• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.756-760
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• 2017

Meeting the growing demand deadlines, reducing the production cost and upgrading the quality control measurements are the reasons why the automotive part manufacturers are venturing into automation. Attaining these objectives is impossible with human inspection for many reasons. Accordingly, the introduction of inspection system purposely for door hinge bracket inspection is presented in this study as an alternative for human inspection. This proposal is designed to meet the demands, features and specifications of door hinge bracket manufacturing companies in striving for increased throughput of better quality. To improve demerits of this manual operation, inspection system is introduced. As the inspection algorithm, template matching algorithm is applied to distinguish the articles of good quality and the poorly made articles. Through the verification test of the inspection process algorithm and the similarity metric matching algorithm, the detection accuracy was 98%, and it was applied to the production site to contribute to the improvement of the productivity due to the decrease of the defective product.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1072-1081
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• 2008

We can categorize the network address allocation mechanism into two types. One is to assign a unique network address using the address allocation server and the other is to make a random address by itself and process the DAD(Duplicate Address Detection) procedure. In this paper we suggest a new address allocation mechanism based on the signal strength for the PLC-based home network. As the combined mechanism of two types this mechanism allocates a unique address for the new node from one of the existing nodes with the simple equation and with the priority based on the signal strength from the new node to the existing nodes. We can use this mechanism for the self-healing function when the packet from the source node may not be delivered to the destination node directly. We developed the simulator for our mechanism using the C# programming and verified the network address assigned uniquely based on the signal strength.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.57-63
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• 2008

This study uses the identification which is one of the critical components of psychological mechanism and enables replacing one's own self because of the needs of self-expression(disclosure) and creation. The study aims to improve educational effects using the realistic by increasing sense of the virtual reality and the attention. After the computer-based contents were developed and converted to be applied into robot, and then the contents were combined the student's photo and the avatar using automatic loading. Finally each one of the contents was applied to the students. The results of the investigation indicated that there were significant effects of the contents based on identification. In other words, the contents effect on student's attention, but not their academic achievement. The study could find the effect of the identification's application using the educational robot. We suggested that improving technical ability of the augmented virtuality as a face-detection and sensitive interaction may lead to the specific suggestions for educational effects for further research.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.82-91
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• 2009

Sign language spotting is the task of detecting and recognizing the signs in a signed utterance. The difficulty of sign language spotting is that the occurrences of signs vary in both motion and shape. Moreover, the signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and non-sign patterns(which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing a threshold model in a conditional random field(CRF) model is proposed. The proposed model performs an adaptive threshold for distinguishing between signs in the vocabulary and non-sign patterns. A hand appearance-based sign verification method, a short-sign detector, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experimental results show that the proposed method can detect signs from continuous data with an 88% spotting rate and can recognize signs from isolated data with a 94% recognition rate, versus 74% and 90% respectively for CRFs without a threshold model, short-sign detector, subsign reasoning, and hand appearance-based sign verification.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.

• Journal of the Korea Concrete Institute
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• v.21 no.5
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• pp.599-609
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• 2009

This paper discusses generalized modeling schemes for both reinforced concrete (RC) and post-tensioned (PT) flat plate buildings. In this modeling approach, nonlinear behavior due to slab flexure, moment and shear transfer at slab-column connections, and punching shear was included along with linear secant stiffness of each member or connection that accounts for concrete cracking. This generalized model was capable of simulating all different scenarios of slab-column connection failures such as brittle punching, flexure-shear interactive failure, and flexural failure followed by drift-induced punching. Furthermore, automatic detection of drift-induced punching shear and subsequent backbone curve modifications were realistically modelled by incorporating the limit state model, in which gravity shear versus drift capacity relations were adopted. The validation of the model was conducted using one-third scale two-story by two-bay RC and PT flat plate frames. The comparisons revealed that the model was robust and effective.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.181-182
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• 1998

In previous study for correlation between P-wave Signal Averaged Electrocardiography (SAECG) and Paroxysmal Atrial Fibrillation (PAF) subjects, we showed that the duration of P-wave in subjects is longer than in controls. In this respect, the P-wave SAECG is a new method proving to be an accurate and independent noninvasive marker for the risk of PAF. To prove this suggestion, accurate detection and alignment of P-wave are indispensible. In previous study, we measured P-wave duration by manual. So it was not accurate and consistent. To measure the P-wave duration accurately and automatically, we have developed an automatic algorithm for P-wave duration measurement. We showed that the duration of P- wave in the subjects is longer than in controls with this algorithm.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.421-433
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• 2011

The importance of acquisition of road information has recently been increased with a rapid growth of spatial-related services such as urban information system and location based service. This paper proposes an automatic road extraction method using object-based approach which was issued alternative of pixel-based method recently. Firstly, the spatial objects were created by MSRS(Modified Seeded Region Growing) method, and then the key road objects were extracted by using properties of objects such as their shape feature information and adjacency. The omitted road objects were also traced considering spatial correlation between extracted road and their neighboring objects. In the end, the final road region was extracted by connecting discontinuous road sections and improving road surfaces through their geometric properties. To assess the proposed method, quantitative analysis was carried out. From the experiments, the proposed method generally showed high road detection accuracy and had a great potential for the road extraction from high resolution satellite images.