• Title/Summary/Keyword: Worst case optimization

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Optimization of Approximate Modular Multiplier for R-LWE Cryptosystem (R-LWE 암호화를 위한 근사 모듈식 다항식 곱셈기 최적화)

  • Jae-Woo, Lee;Youngmin, Kim
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.736-741
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    • 2022
  • Lattice-based cryptography is the most practical post-quantum cryptography because it enjoys strong worst-case security, relatively efficient implementation, and simplicity. Ring learning with errors (R-LWE) is a public key encryption (PKE) method of lattice-based encryption (LBC), and the most important operation of R-LWE is the modular polynomial multiplication of rings. This paper proposes a method for optimizing modular multipliers based on approximate computing (AC) technology, targeting the medium-security parameter set of the R-LWE cryptosystem. First, as a simple way to implement complex logic, LUT is used to omit some of the approximate multiplication operations, and the 2's complement method is used to calculate the number of bits whose value is 1 when converting the value of the input data to binary. We propose a total of two methods to reduce the number of required adders by minimizing them. The proposed LUT-based modular multiplier reduced both speed and area by 9% compared to the existing R-LWE modular multiplier, and the modular multiplier using the 2's complement method reduced the area by 40% and improved the speed by 2%. appear. Finally, the area of the optimized modular multiplier with both of these methods applied was reduced by up to 43% compared to the previous one, and the speed was reduced by up to 10%.

Convolution-Superposition Based IMRT Plan Study for the PTV Containing the Air Region: A Prostate Cancer Case (Convolution-Superposition 알고리즘을 이용한 치료계획시스템에서 공기가 포함된 표적체적에 대한 IMRT 플랜: 전립선 케이스)

  • Kang, Sei-Kwon;Yoon, Jai-Woong;Park, Soah;Hwang, Taejin;Cheong, Kwang-Ho;Han, Taejin;Kim, Haeyoung;Lee, Me-Yeon;Kim, Kyoung Ju;Bae, Hoonsik
    • Progress in Medical Physics
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    • v.24 no.4
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    • pp.271-277
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    • 2013
  • In prostate IMRT planning, the planning target volume (PTV), extended from a clinical target volume (CTV), often contains an overlap air volume from the rectum, which poses a problem inoptimization and prescription. This study was aimed to establish a planning method for such a case. There can be three options in which volume should be considered the target during optimization process; PTV including the air volume of air density ('airOpt'), PTV including the air volume of density value one, mimicking the tissue material ('density1Opt'), and PTV excluding the air volume ('noAirOpt'). Using 10 MV photon beams, seven field IMRT plans for each target were created with the same parameter condition. For these three cases, DVHs for the PTV, bladder and the rectum were compared. Also, the dose coverage for the CTV and the shifted CTV were evaluated in which the shifted CTV was a copied and translated virtual CTV toward the rectum inside the PTV, thus occupying the initial position of the overlap air volume, simulating the worst condition for the dose coverage in the target. Among the three options, only density1Opt plan gave clinically acceptable result in terms of target coverage and maximum dose. The airOpt plan gave exceedingly higher dose and excessive dose coverage for the target volume whereas noAirOpt plan gave underdose for the shifted CTV. Therefore, for prostate IMRT plan, having an air region in the PTV, density modification of the included air to the value of one, is suggested, prior to optimization and prescription for the PTV. This idea can be equally applied to any cases including the head and neck cancer with the PTV having the overlapped air region. Further study is being under process.