353 research outputs found

    Distributed Contingency Analysis over Wide Area Network among Dispatch Centers

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    Traditionally, a regional dispatch center uses the equivalent method to deal with external grids, which fails to reflect the interactions among regions. This paper proposes a distributed N-1 contingency analysis (DCA) solution, where dispatch centers join a coordinated computation using their private data and computing resources. A distributed screening method is presented to determine the Critical Contingency Set (DCCS) in DCA. Then, the distributed power flow is formulated as a set of boundary equations, which is solved by a Jacobi-Free Newton-GMRES (JFNG) method. During solving the distributed power flow, only boundary conditions are exchanged. Acceleration techniques are also introduced, including reusing preconditioners and optimal resource scheduling during parallel processing of multiple contingencies. The proposed method is implemented on a real EMS platform, where tests using the Southwest Regional Grid of China are carried out to validate its feasibility.Comment: 5 pages, 6 figures, 2017 IEEE PES General Meetin

    Sparse Array Signal Processing

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    This dissertation details three approaches for direction-of-arrival (DOA) estimation or beamforming in array signal processing from the perspective of sparsity. In the first part of this dissertation, we consider sparse array beamformer design based on the alternating direction method of multipliers (ADMM); in the second part of this dissertation, the problem of joint DOA estimation and distorted sensor detection is investigated; and off-grid DOA estimation is studied in the last part of this dissertation. In the first part of this thesis, we devise a sparse array design algorithm for adaptive beamforming. Our strategy is based on finding a sparse beamformer weight to maximize the output signal-to-interference-plus-noise ratio (SINR). The proposed method utilizes ADMM, and admits closed-form solutions at each ADMM iteration. The algorithm convergence properties are analyzed by showing the monotonicity and boundedness of the augmented Lagrangian function. In addition, we prove that the proposed algorithm converges to the set of Karush-Kuhn-Tucker stationary points. Numerical results exhibit its excellent performance, which is comparable to that of the exhaustive search approach, slightly better than those of the state-of-the-art solvers, and significantly outperforms several other sparse array design strategies, in terms of output SINR. Moreover, the proposed ADMM algorithm outperforms its competitors, in terms of computational cost. Distorted sensors could occur randomly and may lead to the breakdown of a sensor array system. In the second part of this thesis, we consider an array model in which a small number of sensors are distorted by unknown sensor gain and phase errors. With such an array model, the problem of joint DOA estimation and distorted sensor detection is formulated under the framework of low-rank and row-sparse decomposition. We derive an iteratively reweighted least squares (IRLS) algorithm to solve the resulting problem. The convergence property of the IRLS algorithm is analyzed by means of the monotonicity and boundedness of the objective function. Extensive simulations are conducted in view of parameter selection, convergence speed, computational complexity, and performance of DOA estimation as well as distorted sensor detection. Even though the IRLS algorithm is slightly worse than the ADMM in detecting the distorted sensors, the results show that our approach outperforms several state-of-the-art techniques in terms of convergence speed, computational cost, and DOA estimation performance. In the last part of this thesis, the problem of off-grid DOA estimation is investigated. We develop a method to jointly estimate the closest spatial frequency (the sine of DOA) grids, and the gaps between the estimated grids and the corresponding frequencies. By using a second-order Taylor approximation, the data model under the framework of joint-sparse representation is formulated. We point out an important property of the signals of interest in the model, namely the proportionality relationship. The proportionality relationship is empirically demonstrated to be useful in the sense that it increases the probability of the mixing matrix satisfying the block restricted isometry property. Simulation examples demonstrate the effectiveness and superiority of the proposed method against several state-of-the-art grid-based approaches

    Sparse Array Beamformer Design via ADMM

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    In this paper, we devise a sparse array design algorithm for adaptive beamforming. Our strategy is based on finding a sparse beamformer weight to maximize the output signal-to-interference-plus-noise ratio (SINR). The proposed method utilizes the alternating direction method of multipliers (ADMM), and admits closed-form solutions at each ADMM iteration. The algorithm convergence properties are analyzed by showing the monotonicity and boundedness of the augmented Lagrangian function. In addition, we prove that the proposed algorithm converges to the set of Karush-Kuhn-Tucker stationary points. Numerical results exhibit its excellent performance, which is comparable to that of the exhaustive search approach, slightly better than those of the state-of-the-art solvers, including the semidefinite relaxation (SDR), its variant (SDR-V), and the successive convex approximation (SCA) approaches, and significantly outperforms several other sparse array design strategies, in terms of output SINR. Moreover, the proposed ADMM algorithm outperforms the SDR, SDR-V, and SCA methods, in terms of computational complexity.Comment: Accepted by IEEE Transactions on Signal Processin

    Convergence Analysis of Consensus-ADMM for General QCQP

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    We analyze the convergence properties of the consensus-alternating direction method of multipliers (ADMM) for solving general quadratically constrained quadratic programs. We prove that the augmented Lagrangian function value is monotonically non-increasing as long as the augmented Lagrangian parameter is chosen to be sufficiently large. Simulation results show that the augmented Lagrangian function is bounded from below when the matrix in the quadratic term of the objective function is positive definite. In such a case, the consensus-ADMM is convergent.Comment: 13 pages, 5 figure

    Sparse Array Design for Dual-Function Radar-Communications System

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    The problem of sparse array design for dual-function radar-communications is investigated. Our goal is to design a sparse array which can simultaneously shape desired beam responses and serve multiple downlink users with the required signal-to-interference-plus-noise ratio levels. Besides, we also take into account the limitation of the radiated power by each antenna. The problem is formulated as a quadratically constrained quadratic program with a joint-sparsity-promoting regularization, which is NP-hard. The resulting problem is solved by the consensus alternating direction method of multipliers, which enjoys parallel implementation. Numerical simulations exhibit the effectiveness and superiority of the proposed method which leads to a more power-efficient solution.Comment: Accepted by IEEE Communications Letter

    Interleukin-10-819 promoter polymorphism in association with gastric cancer risk

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    <p>Abstract</p> <p>Background</p> <p>Potential functional allele T/C single nucleotide polymorphism (SNP) of Interleukin 10 (IL-10) promoter -819 (rs1800871) has been implicated in gastric cancer risk. We aimed to explore the role of T/C SNP of IL-10 -819 in the susceptibility to gastric cancer through a systematic review and meta-analysis.</p> <p>Methods</p> <p>Each initially included article was scored for quality appraisal. Desirable data were extracted and registered into databases. 11 studies were ultimately eligible for the meta-analysis of IL-10 -819 T/C SNP. We adopted the most probably appropriate genetic model (recessive model). Potential sources of heterogeneity were sought out via subgroup and sensitivity analyses, and publication biases were estimated.</p> <p>Results</p> <p>IL-10 -819 TT genotype is associated with the overall reduced gastric cancer risk among Asians and even apparently observed among high quality subgroup Asians. IL-10-819 TT genotype is not statistically associated with the overall reduced gastric cancer susceptibility in persons with <it>H. pylori </it>infection compared with controls without <it>H. pylori </it>infection. IL-10 -819 TT genotype is reversely associated with diffuse-subtype risk but not in intestinal-subtype risk. IL-10 -819 TT genotype is not reversely associated with non-cardia or cardia subtype gastric cancer susceptibility.</p> <p>Conclusions</p> <p>IL-10 -819 TT genotype seems to be more protective from gastric cancer in Asians. Whether IL-10 -819 TT genotype may be protective from gastric cancer susceptibility in persons infected with <it>H. pylori </it>or in diffuse-subtype cancer needs further exploring in the future well-designed high quality studies among different ethnicity populations. Direct sequencing should be more used in the future.</p

    On a problem of Henning and Yeo about the transversal number of uniform linear systems whose 2-packing number is fixed

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    For r≥2r\geq2, let (P,L)(P,\mathcal{L}) be an rr-uniform linear system. The transversal number τ(P,L)\tau(P,\mathcal{L}) of (P,L)(P,\mathcal{L}) is the minimum number of points that intersect every line of (P,L)(P,\mathcal{L}). The 2-packing number ν2(P,L)\nu_2(P,\mathcal{L}) of (P,L)(P,\mathcal{L}) is the maximum number of lines such that the intersection of any three of them is empty. In [Discrete Math. 313 (2013), 959--966] Henning and Yeo posed the following question: Is it true that if (P,L)(P,\mathcal{L}) is a rr-uniform linear system then τ(P,L)≤∣P∣+∣L∣r+1\tau(P,\mathcal{L})\leq\displaystyle\frac{|P|+|\mathcal{L}|}{r+1} holds for all k≥2k\geq2?. In this paper, some results about of rr-uniform linear systems whose 2-packing number is fixed which satisfies the inequality are given

    Sustainability Entrepreneurship Supply Chain in Family Business

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    A Family business is a company whose majority shareholder is a family, and the position of manager (management) is controlled by family members and it is expected that the family descendants will follow in their footsteps later as managers. In this context, the application of the concept of sustainable supply chain management in the operation strategy of small business seems to be an important function. This supply chain also covers all three aspects of sustainable development: business, environmental, and social. The purpose of this article is to present the current state of the research in sustainable development in relation to managing the supply chain of family business, as well as the empirical findings in this area. This research supposed to analysis of the comparison of Entrepreneurial supply chain and sustainability of family business in China and Indonesia. This research done with Quantitative Method using SEM / Generalized Structured Component Analysis (GeSCA) program by visiting and interviewing with Family business China and Indonesia. The population in this study was a sample of 100 people. The sampling technique is random sampling. This research proves: 1). Leadership, Culture and Innovation have a significant effect on the Entrepreneurial supply chain in Indonesia and China; 2). Leadership and Innovation have a significant effect in Family Business Sustainability. 3). The Entrepreneurial supply chain, Culture and Innovation have a significant effect on the Sustainability of the Family Business, whereas the Leadership is not significant on the Sustainability of the Family Business in China; 4). Entrepreneurial supply chain does not mediate the influence of Leadership, Culture and Innovation on the Sustainability of Family Businesses in Indonesia; but Entrepreneurial supply chain mediates the influence of Leadership, Culture and Innovation on the Sustainability of Family Businesses in China
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