• Proceedings of the PSK Conference
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• 2003.04a
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• pp.283.2-283.2
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• 2003

This study established a highly sensitive novel quantification method for detecting felodipine in human plasma using LC-MS/MS. The mobile phase used after degassing was composed of 1 mM ammonium acetate and acetonitrile (20:80, pH 6.0), with flow rate of 200 uL/min. One mL plasma were pipetted into glass tubes and spiked with 0.1 mL of internal standard solution. (omitted)

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.282.1-282.1
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• 2003

This study established a sensitive novel Quantification method for detecting glimepiride in human plasma using LC-MS/MS for pharmacokinetic studies. The mobile phase used after degassing was composed of 10 mM ammonium acetate and acetonitrile (20:80, pH 3.0), with flow rate of 200uL/min. One mL plasma were pipetted into glass tubes and spiked with 0.1 mL of internal standard solution. (omitted)

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.106-107
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• 2011

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.67-74
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• 2019

Visual inspection is regarded as one of the critical activities for quality control in a manufacturing company. it is thus important to improve the performance of detecting a defective part or product. There are three probable working modes for visual inspection: fully automatic (by automatic machines), fully manual (by human operators), and semi-automatic (by collaboration between human operators and automatic machines). Most of the current studies on visual inspection have been focused on the improvement of automatic detection performance by developing a better automatic machine using computer vision technologies. However, there are still a range of situations where human operators should conduct visual inspection with/without automatic machines. In this situation, human operators'performance of visual inspection is significant to the successful quality control. However, visual inspection of components assembled into a mobile camera module belongs to those situations. This study aims to investigate human performance issues in visual inspection of the components, paying more attention to human errors. For this, Abstraction Hierarchy-based work domain modeling method was applied to examine a range of direct or indirect factors related to human errors and their relationships in the visual inspection of the components. Although this study was conducted in the context of manufacturing mobile camera modules, the proposed method would be easily generalized into other industries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.61-64
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• 2011

There are many applications that require robust and accurate eye tracking, such as human-computer interface(HCI). In this paper, a novel approach for eye tracking with a principal component analysis on rotated face. In the process of iris detection, intensity information is used. First, for select eye region using principal component analysis. Finally, for eye detection using eye region's intensity. The experimental results show good performance in detecting eye from FERET image include rotate face.

• Analytical Science and Technology
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• v.11 no.3
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• pp.167-173
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• 1998

An electrothermal vaporization-hollow cathode glow discharge-atomic emission spectrometer(ETV-HCGD-AES) has been developed for detecting heavy metals in human serum and urine samples. Fisrt of all, we designed a glow discharge cell for atomic emission spectrometry and its analytical performance was studied with the standard reference materials(SRMs) purchased from the NIST. Practically, the ETV-HCGD-AES demonstrated better instrumental sensitivity and selectivity for detecting Hg and Pb in the SRMs, serum and urine, than ICP-OES since the ETV-HCGD-AES was not required the complicate sample digestion procedure, which improved sample transportation efficiency.

• Journal of Biomedical Engineering Research
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• v.35 no.2
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• pp.14-18
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• 2014

This study is about e-Book program based on human-computer interaction(HCI) system for physically handicapped person. By acquiring background knowledge of HCI, we know that if we use vision-based interface we can replace current computer input devices by extracting any characteristic point and tracing it. We decided betweeneyes as a characteristic point by analyzing facial input image using webcam. But because of three-dimensional structure of glasses, the person who is wearing glasses wasn't suitable for tracing between-eyes. So we changed characteristic point to the bridge of the nose after detecting between-eyes. By using this technique, we could trace rotation of head in real-time regardless of glasses. To test this program's usefulness, we conducted an experiment to analyze the test result on actual application. Consequently, we got 96.5% rate of success for controlling e-Book under proper condition by analyzing the test result of 20 subjects.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.215-220
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• 2013

They are well-known geometric properties of a circle that the perpendicular bisector of a chord passes through the center of a circle, and the intersection of the perpendicular bisectors of any two chords is its center. This paper is related to a fast pupil detection method capable of detecting the center and the radius of a pupil using these geometric properties at high speed when detecting the pupil region for iris segmentation. The proposed method is characterized as rapidly detecting the center and the radius of the pupil, extracting the candidate points of the circle in human eye images using morphological operations, and finding two chords using four points on the circular edge, and taking the intersection of the perpendicular bisectors of these two chords for its center. The proposed method can not only detect the center and the radius of a pupil rapidly but also find partially occluded pupils in human eye images.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.36-46
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• 2007

This paper presents an automated English scoring system designed to help non-native speakers of English, Korean-speaking learners in particular. The system is developed to help the 3rd grade students in junior high school improve their English grammar skills. Without human's efforts, the system identifies grammar errors in English sentences, provides feedback on the detected errors, and scores the sentences. Detecting grammar errors in the system requires implementing a special type of rules in addition to the rules to parse grammatical sentences. Error production rules are implemented to analyze ungrammatical sentences and recognize syntactic errors. The rules are collected from the junior high school textbooks and real student test data. By firing those rules, the errors are detected followed by setting corresponding error flags, and the system continues the parsing process without a failure. As the final step of the process, the system scores the student sentences based on the errors detected. The system is evaluated with real English test data produced by the students and the answers provided by human teachers.