• Title/Summary/Keyword: 프린팅 알고리즘

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Algorithm for Fabricating 3D Breast Implants by Using MRI and 3D Scan Data (MRI와 3D 스캔 데이터를 이용한 3D 프린팅 유방 인공보형물의 제작 알고리즘)

  • Jeong, Young Jin;Choi, Dong Hun;Kim, Ku-Jin
    • Journal of Korea Multimedia Society
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    • v.22 no.12
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    • pp.1385-1395
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    • 2019
  • In this paper, we propose a method to fabricate a patient-specific breast implant using MRI images and 3D scan data. Existing breast implants for breast reconstruction surgery are primarily fabricated products for shaping, and among the limited types of implants, products similar to the patient's breast have been used. In fact, the larger the difference between the shape of the breast and the implant, the more frequent the postoperative side effects and the lower the satisfaction. Previous researches on the fabrication of patient-specific breast implants have used limited information based on only MRI images or on only 3D scan data. In this paper, we propose an algorithm for the fabrication of patient-specific breast implants that combines MRI images with 3D scan data, considering anatomical suitability for external shape, volume, and pectoral muscle. Experimental results show that we can produce precise breast implants using the proposed algorithm.

Development of G-code generating software for 3D printer in Hadoop (Hadoop에서 3D 프린팅용 G-code 생성 소프트웨어 개발)

  • Lee, Kyuyoung;Nam, Kiwon;Kim, Gunyoung;Kim, Sungsuk;Yang, Sun-Ok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.78-80
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    • 2017
  • 3D 프린터를 이용하여 출력을 하기 위해서는 3D 모델 데이터를 G-code로 변환하는 과정을 수행해야 한다. 일반적으로 3D 모델은 STL 파일 형식으로 저장되는데, 이 파일은 대개 삼각형 형식인 페이셋들의 좌표 데이터를 포함하고 있다. 만약 3D 모델의 크기가 커지거나 정밀도가 높아진다면, 페이셋의 수가 매우 많아지게 되고, 결과적으로 3D 모델에서 G-code로 변환하는 시간이 길어지게 된다. 본 논문에서는 널리 활용되고 있는 Hadoop에서 변환 소프트웨어를 개발하고자 하였다. Hadoop은 마스터 노드와 여러 데이터 노드들이 Map-Reduce 방식으로 작업을 수행한다. 이러한 노드들은 하둡 파일시스템(HDFS)을 공유할 수 있어 작업을 효율적으로 수행할 수 있다. 이에 본 논문에서는 이 시스템의 기능을 활용하여 기존에 개발된 분산 알고리즘을 변형한 후 이를 구현하고자 한다.

Development of Methods for Detecting Inkjet Malfunction (잉크젯 헤드의 오작동 검출 방법 개발)

  • Kwon, Kye-Si;Go, Jung-Kook;Kim, Jin-Won;Kim, Dong-Soo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.10
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    • pp.1529-1535
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    • 2010
  • For the reliable use of inkjet technology as patterning tools, the jetting of the inkjet dispenser needs to be monitored for real-time detection of any malfunction. We present a self-sensing circuit that can be used to detect jetting failure by measuring electrical signals only. In addition, practical problems involved in the monitoring of inkjets in multinozzle printheads are discussed. In the study, software was developed and presented to demonstrate the feasibility of the proposed method for detecting inkjet jetting failure in a printing system.

A Study on the conversion method of 3D modeling for 3D printing production (3D 프린팅 제작을 위한 3D 모델링 변환 방법에 관한 연구)

  • Choi, Tae-Jun;Kim, Eun-Hye;Cho, Young-Hoon;Lee, Hee-Man;Lee, Jeong Bae;Kim, Eung-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1404-1405
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    • 2015
  • 최근 들어 3D프린터의 특허권이 만료됨에 따라 3D프린터 연구 및 생산이 활발히 이루어지고 있으며, 저렴한 개인용 3D프린터의 보급으로 남녀노소 누구나 활용할 수 있게 되었다. 하지만 3D프린터를 이용하여 자신이 원하는 제품을 출력하기란 쉽지 않다. 버튼만 누르면 되는 인쇄물 프린터와 달리 3D프린터의 데이터를 제작하기 위해서는 3D 모델링 제작 툴이나 3D 스캐너를 이용해야한다. 이러한 제작 프로그램이나 제품은 개인이 사용하기에는 가격이 고가이며, 사용 방법을 익히는데 많은 시간과 노력이 필요하다. 이에 본 논문에서는 3D 데이터의 획득에 있어 쉽고 간편한 3D 데이터 변환 제작 알고리즘을 이용하여 3D 프린터의 사용 편리성을 향상시킬 수 있다.

A Study on Surface Defect Detection Model of 3D Printing Bone Plate Using Deep Learning Algorithm (딥러닝 알고리즘을 이용한 3D프린팅 골절합용 판의 표면 결함 탐지 모델에 관한 연구)

  • Lee, Song Yeon;Huh, Yong Jeong
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.2
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    • pp.68-73
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    • 2022
  • In this study, we produced the surface defect detection model to automatically detect defect bone plates using a deep learning algorithm. Bone plates with a width and a length of 50 mm are most used for fracture treatment. Normal bone plates and defective bone plates were printed on the 3d printer. Normal bone plates and defective bone plates were photographed with 1,080 pixels using the webcam. The total quantity of collected images was 500. 300 images were used to learn the defect detection model. 200 images were used to test the defect detection model. The mAP(Mean Average Precision) method was used to evaluate the performance of the surface defect detection model. As the result of confirming the performance of the surface defect detection model, the detection accuracy was 96.3 %.

The feasibility of algorithm for iterative metal artifact reduction (iMAR) using customized 3D printing phantom based on the SiPM PET/CT scanner (SiPM PET/CT에서 3D 프린팅 기반 자체제작한 팬텀을 이용한 iMAR 알고리즘 유용성 평가에 관한 연구)

  • Min-Gyu Lee;Chanrok Park
    • The Korean Journal of Nuclear Medicine Technology
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    • v.28 no.1
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    • pp.35-40
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    • 2024
  • Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.

Saturation Compensating Method by Embedding Pseudo-Random Code in Wavelet Packet Based Colorization (웨이블릿 패킷 기반의 컬러화 알고리즘에서 슈도랜덤코드 삽입을 이용한 채도 보상 방법)

  • Ko, Kyung-Woo;Jang, In-Su;Kyung, Wang-Jun;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.4
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    • pp.20-27
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    • 2010
  • This paper proposes a saturation compensating method by embedding pseudo-random code information in wavelet packet based colorization algorithm. In the color-to-gray process, an input RGB image is converted into YCbCr images, and a 2-level wavelet packet transform is applied to the Y image. And then, color components of CbCr are embedded into two sub-bands including minimum amount of energy on the Y image. At this time, in order to compensate the color saturations of the recovered color image during the printing and scanning process, the maximum and minimum values of CbCr components of an original image are also embedded into the diagonal-diagonal sub-band by a form of pseudo-random code. This pseudo-random code has the maximum and minimum values of an original CbCr components, and is expressed by the number of white pixels. In the gray-to-color process, saturations of the recovered color image are compensated using the ratio of the original CbCr values to the extracted CbCr values. Through the experiments, we can confirm that the proposed method improves color saturations in the recovered color images by the comparison of color difference and PSNR values.

A study on the digitalization of 3D Pen (3D펜의 디지털화에 대한 연구)

  • Kim, Jong-Young;Jeon, Byung-Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.583-590
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    • 2021
  • This paper is a study on the digitization of an analog 3D pen. The term digital implies features such as homeostasis, transformability, combinability, reproducibility, and convenience of storage. One device that produces a combination of these digital characteristics is a 3D printer, but its industrial use is limited due to low productivity and limitations with materials and physical characteristics. In particular, improvements are required to use 3D printers, such as better user accessibility owing to expertise and skills in modeling software and printers. Complementing this fact is the 3D pen, which is excellent in portability and ease of use, but has a limitation in that it cannot be digitized. Therefore, in order to secure a digitalization capability and ease of use, and to secure the safety of printing materials that pose controversial hazards during the printing process, research problems and alternatives have been derived by combining food, and digitization was demonstrated with a newly developed 3D pen. In order to digitize the 3D pen, a sensor in a structured device detects the motion of an analog 3D pen, and this motion is converted into 3D data (X-Y-Z coordinate values) through a spatial analysis algorithm. To prove this method, the similarity was confirmed by visualization using MeshLab version 1.3.4. It is expected that this food pen can be used in youth education and senior healthcare programs in the future.

A Study on User Authentication Model Using Device Fingerprint Based on Web Standard (표준 웹 환경 디바이스 핑거프린트를 활용한 이용자 인증모델 연구)

  • Park, Sohee;Jang, Jinhyeok;Choi, Daeseon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.4
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    • pp.631-646
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    • 2020
  • The government is pursuing a policy to remove plug-ins for public and private websites to create a convenient Internet environment for users. In general, financial institution websites that provide financial services, such as banks and credit card companies, operate fraud detection system(FDS) to enhance the stability of electronic financial transactions. At this time, the installation software is used to collect and analyze the user's information. Therefore, there is a need for an alternative technology and policy that can collect user's information without installing software according to the no-plug-in policy. This paper introduces the device fingerprinting that can be used in the standard web environment and suggests a guideline to select from various techniques. We also propose a user authentication model using device fingerprints based on machine learning. In addition, we actually collected device fingerprints from Chrome and Explorer users to create a machine learning algorithm based Multi-class authentication model. As a result, the Chrome-based Authentication model showed about 85%~89% perfotmance, the Explorer-based Authentication model showed about 93%~97% performance.