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检索条件"主题词=Optimization Algorithms"

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Norm Approximation for Imperfect Monitors 14

Norm Approximation for Imperfect Monitors

引用

International Conference on Autonomous Agents and Multiagent Systems

作者： Natasha Alechina Mehdi Dastani Brian Logan School of Computer Science University of Nottingham Department of Information and Computing Sciences Universiteit Utrecht

ISBN: (纸本)9781634391313

In this paper, we consider the runtime monitoring of norms with imperfect monitors. A monitor is imperfect for a norm if it has insufficient observational capabilities to determine if a given execution trace of a multi-agent system complies with or violates the norm. One approach to the problem of imperfect monitors is to enhance the observational capabilities of the normative organisation. However this may be costly or in some cases impossible. Instead we show how to synthesise an approximation of an 'ideal' norm that can be perfectly monitored given a monitor, and which is optimal in the sense that any other approximation would fail to detect at least as many violations of the ideal norm. We give a logical analysis of (im)perfect monitors. We state the computational complexity of the norm approximation problem, and give an optimal algorithm for generating optimal approximations of norms given a monitor.

关键词： Norms Monitoring MONITOR Imperfect approximation optimization algorithms

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Coding Sensor Outputs for Injection Attacks Detection

Coding Sensor Outputs for Injection Attacks Detection

引用

IEEE Annual Conference on Decision and Control

作者： Fei Miao Quanyan Zhu Miroslav Pajic George J. Pappas Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA 19014 Department of Electrical and Computer Engineering New York University Brooklyn NY USA 11201

ISBN: (纸本)9781467360890

This paper considers a method of coding the sensor outputs in order to detect stealthy false data injection attacks. An intelligent attacker can design a sequence of data injection to sensors that pass the state estimator and statistical fault detector, based on knowledge of the system parameters. To stay undetected, the injected data should increase the state estimation errors while keep the estimation residues in a small range. We employ a coding matrix to the original sensor outputs to increase the estimation residues, such that the alarm will be triggered by the detector even under intelligent data injection attacks. This is a low cost method compared with encryption over sensor communication networks. We prove the conditions the coding matrix should satisfy under the assumption that the attacker does not know the coding matrix yet. An iterative optimization algorithm is developed to compute a feasible coding matrix, and, we show that in general, multiple feasible coding matrices exist.

关键词： State estimation Injections Sensors system parameter cryptography Alarm Output optimization algorithms Satisfaction

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A Survivability-Centered Research Agenda for Cloud Computing Supported Emergency Response and Management Systems

A Survivability-Centered Research Agenda for Cloud Computing...

引用

IEEE Aerospace Conference

作者： Zhanshan (Sam) Ma Ronald P. Neilson Liexun Yang Andrew Hess Richard Millar Computational Biology & Medical Ecology Lab State Key Lab. of Genetic Resources & Evolution KIZ Chinese Academy of Sciences BioClimatologist USDA Forest Service USDA Forest Services & Oregon State University Department of Management Sciences National Natural Science Foundation of China The Hess PHM Group Inc Department of Systems Engineering Naval Postgraduate School

ISBN: (纸本)9781479916191

Cloud computing is evolved from grid computing with a key support from the rapidly expanding virtualization technology. We argue that clouding computing is particularly suitable for supporting emergency response and management (ERM) because of some of its unique features such as rapid setup and deployment on ad hoc basis, highly flexible platforms (PaaS: Platform as a Service) and application services (SaaS: Software as a Service) with little time-space constraints. ERM is one of the seven critical national infrastructures and services mandated to protect by the 1999 US President's Executive Order (PCCIP). The paradigm of survivability and survivable network systems was a response of academia to the president's executive order. We concur that survivability should be the lifeline of any ERM, including the cloud computing supported (CCS) ERM systems. In this article, we present a research agenda that is aimed at developing a survivability-centered architecture for evolving reliable and survivable CCS-ERM systems. The research agenda suggests that biological and computational evolutions should be rich sources of biological inspirations as well as powerful optimization algorithm for designing (evolving) the ERM systems. The proposed research agenda advocates the application of three-layer survivability analysis, dynamic hybrid fault models, and extended evolutionary game theory modeling developed by Ma & Krings [Ma & Krings (2008a-e, 2011), Ma et al. (2009a), Ma (2008, 2009, 2010, 2011a,b). We use banking system survivability as an example to illustrate the proposed research agenda.

关键词： Cloud Computing Emergency Response and Management Reliability Survivability Three-Layer Survivability Analysis Extended Evolutionary Game Theory Dynamic Hybrid Fault Models Evolutionary Computing Cloud Computing survivability Legal Services Software as a service optimization algorithms executive command EMERGENCY RESPONSE Emergency Services VT Griffin

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Learning of Closed-Loop Motion Control

Learning of Closed-Loop Motion Control

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Farbod Farshidian Michael Neunert Jonas Buchli Agile & Dexterous Robotics Lab at the Institute of Robotics and Intelligent Systems ETH Zurich Switzerland

ISBN: (纸本)9781479969357

Learning motion control as a unified process of designing the reference trajectory and the controller is one of the most challenging problems in robotics. The complexity of the problem prevents most of the existing optimization algorithms from giving satisfactory results. While model-based algorithms like iterative linear-quadratic-Gaussian (iLQG) can be used to design a suitable controller for the motion control, their performance is strongly limited by the model accuracy. An inaccurate model may lead to degraded performance of the controller on the physical system. Although using machine learning approaches to learn the motion control on real systems have been proven to be effective, their performance depends on good initialization. To address these issues, this paper introduces a two-step algorithm which combines the proven performance of a model-based controller with a model-free method for compensating for model inaccuracy. The first step optimizes the problem using iLQG. Then, in the second step this controller is used to initialize the policy for our PI~2-01 reinforcement learning algorithm. This algorithm is a derivation of the PI~2 algorithm enabling more stable and faster convergence. The performance of this method is demonstrated both in simulation and experimental results.

关键词： Motor Control Controllers optimization algorithms degraded performance Learning initialization

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Cost Allocation Strategies for Wide-Area Control of Power Systems Using Nash Bargaining Solution

Cost Allocation Strategies for Wide-Area Control of Power Sy...

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IEEE Annual Conference on Decision and Control

作者： Feier Lian Alexandra Duel-Hallen Aranya Chakrabortty Electrical & Computer Engineering North Carolina State University

ISBN: (纸本)9781467360890

In this paper we present a novel game-theoretic strategy that guarantees fair cost allocation incurred by communication links in wide-area control for electric power systems. The underlying transmission network topology results in vastly diverse requirements for inter-area feedback for operating areas owned by different utility companies. Thus, it is unfair to divide the total communication cost equally among all companies. Our objective is to quantify these requirements and incorporate them into a fair cost distribution scheme. We formulate the wide-area control problem as a state-feedback based LQR minimization problem and cast it as a cooperative game with companies acting as game-players. We first apply sparsity-promoting optimization algorithms to construct the feedback gain matrix such that its off-diagonal blocks that characterize the inter-area feedback are as sparse as possible under a desired energy constraint. Assigning a fixed cost to every non-zero element in these off-diagonal blocks, we apply the Nash Bargaining Solution (NBS) to fairly allocate the total cost among the various game-players. Resulting insights into the wide-area communication requirements for different areas over a range of energy constraints are discussed.

关键词： Cost Allocation Power system control power systems Companies Total Communication Bargaining information matrix optimization algorithms off-diagonal Total Costs

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A Fast Adaptive Guided Filtering Algorithm for Light Field Depth Interpolation

A Fast Adaptive Guided Filtering Algorithm for Light Field D...

引用

IEEE International Symposium on Circuits and Systems

作者： Jie Chen Lap-Pui Chau Nanyang Technological University Singapore 639798

ISBN: (纸本)9781479934331

Light field camera provides 4D information of the light rays, from which the scene depth information can be inferred. The disparity/depth maps calculated from light field data are always noisy with missing and false entries in homogeneous regions or areas where view-dependant effects are present. In this paper we proposed an adaptive guided filtering (AGF) algorithm to get an optimized output disparity/depth map. A guidance image is used to provide the image contour and texture information, the filter is able to preserve the disparity edges, smooth the regions without influence of the image texture, and reject the data entries with low confidence during coefficients regression. Experiment shows AGF is much faster in implementation as compared to other variational or hierarchical based optimization algorithms, and produces competitive visual results.

关键词： AGF light regions ANGPTL6 gene Light image profile Light fields image texture data entry Filtering algorithms optimization algorithms

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Nonlinear optimization Technique for the Homogenization of Metamaterials from Scattering Parameters

Nonlinear Optimization Technique for the Homogenization of M...

引用

7th International Congress on Advanced Electromagnetic Materials in Microwaves and Optics (METAMATERIALS)

作者： Kallos, Efthvmios Kallos, Georgios Palikaras, George Yannopapasi, Vassilios Univ Patras Dept Mat Sci GR-26504 Patras Greece BT Technol Serv & Operat Ipswich Suffolk England Metamat Technol Inc Dartmouth NS B2Y 4M9 Canada

ISBN: (纸本)9781479912322

We propose a novel numerical method for extracting the effective medium parameters of metamaterial structures. The reference scattering parameters of a metamaterial structure are provided as the target goal of a nonlinear optimization algorithm. The algorithm internally executes electromagnetic simulations of a homogeneous medium for identical excitations, and varies the relative permittivity and permeability values until the scattering parameters of that medium match the reference scattering values. A specific example for homogenizing a row of silver nanorods in visible wavelengths is presented, which highlights the limitations of relying solely on the scattering parameters.

关键词： scattering parameters left-handed materials homogenization Visible Wavelengths inhomogeneous media Numerical methods Dielectric constant optimization algorithms

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Performance optimization for Distributed Intra-Node-Parallel Streaming Systems

Performance Optimization for Distributed Intra-Node-Parallel...

引用

29th IEEE International Conference on Data Engineering (ICDE)

作者： Sax, Matthias J. Castellanos, Malu Chen, Qiming Hsu, Meichun Humboldt Univ Databases & Informat Syst Grp Frankfurt Germany

ISBN: (纸本)9781467353045;9781467353038

The performance of intra-node parallel dataflow programs in the context of streaming systems depends mainly on two parameters: the degree of parallelism for each node of the dataflow program as well as the batching size for each node. In the state-of-the-art systems the user has to specify those values manually. Manual tuning of both parameters is necessary in order to get good performance. However, this process is difficult and time consuming-even for experts. In this paper we introduce and optimization algorithm that optimizes both parameters automatically. We define a novel cost model for intra-node parallel dataflow programs with user-defined functions. Furthermore, we introduce different batching schemes to reduce the number of output buffers, i.e., main memory consumption. We implemented our approach on top of the open source system Storm and ran experiments with different workloads. Our results show a throughput improvement of more than one order of magnitude while the optimization time is less than a second.

关键词： data flow FIRST ORDER Streaming Line of nodes parallelism optimization algorithms user-defined function

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Computation Time Analysis of a Distributed optimization Algorithm Applied to Automated Irrigation Networks

Computation Time Analysis of a Distributed Optimization Algo...

引用

52nd IEEE Annual Conference on Decision and Control (CDC)

作者： Farhadi, Alireza Cantoni, Michael Dower, Peter M. Sharif Univ Technol Dept Elect Engn Tehran Iran Univ Melbourne Dept Elect & Elect Engn Melbourne Vic 3010 Australia

ISBN: (纸本)9781467357173

This paper considers the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the interior point method that does not exploit problem structure. The second is distributed and based on a consensus algorithm, not specifically tailored to account for system structure, but devised rather to facilitate the management of conflicting computational and communication overheads. It is shown that there is a significant advantage in terms of computation time in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation time of the centralized algorithm grows as O(n(4)) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that the computation time of the distributed algorithm grows as O(n) with the number n of sub-systems.

关键词： computational time irrigation networks optimization algorithms Irrigation systems algorithms interior point method distributed algorithms SUB-SYSTEM Automation

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optimization OF FORCING PARAMETERS OF FILM COOLING EFFECTIVENESS

引用

ASME Turbo Expo: Turbine Technical Conference and Exposition

作者： Babaee, Hessam Acharya, Sumanta Wan, Xiaoliang Louisiana State Univ Mech Engn Baton Rouge LA 70803 USA Louisiana State Univ Math Baton Rouge LA 70803 USA

ISBN: (纸本)9780791855157

An optimization strategy is described that combines high-fidelity simulations with response surface construction, and is applied to pulsed film cooling for turbine blades. The response surface is constructed for the film cooling effectiveness as a function of duty cycle, in the range of DC between 0.05 and I, and pulsation frequency St in the range of 0.2-2, using a pseudo-spectral projection method. The jet is fully modulated and the blowing ratio, when the jet is on, is 1.5 in all cases. Overall 73 direct numerical simulations (DNS) using spectral element method were performed to sample the film cooling effectiveness on a Clenshaw-Curtis grid in the design space. The geometry includes a 35-degree delivery tube and a plenum. It is observed that in the parameter space explored a global optimum exists, and in the present study, the best film cooling effectiveness is found at DC = 0.14 and St = 1.03. In the same range of DC and St, four other local optimums were found. The physical mechanisms leading to the forcing parameters of the global optimum are explored and ingestion of the crossflow into the delivery tube is observed to play an important role in this process. The gradient-based optimization algorithms are argued to be unsuitable for the current problem due to the non-convexity of the objective function.

关键词： Simulation Turbine blades Film cooling optimization Engineering simulation Cycles Design Computer simulation optimization algorithms Geometry Response surface methodology Construction

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