• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.444-454
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• 2005

Recently, the requirements of multi-resolution models of a solid model, which represent an object at multiple levels of feature detail, are increasing for engineering tasks such as analysis, network-based collaborative design, and virtual prototyping and manufacturing. The research on this area has focused on several topics: topological frameworks for representing multi-resolution solid models, criteria for the level of detail (LOD), and generation of valid models after rearrangement of features. As a solution to the feature rearrangement problem, the new concept of the effective zone of a feature is introduced in the former part of the paper. In this paper, we propose a feature-based non-manifold modeling system to provide multi-resolution models of a feature-based solid or non-manifold model on the basis of the effective feature zones. To facilitate the implementation, we introduce the class of the multi-resolution feature whose attributes contain all necessary information to build a multi-resolution solid model and extract LOD models from it. In addition, two methods are introduced to accelerate the extraction of LOD models from the multi-resolution modeling database: the one is using an NMT model, known as a merged set, to represent multi-resolution models, and the other is storing differences between adjacent LOD models to accelerate the transition to the other LOD. We also suggest the volume of the feature, regardless of feature type, as a criterion for the LOD. This criterion can be used in a wide range of applications, since there is no distinction between additive and subtractive features unlike the previous method.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.828-833
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• 2009

WWW which is an applicable massive set of document on the Web is a thesaurus of various information for users. However, Search engines spend a lot of time to retrieve necessary information and to filter out unnecessary information for user. In this paper, we propose the EFAM(the Extended Fuzzy AHP Method) model to manage the Web resource efficiently, and to make a decision in the problem of specific domain definitely. The EFAM model is concerned with the emotion analysis based on the domain corpus information, and it composed with systematic common concept grids by the knowledge of multiple experts. Therefore, The proposed the EFAM model can extract the documents by considering on the emotion criteria in the semantic context that is extracted concept from the corpus of specific domain and confirms that our model provides more efficient decision-making through an experiment than the conventional methods such as AHP and Fuzzy AHP which describe as a hierarchical structure elements about decision-making based on the alternatives, evaluation criteria, subjective attribute weight and fuzzy relation between concept and object.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.132-138
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• 2009

Cognitive radio is considered as a promising solution to scarce spectrum problem. The primary object of cognitive radio is to increase spectral efficiency, while causing limited interference to primary users who are using the spectrum. Hence, an essential part of cognitive radio systems is spectrum sensing which determines whether a particular spectrum is occupied or not by a primary user at a particular time. However, sensing decision of each individual secondary user alone may not be reliable enough due to shadowing and multipath fading of wireless channels. The so called hidden terminal problem makes the problem even worse, possibly yielding undesired interference to the primary users. Recently, cooperative spectrum sensing is emerging as a remedy to these problems of individual sensing. Cooperative sensing allows a group of secondary users to share local sensing information to extract a global decision with high fidelity. In this paper, we investigate a cooperative spectrum sensing algorithm based on hard decisions of local sensing outcomes. Specifically, we propose an effective scheme for combining local decisions by introducing weighting factors that reflect reliability of the corresponding secondary user. Through computer simulations, the performance of the proposed combining scheme is compared with that of the conventional scheme without weighting factors in various environments.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.569-576
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• 2000

The GST can extract the position of facial features without a prior information in an image. However, this method requires a plenty of the processing time because the mask size to process GST must be larger than the size of object such as eye, mouth and nose in an image. In addition, it has the complexity for the computation of middle line to decide facial features. In this paper, we proposed two methods to overcome these disadvantage of the conventional method. First, we used the reduced image having enough information instead of an original image to decrease the processing time. Second, we used the extracted peak positions instead of the complex statistical processing to get the middle lines. To analyze the performance of the proposed method, we tested 200 images including, the front, rotated, spectacled, and mustached facial images. In result, the proposed method shows 85% in the performance of feature extraction and can reduce the processing time over 53 times, compared with existing method.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.52-58
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• 2008

The object of this study is to investigate the effects of intermittent cyclic stretching on the smooth muscle cells (SMCs) seeded onto aligned multi-layered fibrous scaffold. To make multi-layered fibrous scaffold, polyurethane (PU) and poly(ethylene oxide) (PEO) were electrospun alternatively, then were immersed into distilled water to extract PEO. Various types of scaffolds were fabricated depending on fiber directions, i.e., aligned or randomly oriented. The direction of stretching was either parallel or vertical to the fiber direction for the aligned scaffolds. The stretching was also applied to the randomly aligned scaffolds. The duration of stretching was 2 min with 15 min resting period. During the stretching, the maximum and minimum strain was adjusted to be 10 and 7%, respectively with the frequency of 1 Hz. The bioactivities of cells on the scaffolds were assessed by quantifying DNA, collagen, and glycosaminoglycan (GAG) levels. And the cell morphology was observed by staining F-actin. SMCs under parallel stretching to the fiber direction responded more positively than those in other conditions. From the results, we could explain the morphological effect of a substrate on cellular activities. In addition the synergistic effects of substrate and mechanical stimuli effects were confirmed.

• Smart Media Journal
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• v.5 no.1
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• pp.24-29
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• 2016

To satisfy the needs of high-level intelligent surveillance system, it shall be able to extract objects and classify to identify precise information on the object. The representative method to identify one's identity is face recognition that is caused a change in the recognition rate according to environmental factors such as illumination, background and angle of camera. In this paper, we analyze the robust face recognition of face image by changing the distance through a variety of experiments. The experiment was conducted by real face images of 1m to 5m. The method of face recognition based on Linear Discriminant Analysis show the best performance in average 75.4% when a large number of face images per one person is used for training. However, face recognition based on Convolution Neural Network show the best performance in average 69.8% when the number of face images per one person is less than five. In addition, rate of low resolution face recognition decrease rapidly when the size of the face image is smaller than $15{\times}15$.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.715-726
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• 2019

With the increasing prevalence of high-resolution satellite images, the need for technology to generate accurate 3D information from the satellite images is emphasized. In order to create a digital terrain model (DTM) that is widely used in applications such as change detection and object extraction, it is necessary to extract trees, buildings, etc. that exist in the digital surface model (DSM) and estimate the height of the ground. This paper presents a method for automatically generating DTM from DSM extracted from KOMPSAT-3A stereo images. The technique was developed to detect the non-ground area and estimate the height value of the ground by using the previously constructed low-resolution topographic data. The average vertical accuracy of DTMs generated in the four experimental sites with various topographical characteristics, such as mountainous terrain, densely built area, flat topography, and complex terrain was about 5.8 meters. The proposed technique would be useful to produce high-quality DTMs that represent precise features of the bare-earth's surface.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.129-134
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• 1994

A Laser Cutter is designed for the precise fabrications in the shipyards recently. The cutter is a gantry type one with specified functions of movability and strength in order to satisfy the workability. The gantry frame should move with a certain velocity in a relatively short time for the proper cutting of the object materials. The gantry is fitted with ball screw and the acceleration field is formed by actuating this ball screw. The relative displacement should be within the allowable design criteria to make sure the precise cutting of the materials by the laser. In this paper, modal and structural analysis for a Laser Cutter which is commonly used in the shipyards, is carried out to check the design criteria of the system. The system is modeled by placing the proper shell and soils finite elements and fictitious mass properties to represent the real one. The way how to extract the loading conditions based on the given velocity criteria of the system is presented. Static structural analysis is performed and the results came out as expected. Modal analysis for finding eigen-values and mode shapes of the system is performed and it is shown that the time dependent dynamic analysis is unnecessary for this system for its operating circumstances.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.263-272
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• 2008

The proposed system can achieve more safety of RFID system with the 2-step authentication procedures for the enhancement about the security of general RFID systems. After it has authenticated RFID tag, additionally, the proposed system extract the characteristic information in the user image for acquisition of the additional authentication information of the user with the camera. In this paper, the system which was proposed more enforce the security of the automatic entrance and exit authentication system with the cognitive characters of RFID tag and the extracted characteristic information of the user image through the camera. The RFID system which use the active tag and reader with 2.4GHz bandwidth can recognize the tag of RFID in the various output manner. Additionally, when the RFID system have errors. the characteristic information of the user image is designed to replace the RFID system as it compare with the similarity of the color, outline and input image information which was recorded to the database previously. In the experimental result, the system can acquire more exact results as compared with the single authentication system when it using RFID tag and the information of color characteristics.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.419-428
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• 2021

Shadow removal plays a key role for the pre-processing of image processing techniques such as object tracking and detection. With the advances of image recognition based on deep convolution neural networks, researches for shadow removal have been actively conducted. In this paper, we propose a novel method for shadow removal, which utilizes self attention distillation to extract semantic features. The proposed method gradually refines results of shadow detection, which are extracted from each layer of the proposed network, via top-down distillation. Specifically, the training procedure can be efficiently performed by learning the contextual information for shadow removal without shadow masks. Experimental results on various datasets show the effectiveness of the proposed method for shadow removal under real world environments.