be used to detect the impact damage.

• Journal of Food Hygiene and Safety
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• v.35 no.4
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• pp.365-374
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• 2020

This study was conducted to monitor the residual pesticides on a total of 320 stalk and stem vegetables from January 2019 to December 2019 in the Incheon metropolitan area. Pesticide residues in samples were analyzed by the multi-residue method for 373 pesticides using GC-MS/MS, LC-MS/MS, GC-ECD, GC-NPD and HPLC-UVD. Risk assessment was also carried out based on the amount of stalk and stem vegetables consumed. The linearity correlation coefficient for the calibration curve was 0.9951 to 1.0000, LOD 0.002 to 0.022 mg/kg, LOQ 0.005 to 0.066 mg/kg and recovery was 82.0 to 108.0%. According to the monitoring of pesticides, 36 (11.3%) of 320 were detected with pesticide residues and 3 (0.9%) samples exceeded the maximum residual limit. The detection frequency for Chinese chives and Welsh onion was higher than that for other stalk and stem vegetables. The frequently detected pesticides were etofenprox, procymidone, fludioxonil, and pendimethalin. As a tool of risk assessment through the consumption of pesticide detectable agricultural products, the ratio of estimated daily intake (EDI) to acceptable daily intake (ADI) was calculated in the range of 0.0062-24.1423%. These results indicate that there is no particular health risk through consumption of commercial stalk and stem vegetables detected with pesticide residues.