• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.2
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• pp.34-41
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• 2009

The latest vehicle yields a superior safety and reduction of driving burden by monitoring the driving state of vehicle and its environment with various sensors. To detect other vehicles and objects of the rear left and right-side blind spot area of driver, provide the information about a existence of objects inside the blind spot, and give a signal to avoid collision, this study proposes the intelligent outside rear-view mirror system. This task has substantially complicated several factors. For example, the size, geometry and features of the various vehicles which might enter the monitored zone is varied widely and therefore present various reflective characteristics. This study proposes the optimal specification and configuration of optical system and IR array sensor of blind spot detection system, and shows the results of the performance evaluation of developed system.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.47-52
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• 2006

The cultural grounds of laver has been surveyed using SPOT-5 satellite images to calculate the facilities of laver cultivation area in the coastal waters of Korea 10m resolution multispectral images of SPOT-5 are adopted for the south area of Daebu Island, Hwaseong city to develop an automatic detection approach of laver nets that consists of the following: band difference technique, canny edge detector and morphological analysis. The satellite-based facilities number was relatively high as compared with the licensed number in 2005, 676,749 chaek and 572,745 chaek(柵, unit of measure for laver farm), respectively. The data could be applied to achieve a good harvest for laver seaweed growers and to control its national production keeping a stable market price for the government body.

• Journal of Microbiology and Biotechnology
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• v.27 no.3
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• pp.471-479
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• 2017

White spot syndrome virus (WSSV) is a major threat to the shrimp farming industry and so far there is no effective therapy for it, and thus early diagnostic of WSSV is of great importance. However, at the early stage of infection, the extremely low-abundance of WSSV DNA challenges the detection sensitivity and accuracy of PCR. To effectively detect low-abundance WSSV, here we developed a pre-amplification PCR (pre-amp PCR) method to amplify trace amounts of WSSV DNA from massive background genomic DNA. Combining with normal specific PCR, 10 copies of target WSSV genes were detected from ${\sim}10^{10}$ magnitude of backgrounds. In particular, multiple target genes were able to be balanced amplified with similar efficiency due to the usage of the universal primer. The efficiency of the pre-amp PCR was validated by nested-PCR and quantitative PCR, and pre-amp PCR showed higher efficiency than nested-PCR when multiple targets were detected. The developed method is particularly suitable for the super early diagnosis of WSSV, and has potential to be applied in other low-abundance sample detection cases.

• Journal of Veterinary Science
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• v.21 no.2
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• pp.31.1-31.5
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• 2020

In this study, whiteleg shrimp (Penaeus vannamei) imported from Vietnam were collected from South Korean markets, and examined for 2 viruses: infectious hypodermal and hematopoietic necrosis virus (IHHNV, recently classified as decapod penstyldensovirus-1), and white spot syndrome virus (WSSV). Among 58 samples, we detected IHHNV in 23 samples and WSSV in 2 samples, using polymerase chain reaction and sequencing analyses. This is the first report of IHHNV and WSSV detection in imported shrimp, suggesting that greater awareness and stricter quarantine policies regarding viruses infecting shrimp imported to South Korea are required.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.41-47
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• 2009

A solution to the problems of recognizing as one spot or detection failures for complex regions, in which many spots representing proteins are overlapped and saturated, is suggested. The accumulated gradients of each point in complex regions are calculated, and the resulting accumulated gradient image segmented using watershed technique. The suggested solution show better and efficient result than existing method for spot separation, detects more protein spots hidden in the image of 2-dimensional electrophoresis, and expands the scope of prediction.

• Journal of Bio-Environment Control
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• v.33 no.1
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• pp.1-11
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• 2024

In this study, five artificial intelligence (AI) models: Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc were used to classify tea leaf diseases. Eight image categories were used: healthy, algal leaf spot, anthracnose, bird's eye spot, brown blight, gray blight, red leaf spot, and white spot. Software used in this study was Orange 3 which functions as a Python library for visual programming, that operates through an interface that generates workflows to visually manipulate and analyze the data. The precision of each AI model was recorded to select the ideal AI model. All models were trained using the Adam solver, rectified linear unit activation function, 100 neurons in the hidden layers, 200 maximum number of iterations in the neural network, and 0.0001 regularizations. To extend the functionality of Orange 3, new add-ons can be installed and, this study image analytics add-on was newly added which is required for image analysis. For the training model, the import image, image embedding, neural network, test and score, and confusion matrix widgets were used, whereas the import images, image embedding, predictions, and image viewer widgets were used for the prediction. Precisions of the neural networks of the five AI models (Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc) were 0.807, 0.901, 0.780, 0.800, and 0.771, respectively. Finally, the SqueezeNet (local) model was selected as the optimal AI model for the detection of tea diseases using tea leaf images owing to its high precision and good performance throughout the confusion matrix.

• Journal of Auto-vehicle Safety Association
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• v.4 no.1
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• pp.27-32
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• 2012

Recently, in order to reduce traffic accident related fatalities, increasing number of studies are conducted regarding the vehicle safety enhancement devices. But very few studies about test procedures and requirements for vehicle safety systems are being carried out. Since BSD, as one of the most important safety features, is installed on a new vehicle, its performance test method has to be evaluated. Independent factors irrelevant to the device types including collision position, vehicle speed and closing speed are used to calculate test distance away from the current vehicle. Effect of roadway geometry as radius of curvature is introduced to propose possible misjudgement of following vehicle as adjacent one. The study results would be utilized to enhance the test procedure of BSD performance.

• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.235-242
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• 2000

This paper presents a method to detect buildings using shadow information in satellite imagery. We classify image into three categories of building region, shadow region and background region to find buildings with consistent intensity. After the removal of noises in building regions and shadow regions, buildings adjacent to shadow regions are detected using the constraint of building and shadow sizes. The algorithm has been applied to KOMPSAT and SPOT images and the result showed buildings are efficiently detected.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• Parasites, Hosts and Diseases
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• v.59 no.1
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• pp.15-22
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• 2021

Artemisinin resistance (ART) has been confirmed in Greater Mekong Sub-region countries. Currently, C580Y mutation on Pfkelch13 gene is known as the molecular marker for the detection of ART. Rapid and accurate detection of ART in field study is essential to guide malaria containment and elimination interventions. A simple method for collection of malaria-infected blood is to spot the blood on filter paper and is fast and easy for transportation and storage in the field study. This study aims to evaluate LAMP-SNP assay for C580Y mutation detection by introducing an extra mismatched nucleotide at the 3' end of the FIP primer. The LAMP-SNP assay was performed in a water bath held at a temperature of 56℃ for 45 min. LAMP-SNP products were interpreted by both gel-electrophoresis and HNB-visualized changes in color. The method was then tested with 120 P. falciparum DNA from dried blood spot samples. In comparing the LAMP-SNP assay results with those from DNA sequencing of the clinical samples, the 2 results fully agreed to detect C580Y. The sensitivity and specificity of the LAMP-SNP assay showed 100%. There were no cross-reactions with other Plasmodium species and other Pfkelch13 mutations. The LAMP-SNP assay performed in this study was rapid, reliable, and useful in detecting artemisinin resistance in the field study.