• 한국융합학회논문지
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• 제6권5호
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• pp.227-232
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• 2015

퍼지 선형계획법은 불확실성하에서의 문제들을 해결하는데 유용한 의사결정 모형이다. 본 연구에서는 목적함수 값이 퍼지수이고 우변 상수도 퍼지수인 융합 등식 제약식을 갖는 퍼지 선형계획법 문제를 다룬다. 연구의 목적은 퍼지 해를 정의하고 그것을 구하는 절차를 모색하는 것이다. 목적함수 값에 대한 소속 함수로 부분 선형함수를, 제약식의 소속 함수로는 사다리꼴 함수를 도입한다. 사다리꼴 함수는 구간별 선형 함수 들로 나누어 나타낼 수 있다. 따라서 모든 소속 함수들을 선형식 들로 대체함으로써 퍼지 선형계획 모형을 Zimmermann의 대칭 선형 모형으로 바꿀 수 있다. 여기에 최대-최소 기준을 적용하여 일반 선형계획법 문제를 도출해 내고, 이 문제의 최적해로부터 원 문제의 퍼지 해를 얻게 된다. 본 논문에서는 사다리꼴 소속 함수에 대해 살펴보았는데 앞으로는 오목 부분 선형함수와 같은 좀 더 일반화된 소속 함수에 대한 연구가 필요하다.

• 대한전자공학회논문지TC
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• 제47권2호
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• pp.9-17
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• 2010

최근 들어, 차세대 무선 광대역 통신 시스템의 전송 방식으로 큰 관심을 받고 있는 OFDM (Orthogonal Frequency Division Multiplexing) 시스템은 다수 반송파 전송의 특수한 형태로 볼 수 있으며 하나의 데이터열이 보다 낮은 데이터 전송률을 갖는 부반송파를 통해 전송된다. OFDM을 사용하는 중요한 이유 중 하나는 OFDM을 사용하면 주파수 선택적 페이딩이나 협대역 간섭에 대한 강건함이 증가하기 때문이다. 하지만 출력 신호의 크기가 Rayleigh 분포를 갖기 때문에 무선 통신 환경에서 SSPA (Solid State Power Amplifier)와 같은 고출력 증폭기 (High Power Amplifier; HPA)의 비선형 특성으로 인하여 단일 반송파 전송 방식보다 심각한 비선형 왜곡이 발생하게 된다. 본 논문에서는 OFDM 신호의 높은 PAPR (Peak-to-Average Power Ratio)과 HPA의 비선형성에 의한 신호의 왜곡과 스펙트럼의 확산을 방지하기 위해 canonical piecewise-linear (PWL) 모델 기반의 디지털 사전왜곡기를 제안한다. 제안된 사전왜곡기의 성능평가를 위해 AWGN (Additive White Gaussian Noise) 채널 하에서 QPSK, 16-QAM, 64-QAM 변조 방식을 이용하고, 1024-point FFT/IFFT로 구현된 OFDM 시스템에 대한 모의실험을 실시한 결과, 비트오율과 비선형성 개선측면에서 우수한 성능을 나타내었다.

• 전자공학회논문지CI
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• 제49권1호
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• pp.16-22
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• 2012

본 논문에서는 알츠하이머병이 유도된 형질전환 마우스로부터 획득한 혈소판 라만 스펙트럼의 분석을 위해 가우시안 모델을 이용한 커브 피팅으로 기준선을 추정하고 보정하는 방법을 제안하였다. 측정된 라만 스펙트럼은 의미 있는 정보와 불필요한 노이즈 성분인 기준선과 가산 노이즈를 포함하고 있다. 스펙트럼의 효율적인 분석을 위해 노이즈를 포함하고 있는 스펙트럼을 몇 개의 피크를 포함하는 영역으로 분할하고 각 로컬 영역의 스펙트럼을 가우시안 모델을 이용한 커브 피팅으로 모델링한다. 가산 노이즈는 원 스펙트럼을 이 델로 대체하는 과정에서 명백하게 제거된다. 피팅된 모델의 로컬 최저점을 linear, piecewise cubic Hermite, cubic spline 알고리즘으로 보간하고 기준선을 보정한다. 기준선을 보정한 피팅 모델은 PCA(principal component analysis) 방법을 이용하여 특징을 추출하고 SVM(support vector machine)과 MAP(maximum $a$ posteriori probability) 분류 방법으로 성능 비교 실험을 하였다. 실험 결과에 따르면 linear 보간법이 모든 주성분 수에 대한 분류율의 평균에서 우세하였고 특히 piecewise cubic Hermite 보간법은 주성분의 수가 5개인 경우에서 SVM 분류율이 약 97.3%로 가장 좋은 성능을 보였다. 또한 이전의 연구 결과와 비교를 통해 제안한 기준선 보정 방법이 혈소판 라만 스펙트럼의 분석에 효과적으로 적용될 수 있음을 확인하였다.

• ETRI Journal
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• 제30권1호
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• pp.170-172
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• 2008

A substitution box (S-box) plays a central role in cryptographic algorithms. In this paper, an efficient method for designing S-boxes based on chaotic maps is proposed. The proposed method is based on the mixing property of piecewise linear chaotic maps. The S-box so constructed has very low differential and linear approximation probabilities. The proposed S-box is more secure against differential and linear cryptanalysis compared to recently proposed chaotic S-boxes.

• ETRI Journal
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• 제42권4호
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• pp.619-632
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• 2020

Highly dispersive S-boxes are desirable in cryptosystems as nonlinear confusion sublayers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information in a cryptosystem appearing as a high DP during differential cryptanalysis of an S-box is minimized. While mapping from the chaotic trajectory to integer domain, a randomness test is performed that justifies the nonlinear behavior of the highly dispersive and nonlinear chaotic S-box. The proposed scheme is vetted using well-established cryptographic performance criteria. The proposed S-box meets the cryptographic performance criteria and further minimizes the differential propagation justified by the low DP value. The suitability of the proposed S-box is also tested using an image encryption algorithm. Results show that the proposed S-box as a confusion component entails a high level of security and improves resistance against all known attacks.

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.353-359
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• 2009

This paper proposes a novel technique for calculating the security costs that properly includes ramping constraints in the operation of a deregulated power system. The ramping process is modeled by a piecewise linear function with certain assumptions. During this process, a ramping cost is incurred if the permissible limits are exceeded. The optimal production costs of the power producers are calculated with the ramping cost included, considering a time horizon with N-1 contingency cases using contingency constrained optimal power flow (CCOPF), which is solved by the primal-dual interior point method (PDIPM). A contingency analysis is also performed taking into account the severity index of transmission line outages and its sensitivity analysis. The results from an illustrative case study based on the IEEE 30-bus system are analyzed. One attractive feature of the proposed approach is that an optimal solution is more realistic than the conventional approach because it satisfies physical constraints, such as the ramping constraint.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.200-220
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• 2016

Orthogonal frequency division multiplexing (OFDM) signals suffer from the problem of large peak-to-average power ratio (PAPR) which complicates the design of the analog front-end of the system. Companding is a well-known PAPR reduction technique that reduces the PAPR by transforming the signal amplitude using a deterministic function. In this paper, a novel piecewise linear companding transform is proposed. The design criteria for the proposed transform is developed by investigating the relationships between the compander and decompander's profile and parameters with the system's performance metrics. Using analysis and simulations, we relate the companding parameters with the bit error rate (BER), out-of-band interference (OBI), amount of companding noise, computational complexity and average power. Based on a set of criteria developed thereof, we formulate the design of the proposed transform. The main aim is to preserve the signal's attributes as much as possible for a predetermined amount of PAPR reduction. Simulations are carried out to evaluate and compare the proposed scheme with the existing companding transforms to demonstrate the enhancement in PAPR, BER and OBI performances.

• Advances in Computational Design
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• 제5권4호
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• pp.397-416
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• 2020

Functionally graded material (FGM) illustrates a novel class of composites that consists of a graded pattern of material composition. FGM is engineered to have a continuously varying spatial composition profile. Current work focused on buckling analysis of beam made of stepwise linear and quadratic graded material in axial direction subjected to axial span-load with piecewise function and rested on shear layer based on classical beam theory. The various boundary and natural conditions including simply supported (S-S), pinned - clamped (P-C), axial hinge - pinned (AH-P), axial hinge - clamped (AH-C), pinned - shear hinge (P-SHH), pinned - shear force released (P-SHR), axial hinge - shear force released (AH-SHR) and axial hinge - shear hinge (AH-SHH) are considered. To the best of the author's knowledge, buckling behavior of this kind of Euler-Bernoulli beams has not been studied yet. The equilibrium differential equation is derived by minimizing total potential energy via variational calculus and solved analytically. The boundary conditions, natural conditions and deformation continuity at concentrated load insertion point are expressed in matrix form and nontrivial solution is employed to calculate first buckling loads and corresponding mode shapes. By increasing truncation order, the relative error reduction and convergence of solution are observed. Fast convergence and good compatibility with various conditions are advantages of the proposed method. A MATLAB code is provided in appendix to employ the numerical procedure based on proposed method.

• 산업경영시스템학회지
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• 제44권1호
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.