• Title/Summary/Keyword: 차분

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Comparison with SAR Patterns of Biological Objects Contacted with Coaxial Waveguide Antenna Using MUR and GPML ABCs in the FDTD Method (유한차분법에서 MUR과 GPML 흡수경계조건을 이용한 동축 도파관 안테나에 접촉된 생체의 SAR 패턴 비교)

  • 구성모;권광희;이창원;원철호;조진호
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.9 no.2
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    • pp.149-158
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    • 1998

  • The SAR patterns of biological objects contacted with coaxial waveguide antennal has been investigated, in which the biological object was modeled by a homogeneous and four-layered lossy human body. We derived the finite-difference time-domain(FDTD) algorithm and equation of MUR and generalized perfectly matched layer(GPML) ABCs in cylindrical coordination. The coupling between coaxial waveguide antenna and a biological object was analyzed by use of MUR and GPML ABCs in the FDTD method to obtain the absorbed power patterns in the media. The specific absorption rates (SAR) distribution which was corresponding to the temperature distribution was calculated in each region by use of the steady-state response in the FDTD method. The SAR patterns of the FDTD method using MUR absorbing boundary conditions(ABCs) was compared with those of the FDTD method using GPML ABCs. The comparison exhibits that the penetration depth of the SAR patterns using MUR ABCs is deeper than that of the SAR patterns using GPML ABCs because of loss in free space. However, the spread in the lateral directions of the SAR patterns using GPML ABCs is smaller than of the SAR patterns using MUR ABCs.

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A Robust Hand Recognition Method to Variations in Lighting (조명 변화에 안정적인 손 형태 인지 기술)

  • Choi, Yoo-Joo;Lee, Je-Sung;You, Hyo-Sun;Lee, Jung-Won;Cho, We-Duke
    • The KIPS Transactions:PartB
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    • v.15B no.1
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    • pp.25-36
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    • 2008

  • In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.

  • https://doi.org/10.3745/KIPSTB.2008.15-B.1.25 인용 PDF KSCI

How to Generate Lightweight S-Boxes by Using AND Gate Accumulation (AND 연산자 축적을 통한 경량 S-boxes 생성방법)

  • Jeon, Yongjin;Kim, Jongsung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.3
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    • pp.465-475
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    • 2022

  • Due to the impact of COVID-19, people are paying attention to convenience and health, and the use of IoT devices to help them is increasing. In order to embed a lightweight security element in IoT devices that need to handle sensitive information even with limited resources, the development of a lightweight S-box is essential. Until 2021, it was common to develop a lightweight 4-bit S-box by a heuristic method, and to develop an extended structure or repeat the same operation for a larger size lightweight S-box. However, in January 2022, a paper that proposed a heuristic algorithm to find an 8-bit S-box with better differential uniformity and linearity than the S-box generated with an MISTY extended structure, although non-bijective, was published [1]. The heuristic algorithm proposed in this paper generates an S-box by adding AND operations one by one. Whenever an AND operation is added, they use a method that pre-removes the S-box for which the calculated differential uniformity does not reach the desired criterion. In this paper, we improve the performance of this heuristic algorithm. By increasing the amount of pre-removal using not only differential uniformity but also other differential property, and adding a process of calculating linearity for pre-removing, it is possible to satisfy not only differential security but also linear security.

  • https://doi.org/10.13089/JKIISC.2022.32.3.465 인용 PDF KSCI HTML