• Journal of information and communication convergence engineering
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• 제5권1호
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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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• 제14권2호
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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.

• 한국섬유공학회:학술대회논문집
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• 한국섬유공학회 2001년도 학술발표회 논문집(Proceedings of the Korean Textile Conference) 상
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• pp.87-90
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• 2001

• 한국정보시스템학회지:정보시스템연구
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• 제32권4호
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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.

• 한국정보통신학회논문지
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• 제8권1호
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• pp.185-191
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• 2004

본 논문은 컴퓨터 그래픽에서 주요 이슈중 하나인 의류 착장시스템 구현을 위하여 직물의 가장 큰 특성중의 하나인 드레이프성 측정에 관한 연구이다. 가장 최적의 직물의 드레이프성을 구하기 위해 거리함수를 이용하여 볼록점을 계산한 후 직물의 둘레 및 면적, 볼록점 사이의 최대 최소 점과 평균거리와 같은 정보를 구하였다. 그리고 직물의 드레이프성을 나타내는 척도로 직물의 둘레와 면적을 기준으로 원형도를 구하였다. 실험결과 원형도가 직물의 드레이프성을 나타내는 여러 특성치 중 가장 좋은 결과를 보였다. 측정된 직물의 드레이프성은 의류 착장시스템 개발에 기여할 것이다.

• 사물인터넷융복합논문지
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• 제10권1호
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• pp.7-12
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• 2024

암호화폐를 거래하기 위해서 거래자들은 개인의 암호화폐 지갑이 요구된다. 블록체인 기술을 활용한 암호화폐 그 자체는 우수한 보안성과 신뢰성을 보장받고 있어 블록체인 해킹 위협은 거의 불가능하지만, 거래자들이 거래를 위해 사용하는 거래소 환경에서 해킹 위협을 가장 많이 받고 있다. 거래 과정에서 블록체인을 통해 안전하게 거래가 이루어 진다 해도 거래자의 지갑 정보 자체가 해킹되면 이와 같은 과정들에서 보안을 확보할 수 없다. 거래소 해킹은 주로 거래자의 지갑 정보를 탈취함으로써, 해커가 피해자의 지갑 자산에 접근이 가능해지므로 이루어진다. 본 논문에서는 이를 방지하고자 기존 Hyperledger Fabric 구조를 재구성하고, Whitelisting을 활용하여 거래 과정에서 거래자의 신원 무결성을 검증하는 시스템을 제안하고자 한다. 해당 과정을 거쳐 해커에 의한 암호화폐 자산 피해를 방지하고 인지할 수 있다는 장점이 있다. 또한, 기존 Hyperledger Fabric에서 피해자의 지갑 정보가 탈취되었을 경우 발생할 수 있는 거래 과정의 문제점을 지적하고 이를 보완하고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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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.

• 패션비즈니스
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• 제19권6호
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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.

• 복식
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• 제58권4호
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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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• 제어로봇시스템학회 2003년도 ICCAS
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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.