• Journal of Families and Better Life
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• v.32 no.5
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• pp.193-205
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• 2014

The purpose of this research is to gather basic data to make nursery teachers' role clear and to suggest a way to improve their expertise by investigating their sensitivity and expertise. To fulfill this aim, this research was performed by targeting 180 nursery teachers responsible for infant classes in national, public, and private nursery schools. To measure the nursery teachers' sensitivity, Gerber's (2003) teacher sensitivity indicator is used. And to measure the efficacy of teaching play, the indicator, which was developed by E. Shin, Y. Yu and H. Park (2004), was used through modification and complement. Also for measuring the teacher's expertise, research data were collected by the generalized and modified questionnaire which was used in H. Yoon's (2010) research. The results of the analysis of collected data show that the teacher group with higher sensitivity in the infant class shows meaningfully higher professional ethics, higher performance, and higher recognition of expertise than the teacher group with lower sensitivity. And the teacher group with higher awareness of the efficacy of play shows higher professional ethics, higher performance, and higher recognition of expertise than the teacher group with lower sensitivity. too. Also, the results of the analysis of the correlation between the infant teacher's sensitivity, efficacy of teaching play, and recognition of expertise show that the teacher's sensitivity has a static correlation with the total points of social necessity, professional ethics, fairness, teacher's performance, and recognition of expertise. When we generalize the research results, we find that positive sensitivity and higher efficacy of teaching play make the infant class teacher's expertise recognition higher.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.761-762
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• 2008

In this paper, a novel approach for robust recognition of partially occluded 3-D target objects from computationally reconstructed integral images is proposed. The occluding object noises are selectively removed from the picked-up elemental images and performance of the proposed integral imaging-based 3-D target recognition system can be improved.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.704-710
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• 2016

In this paper, we proposed pole position detection system for providing exact location information to users. The proposed system consists of pole recognition part and pole number recognition part. Above all, exact pole recognition is carried out by PDD(Pole Detection Device). And recognition of pole number is performed by PID(Pole Inspection Device). Acquired image by using line scan camera is judged whether it is free bracket or not through image processing. When it is judged as free bracket, pole number image is acquired by OCR camera and recognized by OCR. By recognizing pole number, exact location information is provided to user.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2515-2517
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• 2002

The process of character recognition goes through 5 steps; image acquisition, character region extraction, preprocessing, character region segmentation, character recognition. Therefore the final recognition rate of character recognition is directly affected by the performance of each step. This paper is a leading research for object recognition using image processing algorithm which is one of the field of study in computer vision. And this paper will suggest an algorithm to extract the portion of number chain, which is part of the research embodying a system to perceive the data of manufacture and the name of the producer on the wrapping of groceries. In addition, this can extract the number chain comparatively accurate without using many complex algorithm by diving and extracting the moving number region at the same time.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.213-218
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• 2009

This paper describes a classical algorithm carrying out dynamic 3D obstacle recognition for autonomous underwater vehicles (AUVs), Support Vector Machines (SVMs). SVM is an efficient algorithm that was developed for recognizing 3D object in recent years. A recognition system is designed using Support Vector Machines for applying the capabilities on appearance-based 3D obstacle recognition. All of the test data are taken from OpenGL Simulation. The OpenGL which draws dynamic obstacles environment is used to carry out the experiment for the situation of three-dimension. In order to verify the performance of proposed SVMs, it compares with Back-Propagation algorithm through OpenGL simulation in view of the obstacle recognition accuracy and the time efficiency.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.334-338
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• 2022

In visual simultaneous localization and mapping (vSLAM), the correct recognition of a place benefits in relocalization and improved map accuracy. However, its performance is significantly affected by the environmental conditions such as variation in light, viewpoints, seasons, and presence of dynamic objects. This research addresses the problem of feature occlusion caused by interference of dynamic objects leading to the poor performance of visual place recognition algorithm. To overcome the aforementioned problem, this research analyzes the role of scene semantics in correct detection of a place in challenging environments and presents a semantics aided visual place recognition method. Semantics being invariant to viewpoint changes and dynamic environment can improve the overall performance of the place matching method. The proposed method is evaluated on the two benchmark datasets with dynamic environment and seasonal changes. Experimental results show the improved performance of the visual place recognition method for vSLAM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.396-402
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• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.158-164
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• 2014

Substance P and neuropeptide Y were discovered as early diagnostic biomarkers of acute myocardial infarction in Korean patients and confirmed using enzyme-linked immunosorbent assay (ELISA). We screened 12 peptides from the sera of Korean acute myocardial infarction (AMI) patients and detected 3 peptides (neuropeptide Y, substance P, and N-terminal pro-B-type natriuretic peptide) to be elevated from patients' sera by liquid chromatography mass/mass spectrometry. The elevated concentration of 3 peptides was confirmed by ELISA. The screening results revealed the substance P, neuropeptide Y, and pro-B-type natriuretic peptide (47-76) concentrations were higher in patients' sera than in healthy controls. The sensitivity and specificity of substance P for AMI diagnostic marker were 80% and 83%, respectively, and those of neuropeptide Y were 87% and 90%, respectively compared to healthy controls. These results suggest that substance P and neuropeptide Y could be used as early diagnostic biomarkers in patients with AMI.

• Bulletin of the Korean Chemical Society
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• v.34 no.4
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• pp.1101-1107
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• 2013

In this study, total mercury and methyl mercury in whole blood of Korean was analyzed so as to investigate the correlation between total mercury (T-Hg) and methyl mercury (Me-Hg). 4000 whole blood samples were divided in four groups, according to T-Hg concentration in percentile: group I (p25-p50), group II (p50-p75), group III (p75-p95) and group IV (p95-p100). 100 samples were randomly selected from the each group, and Me-Hg concentration was measured. T-Hg concentration in whole blood was analyzed using a Direct Mercury Analyzer-80 and obtained limit of detection (LOD) was $0.2{\mu}gL^{-1}$. Me-Hg concentration was analyzed with ethylate derivatization using headspace-gas chromatography-mass spectrometry, and obtained LOD of methyl mercury was $0.5{\mu}gL^{-1}$. The geometric means of T-Hg and Me-Hg were $6.35{\mu}gL^{-1}$ and $4.44{\mu}gL^{-1}$, respectively, and 71.91% of T-Hg was presented as Me-Hg.