• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.23-28
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• 2007

In this paper, we propose ATM switch structure including AAL type 2 switch which can efficiently transmit low-bit rate data, even if the network has many endpoints. We simulate the architecture of ATM switch fabric that is modeled in computer program and analyze the performance according to offered loads. ATM switch proposed in this paper can support cell switching for all types of AAL cells which consist of AAL type 1, AAL type 2, AAL type 3/4, and AAL type 5 cells. We propose two switch fabric methods; One supports the AAL type 2 cell processing per input port, the other global AAL type 2 cell processing for every input port. The simulation results show that the latter is superior to the former. But the former has a strong point for easy implementation and extensibility. The proposed ATM switch fabric architecture is applicable to mobile communication, narrow band services over ATM network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.687-701
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• 2020

In the production of industrial fabric, it needs automatic real-time system to detect defects on the fabric for assuring the defect-free products flow to the market. At present, many visual-based methods are designed for detecting the fabric defects, but they usually lead to high false alarm. Base on this reason, we propose a Sobel operator combined with patch statistics (SOPS) algorithm for defects detection. First, we describe the defect detection model. mean filter is applied to preprocess the acquired image. Then, Sobel operator (SO) is applied to deal with the defect image, and we can get a coarse binary image. Finally, the binary image can be divided into many patches. For a given patch, a threshold is used to decide whether the patch is defect-free or not. Finally, a new image will be reconstructed, and we did a loop for the reconstructed image to suppress defects noise. Experiments show that the proposed SOPS algorithm is effective.

• Proceedings of the Korean Fiber Society Conference
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• 2001.04b
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• pp.87-90
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• 2001

• The Journal of Information Systems
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• v.32 no.4
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• pp.149-162
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• 2023

Purpose In the textile industry, fabric defects significantly impact product quality and consumer satisfaction. This research seeks to enhance defect detection by developing a transformer-based deep learning image segmentation model for learning high-dimensional image features, overcoming the limitations of traditional image classification methods. Design/methodology/approach This study utilizes the ZJU-Leaper dataset to develop a model for detecting defects in fabrics. The ZJU-Leaper dataset includes defects such as presses, stains, warps, and scratches across various fabric patterns. The dataset was built using the defect labeling and image files from ZJU-Leaper, and experiments were conducted with deep learning image segmentation models including Deeplabv3, SegformerB0, SegformerB1, and Dinov2. Findings The experimental results of this study indicate that the SegformerB1 model achieved the highest performance with an mIOU of 83.61% and a Pixel F1 Score of 81.84%. The SegformerB1 model excelled in sensitivity for detecting fabric defect areas compared to other models. Detailed analysis of its inferences showed accurate predictions of diverse defects, such as stains and fine scratches, within intricated fabric designs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.185-191
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• 2004

This article is concerned with cloth wearing system issues arising in the computer graphics. In particular, we study the issues of fabric drape properties for representing cloth wearing system. The convex points based on distance function are calculated to represent useful fabric drape properties. The information such as perimeter area, max and min point among convex point, the average distance between convex points are extracted. A strategy of a circularity based on the perimeter and area is considered for fabric drape property measurement. By experimental result, the circularity is most powerful factor to represent the drape property among the several characteristics. The measured drape properties will contribute to cloth wearing system development.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.7-12
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• 2024

To trade cryptocurrency, traders require a personal cryptocurrency wallet. Cryptocurrency itself using blockchain technology is guaranteed excellent security and reliability, so the threat of blockchain hacking is almost impossible, but the exchange environment used by traders for transactions is most subject to hacking threats. Even if transactions are made safely through blockchain during the transaction process, if the trader's wallet information itself is hacked, security cannot be secured in these processes. Exchange hacking is mainly done by stealing a trader's wallet information, giving the hacker access to the victim's wallet assets. In this paper, to prevent this, we would like to reconstruct the existing Hyperledger Fabric structure and propose a system that verifies the identity integrity of traders during the transaction process using whitelisting. The advantage is that through this process, damage to cryptocurrency assets caused by hackers can be prevented and recognized. In addition, we aim to point out and correct problems in the transaction process that may occur if the victim's wallet information is stolen from the existing Hyperledger Fabric.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.998-1000
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• 2018

데이터 무결성을 보장하는 블록체인은 IoT 환경과 같은 비금융 분야에서 활용이 증가되고 있으며 IoT 환경의 수집된 자료를 저장할 수 있는 단순한 인프라로 활용되고 있다. 이 논문에서는 산업사고 발생시 주요 원인에 대한 추적검증을 위해 산업현장에서의 환경정보를 블록체인에 저장하기 위한 센서자료 수집시스템을 기술한다. 본 개발 시스템은 허가형 블록체인 플랫폼인 HyperLedger Fabric을 사용하여 온도, 충격 및 영상데이터의 주요 특징을 요약하여 블록체인에 저장할 수 있도록 한다.

• Journal of Fashion Business
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• v.19 no.6
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• pp.28-41
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• 2015

Properties of textile fabrics influence the appearance, aesthetics, and performance of garment. Drape and related properties of fabrics affect profoundly the static and dynamic appearance during wearer's movement. The three dimensional shape of the folded structure often deforms with time or with subtle vibration around the fabric specimen during the drape measurement. Due to the uneven and complex nature of fabrics, the overall shape of the fabric specimen on the drape tester often becomes unstable. There is a need to understand the fundamental mechanisms of how draping may generate pleasing forms. Two drape test methods, conventional Cusick drape test, and in-built drape tester, based on a depth camera, are compared. Fabric specimens including cotton, linen, silk, wool, polyester, and rayon are investigated for the fabric drape and other physical/mechanical parameters. Drape coefficient values of fabric specimens are compared based on the final drape images, together with the intermediate 3D drape images of the specimens during elevation process of the drape tester equipped with a stepper motor system. The correlation coefficient between the data based on the two methods is reasonably high. Another advantage from the depth camera system is that it allows further analysis of three-dimensional information regarding the fabric drape shape, including the shape of nodes or crest and trough.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.26-34
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• 2008

The purpose of this study was to create a database of information on the mechanical properties of two different waterproof and breathable shell fabric groups(high density woven and PTFE laminate) used for outdoor apparel and to compare and correlate data of their mechanical properties and hand values. The results of this study were as follows; There were no statistically significant differences between two fabric groups in extension, bending and shearing properties. There were statistically significant differences between two fabric groups in MMD, SMD, LC and we values. High density woven fabrics had smoother surface than PTFE laminated fabrics. PTFE laminated fabrics can be compressed easily more than high density woven fabrics but their recovery after compression was not better than high density woven fabrics. There were statistically significant differences between two fabric groups in NUMERI, FUKURAMI. There was statistically significant difference between two fabric groups in total hand value. Total hand value and mean deviation of MIU had a very high and statistically significant negative correlation coefficient.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.53-56
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• 2003

For identifying how a sample knit fabric is woven a method to obtain positional information of each yarn of the sample from voxel data made out of its x-ray CT images is newly proposed in this paper. The positional information is obtained by tracing the each yarn. The each yarn is traced by estimating a direction of the yarn in a certain small region in which the yarn can be regarded as straight and moving the region slightly along the estimated direction alternately. The yarn direction is estimated by correlating the voxel data in the region with a three-dimensional yarn model. The effectiveness of this method is confirmed by applying the method to voxel data made out of CT images of a knit fabric experimentally.