• Analytical Science and Technology
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• v.5 no.3
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• pp.277-283
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• 1992

Acid effects on the ICP-AES signals are studied as the concentrations of nitric acid, hydrochloric acid, sulfuric acid, and 1:1 mixture of nitric acid and hydrochloric acid are changed. Almost all analyte signals are depressed. The extent of the depression due to the pressence of the acids became to be pecular when the acid concentration was over 1%. Among the acids used, the suppression due to sulfuric acid is most severe and unexpectable. The ratios of the analyte signal to Ar signal and the Mg II signal to Mg I signal are measured as the concentration of the acids changed. In this study, it is proved that the main reason of the signal reduction is the change in the nebulization efficiency, for example, droplet size distribution, viscosity and surface tension variation, not the alteration of plasma excitation characteristics. There was no relationship found between ionization potential and analyte signal reduction in ICP-MS.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.24-29
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• 2005

Purpose : Instead of conventional two-dimensional (2-D) visual stimuli, three-dimensional (3-D) visual stimuli with stereoscopic vision were employed for the study of functional Magnetic Resonance Imaging (f-MRI). In this paper f-MRI with 3-D visual stimuli is investigated in comparison with f-MRI with 2-D visual stimuli. Materials and Methods : The anaglyph which generates stereoscopic vision by viewing color coded images with red-blue glasses is used for 3-D visual stimuli. Two-dimensional visual stimuli are also used for comparison. For healthy volunteers, f-MRI experiments were performed with 2-D and 3-D visual stimuli at 3.0 Tesla MRI system. Results : Occipital lobes were activated by the 3-D visual stimuli similarly as in the f-MRI with the conventional 2-D visual stimuli. The activated regions by the 3-D visual stimuli were, however, larger than those by the 2-D visual stimuli by $18\%$. Conclusion : Stereoscopic vision is the basis of the three-dimensional human perception. In this paper 3-D visual stimuli were applied using the anaglyph. Functional MRI was performed with 2-D and 3-D visual stimuli at 3.0 Tesla whole body MRI system. The occipital lobes activated by the 3-D visual stimuli appeared larger than those by the 2-D visual stimuli by about $18\%$. This is due to the more complex character of the 3-D human vision compared to 2-D vision. The f-MRI with 3-D visual stimuli may be useful in various fields using 3-D human vision such as virtual reality, 3-D display, and 3-D multimedia contents.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.161-168
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• 2013

Nowadays, one of the most interested area of automobile industry is the production of vehicle which has collision safety and ability to produce less amount of $CO_2$. The achievement of such a dual performance is done by choosing the materials like dual phase steel, ferrite bainite steel, etc. These steels have been used in automotive chassis and body parts, and also used to be formed by hole flanging to meet the goal of strength and design requirement. The formability of sheet material was experimented by hole expansion test and the judgement relies on human eye and his experience. This manual judgement involves many errors and large deviation. This paper develops the automatic crack recognition system which finds a crack based on CCD image to complement the problem of the current method depending on human's sense.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.1-12
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• 2004

In this paper, we present an identificable face (n face) detection method robust to color degradation and partial veiling. This method is composed of three parts: segmentation of face candidate regions, extraction of face candidate windows, and decision of veiling. In the segmentation of face candidate regions, face candidate regions are detected by finding skin color regions and facial components such as eyes, a nose and a mouth, which may have degraded colors, from an input image. In the extraction of face candidate windows, face candidate windows which have high potentials of faces are extracted in face candidate regions. In the decision of veiling, using an eigenface method, a face candidate window whose similarity with eigenfaces is maximum is determined and whether facial components of the face candidate window are veiled or not is determined in the similar way. Experimental results show that the proposed method yields better the detection rate by about $11.4\%$ in test DB containing color-degraded faces and veiled ones than a conventional method without considering color degradation and partial veiling.

• Journal of Veterinary Clinics
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• v.32 no.2
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• pp.205-208
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• 2015

A 6-year old, neutered male, Maltese dog was presented in Veterinary Medical Teaching Hospital, Seoul National University. As hyphema and aqueous flare in the right eye were found, medical treatment for uveitis was started. Four months later, anterior displacement of dorsotemporal iris was observed. A mass originating from ciliary body of the right eye was revealed by ocular sonography. There was no evidence of metastasis on thoracic and abdominal radiographic imaging. Enucleation was performed on the right eye due to the enlargement of the mass and deteriorating uveitis. On histopathological evaluation, anterior uveal melanocytoma with chronic hemorrhage was confirmed. This case suggests adequate removal of intraocular neoplasm by enucleation can be curative in case of continuous hemorrhage or inflammation in the eye that cannot be controlled by non-surgical medications.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.665-671
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• 2014

Recent researches show that the traffic fatality rate in fog is higher than that in rain and snow. In that sense, methods to measure visibility accurately and to notify the measured visibility information to drivers are required. We thus developed a system for measuring the road visibility in realtime by employing CCTV cameras. In this paper, we also propose a wide-area visibility information system through measuring the visibility of every highway by using the developed system. The proposed wide-area visibility information system uses the video clips from the CCTV camera instead of the output from the expensive fog sensor. Hence, we expect that it can reduce the cost of installation and operation dramatically and the measured visibility information has a number of applications.

• Journal of IKEEE
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• v.24 no.1
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• pp.232-237
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• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1314-1319
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• 2018

The current TW3 - based maximum height prediction technique used in KMAA(Korean Medical Academy of Auxology) is manual and subjective, and it requires a lot of time and effort in the medical treatment, while the interest in the child's growth is very high. In addition, the technique of classifying images using deep learning, especially convolutional neural networks, is used in many fields at a more accurate level than the human eyes, also there is no exception in the medical field. In this paper, we introduce a TW3 algorithm using deep learning, that uses the convolutional neural network to predict the growth level of the left hand bone, to predict the maximum height of child and youth in order to increase the reliability of predictions and improve the convenience of the doctor.

• Journal of IKEEE
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• v.25 no.3
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• pp.430-436
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• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.