• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.87-91
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• 2016

Background: A hand-held detector for an emergency response was developed for nuclide identification and to estimate the information of the ambient dose rate in the scene of an accident as well as the radioactivity of the contaminants. Materials and Methods: To achieve this, the most suitable sensor was first selected as a cadmium zinc telluride (CZT) semiconductor and the signal processing unit from a sensor and the signal discrimination and storage unit were successfully manufactured on a printed circuit board. Results and Discussion: The performance of the developed signal processing unit was then evaluated to have an energy resolution of about 14 keV at 662 keV. The system control unit was also designed to operate the CZT detector, monitor the detector, battery, and interface status, and check and transmit the measured results of the ambient dose rate and radioactivity. In addition, a collimator, which can control the inner radius, and the airborne dust sampler, which consists of an air filter and charcoal filter, were developed and mounted to the developed CZT detector for the quick and efficient response of a nuclear accident. Conclusion: The hand-held CZT detector was developed to make the in-situ gamma-ray spectrometry and its performance was checked to have a good energy resolution. In addition, the collimator and the airborne dust sampler were developed and mounted to the developed CZT detector for a quick and efficient response to a nuclear accident.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.79-86
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• 2010

Generally, image fusion is defined as generating re-organized image by merging two or more data using special algorithms. In remote sensing, image fusion technique is called as Pan-sharpening algorithm because it aims to improve the spatial resolution of original multispectral image by using panchromatic image of high-spatial resolution. The pan-sharpened image has been an important task due to various applications such as change detection, digital map creation and urban analysis. However, most approaches have tended to distort the spectral information of the original multispectral data or decrease the spatial quality compared with the panchromatic image. In order to solve these problems, a novel pan-sharpening algorithm is proposed by considering the spectral and spatial characteristics of multispectral image. The algorithm is applied to the KOMPSAT-2 and QuickBird satellite image and the results showed that our method can improve the spectral/spatial quality compared with the existing fusion algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.421-430
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• 2010

Image segmentation technique is becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification to extract object regions of interest within images. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Improved Seeded Region Growing (ISRG) and Region merging. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained multi-spectral edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying ISRG to consider spectral and edge information. Finally the region merging process, integrating region texture and spectral information, was carried out to get the final segmentation result. The accuracy assesment was done using the unsupervised objective evaluation method for evaluating the effectiveness of the proposed method. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.1
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• pp.201-208
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• 2002

The measurement parameter of QiguㆍInyoung pulse diagnosis distinguishes the excess, deficiency and quick-temper of pulse through relative comparison of Qigu and Inyoung. We have estimated the relationship between measurement of QiguㆍInyoung pulse wave detection system and measurement of manual pulse diagnosis by means of quantifying pulse peak and Inyoung/Qigu index. The results can be summarized as follows : When standardizing manual pulse diagnosis measurement was standardized, Inyoung index of machinery measurement was more significantly correlative with the index of manual pulse diagnosis than Qigu index of machinery measurement. The ratio of Inyoung/Qigu magnitude with machinery measurement was doser to manual pulse diagnosis than that of Qigu and Inyoung pulse magnitude measured separately. A linear proportion relationship was found between measurement of QiguㆍInyoung pulse wave detection system and measurement of manual pulse diagnosis. It was necessary to adjust the output signal of pulse in order to estimate the exact relationship between measurement of QiguㆍInyoung pulse wave detection system and measurement of manual pulse diagnosis.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1365-1372
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• 2018

Recently, the aging of agricultural society has caused a rapid increase in safety accidents in -agricultural machinery. Sometimes, the wounded may be left unattended resulting serious situation. In order to solve these problems, ICT technology is used to detect and inform the accident quickly when a safety accident such as overturning, collision or other accidents occurs during the operation or moving the agricultural machinery, such as cultivator, rearing machine, and tractor. A system capable of minimizing the amount of data is required. In this paper, an ICT - based automatic accident detection & propagation system is proposed for the agricultural machinery accident such as colliding crashes or overturning of agricultural machinery. The proposed system enables quick rescue by sending a text message automatically to family, acquaintances, hospitals and 119 in the event of an agricultural accident.

• Food Science and Industry
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• v.54 no.4
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• pp.293-300
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• 2021

Food safety accidents have been increasing by 2% over 5,000 cases every year since 2009. Most people know that the best method to prevent food safety accidents is a quick inspection, but there is a lack of inspection technology that can be used at the non-analytic level to food production and distribution sites. Among the recent on-site diagnostic technologies, the methods for testing gene-based food poisoning bacteria were introduced with the STA technology, which can range from sample to detection. If food safety information can be generated without forgery by directly inspecting food hazard factors by remote, unmanned, not human, pollution sources can be managed by predicting risks more accurately from current big-data and artificial intelligence technology. Since this information processing can be used on smartphones using the current cloud technology, it is judged that it can be used for food safety to small food businesses or catering services.

• Journal of the Korean Society of Visualization
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• v.20 no.3
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• pp.136-145
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• 2022

Later flow immunoassay (LFIA) is a protein analytical method based on immunoreaction. On the LFIA based protein analytical method, bioreceptor molecule plays a key role, and so a system that evaluates and manages the binding affinity of bioreceptor is needed to secure detection reliability. In this study, Lateral Flow Immunoassay based rapid Bioreceptor Screening Method (rBSM) is presented that provide a simple and quick evaluating method for the binding affinity to the target protein of the antibody as model bioreceptor. To verify this evaluation method, Virus-like particles (VLP) and anti-VLP antibodies are selected as a model norovirus, which is target protein, and the candidate bioreceptors respectively. Among the 5 different candidate antibodies, appropriate antibody could be sorted out within 30 minutes through rBSM. In addition, selected antibodies were applied to two representative LFIA based techniques, sandwich assay and competitive assay. Among these methods, sandwich assay showed more effective VLP detection method. Through applying selected antibodies and techniques to the commercialized mass production lines, an VLP detecting LFIA kit was developed with a detection limit of 10¹² copies/g of VLPs in real samples. Since this proposed method in this study could be easily transformable into other combinations with bioreceptors, it is expected that this technique would be applied to LFIA kit development system and bioreceptor quality management.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• Korean Journal of Veterinary Service
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• v.40 no.1
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• pp.61-66
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• 2017

Calf diarrhea is a disease experienced by almost all of calves after birth and is one of the representative causes of damage to farmers due to mass mortality and of economic losses to them by inhibiting normal growth. In this study, we conducted quick detection of etiologic agents of diarrhea by using a rapid diagnostic kit to multiply diagnose antigens of five etiologic agents of calf diarrhea (rotavirus, coronavirus, Escherichia coli, Cryptosporidium, Giardia) in Hanwoo (Korean native cattle) calves. When the positive antigen proportion of the calf diarrheal feces for each farm was analyzed, rotavirus, coronavirus, Escherichia coli, Cryptosporidium, and Giardia showed antigen positive rates of 0~67%, 0~20%, 0~60%, 0~20%, and 0~67%, respectively. With regard to the antigen positive rate by age in days after birth, 1-week-old calves showed the antigen positive rate of 20% in rotavirus and 20% in Giardia, and 2-week-old calves showed that of 50% in rotavirus. In addition, 4-week-old calves showed the antigen positive rate of 10% in rotavirus, 10% in coronavirus, 10% in Escherichia coli, and 30% in Giardia, and 8-week-old calves showed the antigen positive rate of 17% in coronavirus, 50% in Escherichia coli, 17% in Cryptosporidium, and 33% in Giardia. Based on the results of this study, the etiologic agents of diarrhea in Hanwoo calves for each farm are widely distributed. Although younger than 2-week-old calves were strongly positive for rotavirus, older than 4-week-old calves were highly positive for Giardia and Escherichia coli. In conclusion, we considered that a rapid diagnostic kit is an effective method for quick detection of etiologic agents and would be helpful for cattle farmers and veterinarians to select appropriate therapeutic method.