• Korean Journal of Clinical Laboratory Science
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• v.53 no.2
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• pp.188-192
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• 2021

The persistent increase of aspartate aminotransferase (AST) due to the presence of a macro-AST can confuse diagnostic or therapeutic decisions in many clinical situations. In this study, we report a case of isolated and persistent AST-elevation without any clinical sign of dysfunction in organs such as the liver, skeletal muscle, cardiac muscle, etc. Despite various investigations, no definite cause for the elevation of AST could be found. With the help of polyethylene glycol (PEG) precipitation, we showed that macro-AST formation was responsible for the elevation of the AST titer in this case. Early recognition of macro-AST by PEG precipitation can prevent diagnostic confusion and unnecessary and even invasive tests.

• Convergence Security Journal
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• v.21 no.2
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• pp.57-66
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• 2021

Deep neural networks (DNNs) provide excellent performance for image, speech, and pattern recognition. However, DNNs sometimes misrecognize certain adversarial examples. An adversarial example is a sample that adds optimized noise to the original data, which makes the DNN erroneously misclassified, although there is nothing wrong with the human eye. Therefore studies on defense against adversarial example attacks are required. In this paper, we have experimentally analyzed the success rate of detection for adversarial examples by adjusting various parameters. The performance of the ensemble defense method was analyzed using fast gradient sign method, DeepFool method, Carlini & Wanger method, which are adversarial example attack methods. Moreover, we used MNIST as experimental data and Tensorflow as a machine learning library. As an experimental method, we carried out performance analysis based on three adversarial example attack methods, threshold, number of models, and random noise. As a result, when there were 7 models and a threshold of 1, the detection rate for adversarial example is 98.3%, and the accuracy of 99.2% of the original sample is maintained.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.19-25
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• 2013

Recently, more accurate database information of facilities is being required, with the increase in importance of urban road facility management. Therefore, this study proposed how to automatically detect particular traffic signs necessary for efficient construction of road facility DB. For this study, central locations of facilities were searched, after recognition and automatic detection of particular traffic signs through an image. Then, coordinate values of traffic signs calculated in the study were compared with real coordinate values, in order to evaluate the accuracy of traffic sign locations which were finally detected. Computer vision technology was used in recognizing and detecting traffic signs through OPEN CV-based coding, and photogrammetry was used in calculating accurate locations of detected traffic signs. For the experiment, circular road signal(No Parking) and triangular road signal(Crosswalk) were chosen out of various kinds of road signals. The research result showed that the circular road signal had a nearly 50cm error value, and the triangular road signal had a nearly 60cm error value, when comparing the calculated coordinates with the real coordinates. Though this result is not satisfactory, it is considered that there would be no problem to find locations of traffic signs.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.

• Clinical and Experimental Pediatrics
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• v.46 no.3
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• pp.295-301
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• 2003

Glutaric aciduria type 1(GA1) is an autosomal recessive disorder of the lysine, hydroxylysine and tryptophan metabolism caused by the deficiency of mitochondrial glutaryl-CoA dehydrogenase. This disease is characterized by macrocephaly at birth or shortly after birth and various neurologic symptoms. Between the first weeks and the 4-5th year of life, intercurrent illness such as viral infections, gastroenteritis, or even routine immunizations can trigger acute encephalopathy, causing injury to caudate nucleus and putamen. But intellectual functions are well preserved until late in the disease course. We report a one-month-old male infant with macrocephaly and hypotonia. In brain MRI, there was frontotemporal atrophy(widening of sylvian cistern). In metabolic investigation, there were high glutarylcarnitine level in tandem mass spectrometry and high glutarate in urine organic acid analysis, GA1 was confirmed by absent glutaryl-CoA dehydrogenase activity in fibroblast culture. He was managed with lysine free milk and carnitine and riboflavin. He developed well without a metabolic crisis. If there is macrocephaly in an infant with neuroradiologic sign of frontotemporal atrophy, GA1 should have a high priority in the differential diagnosis. Because current therapy can prevent brain degeneration in more than 90% of affected infants who are treated prospectively, recognition of this disorder before the brain has been injured is essential for treatment.