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Comparative study on mode-identification algorithms using a phased-array system in a rectangular duct

JOURNAL OF SOUND AND VIBRATION 2015年 347卷 27-45页

作者： Suzuki, Takao Day, Benjamin J. Boeing Co Acoust & Fluid Mech MC OR JF Seattle WA 98124 USA

To identify multiple acoustic duct modes, conventional beam-forming, CLEAN as well as L-2 (i.e. pseudo-inverse) and L-1 generalized-inverse beam-forming are applied to phased-array pressure data A tone signal of a prescribed mode or broadband signal is generated upstream of a curved rectangular duct, and acoustic fields formed in both upstream and downstream stations of the test section are measured with identical wall mounted microphone arrays. Sound power distributions of several horizontal and vertical modes including upstream- and downstream propagating waves can be identified with phased array techniques, and the results are compared among the four approaches. The comparisons using synthetic data demonstrate that the L-2 generalized inverse algorithm can sufficiently suppress undesirable noise levels and detect amplitude distributions accurately in over determined cases (i.e. the number of microphones is more than the number of cut on modes) with minimum computational cost. As the number of cut on modes exceeds the number of microphones (i.e. under-determined problems), the L-1 algorithm is necessary to retain better accuracy. The comparison using Lest data acquired in the curved duct Lest rig (CDTR) at NASA Langley Research Center suggests that the L-1/L-2 generalized-inverse approach as well as CLEAN can improve the dynamic range of the detected mode by as much as 10 dB relative to conventional beam-forming even with mean flow of M=05. (C) 2015 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

关键词： OPTICAL phased arrays MICROPHONE computer algorithms ACOUSTIC field SIGNAL processing

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Application of Two-Dimensional Predictive Functional Control in Injection Molding

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2015年第41期54卷 10088-10102页

作者： Yang, Bo Xu, Zuhua Yang, Yi Gao, Furong Zhejiang Univ Coll Control Sci & Engn Natl Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Kunda Mold Shen Zhen Co Ltd Fuda Intelligent Syst Shenzhen 518129 Peoples R China Hong Kong Univ Sci & Technol Dept Chem & Biomol Engn Hong Kong Hong Kong Peoples R China

A batch process can be viewed as a two-dimensional (2D) system with dynamics in both time and batch directions. To tackle these 2D dynamics, many control algorithms have been proposed by combining iterative learning control (TLC) with high-performance continuous control algorithms under a 2D framework. However, these algorithms require large computational load and memory, which are often demanding for the software and hardware of the controllers in several fast batch processes. In this paper, a 2D predictive functional control algorithm that combines ILC with predictive functional control (PFC) is proposed. Owing to the compactness and effectiveness of PFC, the proposed control algorithm can reduce the required computational load and memory. Other than the general form of the control law, two concise and practical forms are provided as well. The proposed control scheme is tested through simulations and implementation in an injection molding process, which is a typical fast batch process. Results confirm the good performance of the proposed control algorithm.

关键词： Batch processing predictive functional control Injection molding International Labour Conference Controllers compactness Power factor correction computer algorithms

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Opposition-Based Improved PSO for Optimal Reactive Power Dispatch and Voltage Control

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-8页

作者： Cao, Shengrang Ding, Xiaoqun Wang, Qingyan Chen, Bingyan Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Jiangsu Peoples R China Jiangsu Union Tech Inst Nanjing Branch Nanjing 210019 Jiangsu Peoples R China Hohai Univ Nantong Inst Marine & Offshore Engn Nantong 226000 Peoples R China Jiangsu Prov Key Lab Environm Engn Nanjing 210000 Jiangsu Peoples R China

An opposition-based improved particle swarm optimization algorithm (OIPSO) is presented for solving multiobjective reactive power optimization problem. OIPSO uses the opposition learning to improve search efficiency, adopts inertia weight factors to balance global and local exploration, and takes crossover and mutation and neighborhood model strategy to enhance population diversity. Then, a new multiobjective model is built, which includes system network loss, voltage dissatisfaction, and switching operation. Based on the market cost prices, objective functions are converted to least-cost model. In modeling process, switching operation cost is described according to the life cycle cost of transformer, and voltage dissatisfaction penalty is developed considering different voltage quality requirements of customers. The experiment is done on the new mathematical model. Through the simulation of IEEE 30-, 118-bus power systems, the results prove that OIPSO is more efficient to solve reactive power optimization problems and the model is more accurate to reflect the real power system operation.

关键词： PARTICLE swarm optimization REACTIVE power control (Electrical engineering) VOLTAGE control computer algorithms PROBLEM solving COST analysis

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Sub-logarithmic distributed algorithms for metric facility location

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DISTRIBUTED COMPUTING 2015年第5期28卷 351-374页

作者： Hegeman, James W. Pemmaraju, Sriram V. Univ Iowa Dept Comp Sci Iowa City IA 52242 USA

The facility location problem consists of a set of facilities , a set of clients , an opening cost associated with each facility , and a connection cost between each facility and client . The goal is to find a subset of facilities to open, and to connect each client to an open facility, so as to minimize the total facility opening costs plus connection costs. We consider distributed versions of facility location in which the underlying network is either a clique, in which each node is both a client and a facility (and ), or a complete bipartite network, with forming the bipartition. This paper presents the first expected-sub-logarithmic-round distributed -approximation algorithms in the model for the metric facility location problem. We present our approach first for a clique network, and then extend it to a bipartite network. Our algorithms have expected running times of rounds, where , and where for a clique network and for a bipartite network (These results were first published in ICALP 2012 and DISC 2013). In order to obtain these results, our paper makes four main technical contributions. First, we show a new lower bound for metric facility location, extending the lower bound of Bdoiu et al. (ICALP 2005) that applies only to the special case of uniform facility opening costs. Next, we demonstrate a reduction of the distributed metric facility location problem to the problem of computing an -ruling set of an appropriate spanning subgraph. Third, we provide an expected-sub-logarithmic-round algorithm for computing a -ruling set in a spanning subgraph of a clique. Finally, we present a new technique based on probabilistic hashing to solve a problem of information dissemination on bipartite networks.

关键词： DISTRIBUTED computing RESEARCH computer algorithms BANDWIDTH research BIPARTITE graphs LOCATION problems (Programming)

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A Nonlinear Goal Programming Model for University Admission Capacity Planning with Modified Differential Evolution Algorithm

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-13页

作者： El-Quliti, Said Ali Ragab, Abdul Hamid Mohamed Abdelaal, Reda Mohamed, Ali Wagdy Mashat, Abdulfattah Suliman Noaman, Amin Yousef Altalhi, Abdulrahman Helal King Abdulaziz Univ Fac Engn Ind Engn Dept Jeddah 21589 Saudi Arabia King Abdulaziz Univ Informat Syst Dept Fac Comp & Informat Technol Jeddah 21589 Saudi Arabia Univ Jeddah Dept Stat Fac Sci Jeddah 21589 Saudi Arabia King Abdulaziz Univ Deanship Admiss & Registrat Jeddah 21589 Saudi Arabia King Abdulaziz Univ Comp Sci Dept Fac Comp & Informat Technol Jeddah 21589 Saudi Arabia King Abdulaziz Univ Informat Technol Dept Fac Comp & Informat Technol Jeddah 21589 Saudi Arabia

This paper proposes a nonlinear Goal Programming Model (GPM) for solving the problem of admission capacity planning in academic universities. Many factors of university admission capacity planning have been taken into consideration among which are number of admitted students in the past years, total population in the country, number of graduates from secondary schools, desired ratios of specific specialties, faculty-to-students ratio, and the past number of graduates. The proposed model is general and has been tested at King Abdulaziz University (KAU) in the Kingdom of Saudi Arabia, where the work aims to achieve the key objectives of a five-year development plan in addition to a 25-year future plan (AAFAQ) for universities education in the Kingdom. Based on the results of this test, the proposed GPM with a modified differential evolution algorithm has approved an ability to solve general admission capacity planning problem in terms of high quality, rapid convergence speed, efficiency, and robustness.

关键词： NONLINEAR systems GOAL programming (Mathematics) UNIVERSITY & college admission CAPACITY requirements planning DIFFERENTIAL evolution (computer science) computer algorithms

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Interference-constrained coverage algorithms in the protocol and SINR models

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WIRELESS NETWORKS 2015年第4期21卷 1391-1409页

作者： Kapadia, Prateek Damani, Om Kumar, Animesh IIT Dept Comp Sci & Engn Bombay Maharashtra India IIT Dept Elect Engn Bombay Maharashtra India

A wireless network's design must include the optimization of the area of coverage of its wireless transmitters-mobile and base stations in cellular networks, wireless access points in WLANs, or nodes on a transmit schedule in a wireless ad-hoc network. Furthermore, with increasing densities of wireless network deployments, paucity of spectrum, and new developments like whitespace devices and cognitive networks, there is a need to study the computational efficiency of managing interference and optimizing coverage. This work presents new algorithms for computing and optimizing interference-limited coverage of wireless networks under protocol and Signal-to-Interference-and-Noise Ratio (SINR) models. For the protocol model we demonstrate lower bounds on computation of the coverage area for an transmitter topology. We first show that any offline computation has a run-time of , and any dynamic update takes time to locate transmitters whose coverage is modified and time to update affected coverage regions. We then demonstrate an extension of an offline algorithm to a dynamic algorithm that achieves the lower bound. For coverage in the SINR model, we demonstrate the difficulty of geometric direct computation, and report a flexible coverage area estimation method. We then propose a Random Hill Climbing method for optimizing the coverage area measure, and demonstrate the efficacy of this method by experimental comparison with the Nelder-Mead and exhaustive search optimization methods.

关键词： Wireless coverage computer algorithms Computational geometry Random sampling

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Planning Tunnel Construction Using Markov Chain Monte Carlo (MCMC)

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-8页

作者： Vargas, Juan P. Koppe, Jair C. Perez, Sebastian Hurtado, Juan P. Univ Santiago Chile Dept Ingn Minas Santiago Chile Univ Fed Rio Grande do Sul Dept Engn Minas Porto Alegre RS Brazil

Tunnels, drifts, drives, and other types of underground excavation are very common in mining as well as in the construction of roads, railways, dams, and other civil engineering projects. Planning is essential to the success of tunnel excavation, and construction time is one of the most important factors to be taken into account. This paper proposes a simulation algorithm based on a stochastic numerical method, the Markov chain Monte Carlo method, that can provide the best estimate of the opening excavation times for the classic method of drilling and blasting. Taking account of technical considerations that affect the tunnel excavation cycle, the simulation is developed through a computational algorithm. Using the Markov chain Monte Carlo method, the unit operations involved in the underground excavation cycle are identified and assigned probability distributions that, with random number input, make it possible to simulate the total excavation time. The results obtained with this method are compared with a real case of tunneling excavation. By incorporating variability in the planning, it is possible to determine with greater certainty the ranges over which the execution times of the unit operations fluctuate. In addition, the financial risks associated with planning errors can be reduced and the exploitation of resources maximized.

关键词： TUNNEL design & construction MARKOV chain Monte Carlo DATA mining computer algorithms SIMULATION methods & models

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The current state of art in program obfuscations: definitions of obfuscation security

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PROGRAMMING AND computer SOFTWARE 2015年第6期41卷 361-372页

作者： Varnovskiy, N. P. Zakharov, V. A. Kuzyurin, N. N. Shokurov, A. V. Moscow MV Lomonosov State Univ Informat Secur Inst Moscow 119234 Russia Natl Res Univ Higher Sch Econ Moscow 101000 Russia Russian Acad Sci Inst Syst Programming Moscow 109004 Russia

Program obfuscation is a semantic-preserving transformation aimed at bringing a program into a form that impedes understanding of its algorithm and data structures or prevents extracting certain valuable information from the text of the program. Since obfuscation may find wide use in computer security, information hiding and cryptography, security requirements to program obfuscators have become a major focus of interest in the theory of software obfuscation starting from the pioneering works in this field. In this paper we give a survey of various definitions of obfuscation security and basic results that establish possibility or impossibility of secure program obfuscation under certain cryptographic assumptions.

关键词： computer software computer security computer programming CRYPTOGRAPHY computer algorithms

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RBF neural network based second-order sliding mode guidance for Mars entry under uncertainties

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AEROSPACE SCIENCE AND TECHNOLOGY 2015年第Jun.期43卷 226-235页

作者： Li, Shuang Jiang, Xiuqiang Nanjing Univ Aeronaut & Astronaut Coll Astronaut Nanjing 210016 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Space New Technol Lab Nanjing 210016 Jiangsu Peoples R China

There are usually larger uncertainties in the atmosphere density of Mars and the aerodynamic parameters of entry vehicles, which inevitably degrades the performance of entry guidance and control algorithms. This paper studies the robust Mars atmospheric entry guidance design based on the radial basis function neural network (RBF-NN) and second-order sliding mode control (SOSMC). First, second-order sliding mode guidance (SOSMG) law is developed to robustly follow the pre-designed nominal trajectory under larger uncertainties and effectively reduce the longitudinal error. Then, the RBF neural network is included into the second-order sliding surface guidance law to online approximate the bounded uncertain terms and further improve the guidance accuracy. Finally, the effectiveness of the guidance algorithm proposed in this paper is confirmed by Monte Carlo simulations. (C) 2015 Elsevier Masson SAS. All rights reserved.

关键词： Uncertainty Sliding mode Neural network aerodynamic parameters Mars computer algorithms Guidance accuracy of guidance Radial basis function networks entry

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Classification of multilevel converters with a modular reduced structure: implementing a prominent 31-level 5 kVA class B converter

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IET POWER ELECTRONICS 2015年第1期8卷 20-32页

作者： Mojibian, Mohammad Jafar Bina, Mohammad Tavakoli KN Toosi Univ Technol Elect Fac Tehran Iran

Multilevel converters are capable of generating AC voltages with low-total harmonic distortion, applicable to power system applications such as penetration of renewable sources in an active network. These types of topologies may require large number of switches and power supplies, having complex structures along with complicated control algorithms. Recently, a branch of multilevel converters is emerged, in which their 'reduced structure' topologies use lower number of devices compared to the available topologies. This study concentrates on classification of the branched 'multilevel converters' with a 'reduced structure' (MCRS) that lowers the number of semiconductor switches as well as their gate-drivers. Then, these classified structures are compared in terms of their number of power supplies and switches, the number of gate-drivers, breaking voltages of the switches and so on. This will pave the way for the introduction of a structure named B2 in the defined class B among the available MCRS topologies with the lowest number of power electronic devices;this structure is obtained by modifying the structure A2 in the defined class A. Moreover, design and simulation of a 31-level converter is analysed under optimal number of DC sources for all named structures. A laboratory prototype was implemented that verifies operation and performance of the suggested structure B2.

关键词： complex structure multistage converter multilayers Electric Power Source Switches Class B MCRS Converters computer algorithms

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