• 한국전자파학회논문지
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• 제30권6호
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• pp.479-486
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• 2019

레이다는 한정된 시간내에 효과적인 임무수행을 위해 광역빔을 이용한다. 본 논문에서는 완전 디지털 능동배열레이다의 광역빔 설계에 적용 가능한 위상조정 convex 최적화 알고리즘을 제안한다. 먼저 SDR(SemiDefinite Relaxation) 개념을 적용하여 제한 조건을 완화시켜 non-convex 집합을 convex 집합으로 전환한다. 그 후 배열소자의 크기를 어느 정도 고정하고 위상만을 조정하도록 제한조건을 적용하고, 고유값 분해를 통해 획득한 고유값의 합을 최소화하도록 최적화 과정을 수행하였다. 기존 유전알고리즘 적용결과와의 비교를 통해 제안된 알고리즘이 소자의 위상값만을 이용한 광역빔 설계에 효과적임을 확인하였고, 완전 디지털 능동배열레이다를 이용하는 차기호위함/구축함에 적용할 수 있을 것으로 기대된다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.501-505
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• 1998

In this paper, an LP problem with convex polyhedral objective coefficients is treated. In the problem, the interactivities of the uncertain objective coefficients are represented by a bounded convex polyhedron (a convex polytope). We develop a computation algorithm of a maxmin achievement rate solution. To solve the problem, first, we introduce the relaxation procedure. In the algorithm, a sub-problem, a bilevel programing problem, should be solved. To solve the sub-problem, we develop a solution method based on a branch and bound method. As a result, it is shown that the problem can be solved by the repetitional use of the simplex method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2595-2618
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• 2018

In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs). Each base station (BS) has multiple users. And Eves attempt to wiretap a macrocell user (MU). To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network. Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs. We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively. Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case. Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI. Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently. Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search. While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation. In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms. Finally, simulation results validate the effectiveness and robustness of proposed scheme.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제5권2호
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• pp.137-147
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• 2001

Nonconvex Quadratic Optimization Problems (QOP) are solved approximately by SDP (semidefinite programming) relaxation and SOCP (second order cone programmming) relaxation. Nonconvex QOPs with special structures can be solved exactly by SDP and SOCP. We propose a method to formulate general nonconvex QOPs into the special form of the QOP, which can provide a way to find more accurate solutions. Numerical results are shown to illustrate advantages of the proposed method.

• 산업경영시스템학회지
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• 제30권2호
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• pp.83-88
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• 2007

본 논문에서 선형함수의 곱의 형태로 표현된 비선형 함수를 목적식 또는 제약식에 가지는 비선형 최적화 문제를 새로운 변수를 추가하여 선형 Relaxation 최적화 문제로 Reformulation 하는 기법을 소개한다. 특히, 선형함수의 곱의 형태를 가지는 비선형 함수를 포함하는 비선형 정수 최적화 문제를 선형 정수 최적화 문제로 Relaxation할 경우 두 최적화 문제의 해가 일치함을 보인다. 또한 소개된 Relaxation 기법을 응용하여, 추가되는 변수의 수를 증가시킴으로서, 보다 Tight한 Relaxation 문제를 도출하는 과정에 대하여 소개한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4484-4501
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• 2019

In this paper, we put forward a delay-aware secure maximum distance separable (MDS) coded caching scheme to resist the eavesdropping attacks for device-to-device (D2D) content sharing by combining MDS coding with distributed caching. In particular, we define the average system delay to show the potential coupling of delay-content awareness, and learn the secure constraints to ensure that randomly distributed eavesdroppers cannot obtain enough encoded packets to recover their desired contents. Accordingly, we model such a caching problem as an optimization problem to minimize the average system delay with secure constraints and simplify it to its convex relaxation. Then we develop a delay-aware secure MDS coded caching algorithm to obtain the optimal caching policy. Extensive numerical results are provided to demonstrate the excellent performance of our proposed algorithm. Compared with the random coded caching scheme, uniform coded caching scheme and popularity based coded caching scheme, our proposed scheme has 3.7%, 3.3% and 0.7% performance gains, respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.293-298
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• 2016

Document summarization is an important task in various areas where the goal is to select a few the most descriptive sentences from a given document as a succinct summary. Even without training data of human labeled summaries, there has been several interesting existing work in the literature that yields reasonable performance. In this paper, within the same unsupervised learning setup, we propose a more principled learning framework for the document summarization task. Specifically we formulate an optimization problem that expresses the requirements of both faithful preservation of the document contents and the summary length constraint. We circumvent the difficult integer programming originating from binary sentence selection via continuous relaxation and the low entropy penalization. We also suggest an efficient convex-concave optimization solver algorithm that guarantees to improve the original objective at every iteration. For several document datasets, we demonstrate that the proposed learning algorithm significantly outperforms the existing approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.565-581
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• 2019

This paper investigates the wireless powered two way relay network (WPTWRN), where two single-antenna users and one single-antenna relay firstly harvest energy from signals emitted by a multi-antenna power beacon (PB) and then two users exchange information with the help of the relay by using their harvested energies. In order to improve the energy transfer efficiency, energy beamforming at the PB is deployed. For such a network, to explore the performance limit of the presented WPTWRN, an optimization problem is formulated to obtain the achievable rate region bounds by jointly optimizing the time allocation and energy beamforming design. As the optimization problem is non-convex, it is first transformed to be a convex problem by using variable substitutions and semidefinite relaxation (SDR) and then solve it efficiently. It is proved that the proposed method achieves the global optimum. Simulation results show that the achievable rate region of the presented WPTWRN architecture outperforms that of wireless powered one way relay network architecture. Results also show that the relay location has significant impact on achievable rate region of the WPTWRN.

• Communications for Statistical Applications and Methods
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• 제30권2호
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• pp.135-147
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• 2023

Skipped median is more robust than median when outliers are not symmetrically distributed. In this work, we propose a novel algorithm to estimate the skipped median. The idea of skipped median and the new algorithm are extended to regression problem, which is called least clipped absolute deviation (LCAD). Since our proposed algorithm for nonconvex LCAD optimization makes use of convex least absolute deviation (LAD) procedure as a subroutine, regularizations developed for LAD can be directly applied, without modification, to LCAD as well. Numerical studies demonstrate that skipped median and LCAD are useful and outperform their counterparts, median and LAD, when outliers intervene asymmetrically. Some extensions of the idea for skipped median and LCAD are discussed.

• 대한기계학회논문집
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• 제19권3호
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• pp.834-845
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• 1995

An experimental study is made in a nearly two-dimensional 90.deg. curved duct to investigate the effects of interaction between streamline curvature and mean strain on turbulence. The initial shear at the entrance to the curved duct is varied by an upstream shear generator to produce five different shear conditions ; a uniform flow (UF), a positive weak shear (PW), a positive strong shear(PS), a negative weak shear (NW) and a negative strong shear(NS). With the mean field data of the case UF, variations of the momentum thickness, the shape factor and the skin friction over the convex(inner) surface and the concave (outer) surface are scrutinized quantitatively in-depth. It is found that, while the pressure loss due to curvature is insensitive to the inlet shear rates, the distributions of wall static pressure along both convex and concave surfaces are much influenced by the inlet shear rates.