• Title/Summary/Keyword: 패딩 두께

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Padded jacket patterns according to padding thickness for women in their 20s (패딩 두께에 따른 20대 여성용 패딩 재킷 패턴)

  • Lee, Hea-Seung;Suh, Mi-A;Uh, Mi-Kyung
    • The Research Journal of the Costume Culture
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    • v.21 no.5
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    • pp.755-764
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    • 2013
  • This study intends to use the basic patterns in 3oz bodice and 2oz sleeve padded jackets made for women in their 20s to research the proper ease of 2oz bodice and 2oz sleeve, 4oz bodice and 3oz sleeve padded jackets. The study also proposes a method of designing padded jacket patterns according to padding thickness. The results of this study are as follows: The 2oz bodice and 2oz sleeve padded jackets had the following sizes. The front and back bust, waist, and hip circumferences were calculated as B/4+2.5cm and B/4+3cm, W/4+2.6+3.3(D)cm and W/4+1.5+2.6(D)cm, and H/4+2.8cm and H/4+3cm, respectively. The length of the jacket was 62.4cm, and the sleeve length was calculated as 63.4cm. For the 4oz bodice and 3oz sleeve padded jackets, the front and back bust, waist, and hip circumferences were calculated as B/4+4cm and B/4+4cm, W/4+4.1+3(D)cm and W/4+2.5+3.6(D)cm, and H/4+4.3cm and H/4+4cm, respectively. The length of the jacket was 63.2cm, and the sleeve length was calculated as 64.2cm. The results of this study showed that padded jackets with thicker padding need more ease. For jackets with stitches, the decreased lengths must be added in the pattern length. The 2oz bodice and 2oz sleeve, 4oz bodice and 3oz sleeve padded jackets all scored 4 points or higher in the movement functionality assessment, thus showing outstanding movement functionality.

Texture Coding in MPEG-4 Using Modified Boundary Block Merging Technique (변형된 경제 블록 병합 기법을 이용한 MPEG-4의 텍스처 부호화)

  • 김두석;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.4B
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    • pp.725-733
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    • 2000
  • In this paper, we propose a modified boundary block merging technique for the texture coding of MPEG-4. We propose an ORP(Optimized Region Partitioning) method that partition the VOP-based reference position to minimize the number of coding blocks. The merging possibility is improved by adding +90。and -90。 Rotation merging. We propose a MRM(Multiple Rotation Merging) method which applies the rotation merging in the order of 180。, +90。and -90。. If a pair of boundary blocks has low correlation, existing BBM's padding technique is not efficient. Our padding after merging method gives better result even if it has low correlation. The proposed method showed 5 ~8(%) coding bit reduction at the same PSNR values compared to BBM method.

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Performance of Frame Distribution Schemes for MAC Controllers with the Link Aggregation Capability (통합링크기능을 가진 매체접근제어기용 프레임 분배방식의 성능분석)

  • 전우정;윤정호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.7B
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    • pp.1236-1243
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    • 2000
  • 본 논문은 LAN의 대역폭을 증가 시키기 위하여, 여러 개의 링크를 논리적인 하나의 링크처럼 동작하도록 하는 다중링크통함(link aggregation)기술에 대한 것이다. 우리는 망 구성에 따라 이 기술의 동작방식이 상이함에 착안하여, 두 가지의 새로운 프레임 분배방식을 제안하고 SIMULA를 이용한 모의실험으로 성능을 분석하였다. 먼저, LAN스위치와 스위치간에 적용 가능한 동적 프로엠 분배방식을 제안하였다. 이 방식은 특정 포트로 집중되는 프레임들을 분산시키기 위하여 가장 이용율이 낮은 링크를 동적으로 추가하는 것으로서, 링크 추가시 프레임들의 전달순서를 지킬 수 있도록 특별한 플러쉬 버퍼를 사용하였다. 모의실험 결과, 프러임간의 순서가 유지되면서도 스위치의 내부 버퍼에서의 프레임 폐기율이 기존 방식에 비해 감소됨을 확인하였다. 그리고, 단말과 단말간에 다중링크가 사용된 경우, 수신된 프레임들 간의 순서 뒤바뀜 문제에 대한 해결책으로 패딩 방법과, 태깅 방법, 프레임 분할 방식 등의 세가지으 프레임 분배방식을 제안하고 성능을 분석하였다. 이러한 세가지 방법 중에서 프레임 분할방식이 가장 성능면에서 우수함이 모의실험결과\ulcorner서 알 수 있지만, 패딘 방식도 구현관점에서 장점이 있다.

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Efficient Optical Watermark Using Multiple Phase Wrapping and Real-Valued Functions (다중위상래핑과 실수값 함수를 이용한 효율적인 광 워터마킹)

  • Cho, Kyu-Bo;Seo, Dong-Hoan;Lee, Seung-Hee;Hong, Jae-Keun
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.3
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    • pp.10-19
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    • 2009
  • In this paper, an efficient optical watermark method using multiple phase wrapping and real-valued decoding key is proposed. In the embedding process, two zero-padded original images placed in two quadrants on input plane are multiplied with two statistically independent random phase patterns and are Fourier transformed, respectively. Two encoded images are obtained by taking the real-valued data from these Fourier transformed images. And then two phase-encoded patterns, used as a hidden image and a decoding key, are generated by the use of multiple phase wrapping from each of the encoded images. A transmitted image is made from the linear superposition of the weighted hidden images and a cover image. In reconstruction process, the mirror reconstructed images can be obtained at all quadrants by the inverse-Fourier transform of the product of the transmitted image and the decoding key. Computer simulation and optical experiment are demonstrated in order to confirm the proposed method.

Joint Hierarchical Modulation and Network Coding for Asymmetric Data Rate Transmission over Multiple-Access Relay Channel (다중 접속 릴레이 채널에서 비대칭 데이터 전송을 위한 계층 변조 및 네트워크 코딩 결합 기법)

  • You, Dongho;Kim, Dong Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.747-749
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    • 2016
  • We consider a time-division multiple-access relay channel (MARC), in which two source nodes (SNs) transmit data with different data rate to a destination node (DN) with the help of a relay node (RN) using network coding (NC). However, due to its asymmetric data rate, the RN cannot combine the received bits by XOR NC. In this paper, we compare with the problem of asymmetric data rates by using zero padding and hierarchical 16QAM.

A Deep Learning-based Automatic Modulation Classification Method on SDR Platforms (SDR 플랫폼을 위한 딥러닝 기반의 무선 자동 변조 분류 기술 연구)

  • Jung-Ik, Jang;Jaehyuk, Choi;Young-Il, Yoon
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.568-576
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    • 2022
  • Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.