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2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI)

作者： Neri, Ferrante Khan, Noel De Montfort Univ Ctr Computat Intelligence Sch Comp Sci & Informat Gateway Leicester LE1 9B1L Leics England

ISBN: (纸本)9781479944910

Within memetic computing frameworks, the structure as well as a correct choice of memes are important elements that drive successful optimization algorithms. This paper studies variations of a promising yet simple search operator, the S Algorithm, which can easily be integrated within a memetic framework to improve candidate solutions. S is a single-solution optimizer that iteratively perturbs variables and conditionally evaluates solutions along the axes. The first S variant, namely S2, unconditionally evaluates solutions in both directions while S3 maintains D uncorrelated step sizes that are either expanded in the direction of improving fitness or else redirected and contracted. Numerical results from the CEC2010 and CEC2014 benchmarks show that the variants outperform S in terms of the number of function evaluations for a given fitness value and, further, that S3 outperforms S in terms of final fitness against a wide range of problems and dimensionality.

关键词： evolutionary computation iterative methods optimisation search problems CEC2010 benchmark CEC2014 benchmark S algorithm conditional evaluation function evaluation iterative variable perturbation local search components memetic computing frameworks optimization algorithm search operator single-solution optimizer Algorithm design and analysis Benchmark testing Correlation Market research Memetics optimization Sociology Function evaluation Algorithm design and analysis Benchmark testing optimization algorithms tabu search market research Sociology evolutionary algorithm iterative methods axe Axis, Cervical Vertebra Sulfur Frameworks

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Cost-Optimal Execution of Boolean Query Trees with Shared Streams

Cost-Optimal Execution of Boolean Query Trees with Shared St...

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IEEE 28th International Parallel & Distributed Processing Symposium (IPDPS)

作者： Casanova, Henri Lim, Lipyeow Robert, Yves Vivien, Frederic Zaidouni, Dounia Univ Hawaii Manoa Honolulu HI 96822 USA INRIA Ecole Normale Superieure Lyon Lyon France Univ Tennessee Knoxville TN 37996 USA

ISBN: (纸本)9780769552071

The processing of queries expressed as trees of boolean operators applied to predicates on sensor data streams has several applications in mobile computing. Sensor data must be retrieved from the sensors, which incurs a cost, e.g., an energy expense that depletes the battery of a mobile query processing device. The objective is to determine the order in which predicates should be evaluated so as to shortcut part of the query evaluation and minimize the expected cost. This problem has been studied assuming that each data stream occurs at a single predicate. In this work we remove this assumption since it does not necessarily hold in practice. Our main results are an optimal algorithm for single-level trees and a proof of NP-completeness for DNF trees. For DNF trees, however, we show that there is an optimal predicate evaluation order that corresponds to a depth-first traversal. This result provides inspiration for a class of heuristics. We show that one of these heuristics largely outperforms other sensible heuristics, including a heuristic proposed in previous work.

关键词： Heuristics query analysis ENERGY EXPENSES data flow Predicate Sensor Data trees Trees disjunctive normal form optimization algorithms Respiratory Inspiration inspiration rivers streams Batteries

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SuperPUF: Integrating Heterogeneous Physically Unclonable Functions 33

SuperPUF: Integrating Heterogeneous Physically Unclonable Fu...

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33rd IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

作者： Wang, Michael Yates, Andrew Markov, Igor L. Univ Michigan 2260 Hayward St Ann Arbor MI 48109 USA

ISBN: (纸本)9781479962785

Physically Unclonable Functions (PUFs) combat counterfeit ICs by identifying each chip using inherent process variation. PUFs must produce sufficiently many bits, but replicating the same PUF design requires care since process variation and its spatial correlation may change in the next 10 years. Additional challenges arise in system-on-chip and heterogeneous 3D integration of diverse PUFs. Responding to these challenges, we introduce methods for combining PUFs, with provisions for sampling process variation throughout the IC. When multiple sources of entropy are available, our optimization algorithms select sources to maximize joint entropy and minimize physical overhead. Empirical validation uses SPICE simulations for a 45nm technology node.

关键词： entropy integrated circuit design integrated circuit manufacture integrated circuit technology optimisation system-on-chip three-dimensional integrated circuits PUF design replication SPICE simulation chip identification counterfeit IC entropy source heterogeneous 3D integration heterogeneous physically unclonable functions integration inherent process variation optimisation algorithm physical overhead minimization size 45 nm spatial correlation superPUF Clocks Correlation Entropy Integrated circuit modeling Logic gates Robustness system-on-chip entropy optimization algorithms three-dimensional integrated circuits integrated circuit technology integrated circuit manufacture integrated circuit modelling integrated circuit design Timing devices Logic gates process change

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Revisiting the Distribution Index in Simulated Binary Crossover Operator for Evolutionary Multiobjective Optimisation algorithms

Revisiting the Distribution Index in Simulated Binary Crosso...

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4th International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)

作者： Hamdan, Mohammad M. JUST Dept Comp Sci Irbid Jordan Yarmouk Univ Irbid Jordan

ISBN: (纸本)9781479937240

The simulated binary crossover operator is an important variation operator in evolutionary algorithms. The experimental results reported in this work are a detailed study for the distribution index parameter of this operator. The results are for NSGAII algorithm. The results are interesting regarding three metrics: hypervolume, inverted generational distance and spread.

关键词： optimization algorithms Operators Binary Genetic Crossing Over simulating hypervolume

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Private Empirical Risk Minimization: Efficient algorithms and Tight Error Bounds 55

Private Empirical Risk Minimization: Efficient Algorithms an...

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55th Annual IEEE Symposium on Foundations of Computer Science (FOCS)

作者： Bassily, Raef Smith, Adam Thakurta, Abhradeep Penn State Univ Comp Sci & Engn Dept University Pk PA 16802 USA Yahoo Labs Sunnyvale CA USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781479965175

Convex empirical risk minimization is a basic tool in machine learning and statistics. We provide new algorithms and matching lower bounds for differentially private convex empirical risk minimization assuming only that each data point's contribution to the loss function is Lipschitz and that the domain of optimization is bounded. We provide a separate set of algorithms and matching lower bounds for the setting in which the loss functions are known to also be strongly convex. Our algorithms run in polynomial time, and in some cases even match the optimal nonprivate running time (as measured by oracle complexity). We give separate algorithms (and lower bounds) for (epsilon, 0)- and (epsilon, delta)-differential privacy;perhaps surprisingly, the techniques used for designing optimal algorithms in the two cases are completely different. Our lower bounds apply even to very simple, smooth function families, such as linear and quadratic functions. This implies that algorithms from previous work can be used to obtain optimal error rates, under the additional assumption that the contributions of each data point to the loss function is smooth. We show that simple approaches to smoothing arbitrary loss functions (in order to apply previous techniques) do not yield optimal error rates. In particular, optimal algorithms were not previously known for problems such as training support vector machines and the high-dimensional median.

关键词： Algorithm design and analysis Convex functions Noise measurement optimization Privacy Risk management Support vector machines LOSS FUNCTION Algorithm design and analysis Support Vector Network Noise measurement Convex function Privacy Risk Management Lower bound Error analysis algorithms optimization algorithms

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Modulation-format-transparent Carrier Phase Estimation for Optical Coherent Receivers

Modulation-format-transparent Carrier Phase Estimation for O...

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19th OptoElectronics and Communication Conference (OECC) / 39th Australian Conference on Optical Fibre Technology (ACOFT)

作者： Wang, Dawei Geng, Dongyu Fu, H. Y. Huawei Technol Co Ltd Commun Technol Lab Shenzhen 518129 Peoples R China

The general form of U-CPE is presented and the optimal algorithm with better performance and lower complexity is proposed and analyzed. Simulation results show low OSNR penalty can be obtained for various modulation f... 详细信息

ISBN: (纸本)9781922107213

关键词： Bit error rate Complexity theory Feedforward neural networks Optical noise Phase shift keying Signal processing algorithms Signal to noise ratio Optical noise Signal processing algorithms signal to noise ratios Phase shift keying feedforward neural nets Complexity theory Bit error rate coherent receiver Phase estimation optimization algorithms carrier phase

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Mission-driven Sensor Management based on Expected-Utility and Prospect Objectives 17

Mission-driven Sensor Management based on Expected-Utility a...

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17th International Conference on Information Fusion (FUSION)

作者： de Groot, Teun H. Krasnov, Oleg A. Yarovoy, Alexander G. Delft Univ Technol Microwave Sensing Signals & Syst NL-2600 AA Delft Netherlands

ISBN: (纸本)9781479916344

A set of mission-driven objective functions, which can be used for sensor management, is proposed. While an optimization algorithm maximizes the output of objective functions, the definition of such a function is a challenge in itself. Objectives in sensor research are usually based on sensing characteristics (e.g. estimation error, information measure), but they do not necessary describe mission goals. To improve this, we present two types of objective functions based on expected-utility and prospect. Their generality are demonstrated and their properties are compared in two case studies where the end-user has the goal to protect and/or capture physical objects using effectors that are supported by radar sensors and video cameras. A benefit is that the objectives are linked to relevant operational parameters, that are understandable for end-users, and the objectives can be fine-tuned according to end-user's preferences. Because the mission-driven objectives define on a high level what should be achieved in the end, they actually allow to utilize the employed sensors at their full potential.

关键词： Games Linear programming Mathematical model Radar Search problems Sensors Target tracking Sensors tabu search Target tracking radar linear programming End users Objective function Mathematical Model Religious Missions optimization algorithms Game theory

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Sum Energy-Efficiency Maximization for Cognitive Uplink Networks with Imperfect CSI

Sum Energy-Efficiency Maximization for Cognitive Uplink Netw...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Ramamonjison, Rindranirina Bhargava, Vijay K. Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9781479930838

In this work, we investigate the robust energy efficient transmission for the cognitive uplink wireless system. Precisely, we propose an optimization framework for maximizing the sum energy efficiency while taking into account the uncertainty of the channel between the primary and secondary users. Here, we assume that the base station has multiple antennas and employs a zero-forcing receive filter to eliminate the inter-user interference. We handle the intractability of the probabilistic interference constraints by approximating them with convex and linear surrogate constraints. Despite the non convexity of the utility function, we propose a parametric convex programming approach to derive an optimal algorithm based on Newton method. Through numerical simulations, we show the convergence and effectiveness of the proposed method and analyze the effect of channel uncertainty on the energy efficiency of the cognitive uplink system.

关键词： Newton method cognitive radio convex programming intercarrier interference probability base station cognitive uplink wireless system convex surrogate constraints interuser interference linear surrogate constraints optimal algorithm optimization framework parametric convex programming approach primary users probabilistic interference constraints robust energy-efficient transmission secondary users sum energy efficiency Approximation methods Interference Probabilistic logic Resource management Robustness Uncertainty Uplink Newton method up link optimization algorithms convex programming Probabilistic logic intercarrier interference Approximation method Energy efficiency Cognitive radio management of resources BASE STATION Uncertainty

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Level Set-Based Topology optimization of Hinge-Free Compliant Mechanisms Using a Two-Step Elastic Modeling Method

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JOURNAL OF MECHANICAL DESIGN 2014年第3期136卷 031007-031007页

作者： Zhu, Benliang Zhang, Xianmin Fatikow, Sergej S China Univ Technol Guangdong Prov Key Lab Precis Equipment & Mfg Tec Guangzhou 510640 Guangdong Peoples R China Carl von Ossietzky Univ Oldenburg Dept Comp Sci Div Microrobot D-26111 Oldenburg Germany

This paper presents a two-step elastic modeling (TsEM) method for the topology optimization of compliant mechanisms aimed at eliminating de facto hinges. Based on the TsEM method, an alternative formulation is developed and incorporated with the level set method. An efficient algorithm is developed to solve the level set-based optimization problem for improving the computational efficiency. Two widely studied numerical examples are performed to demonstrate the validity of the proposed method. The proposed formulation can prevent hinges from occurring in the resulting mechanisms. Further, the proposed optimization algorithm can yield fewer design iterations and thus it can improve the overall computational efficiency.

关键词： Hinges Design optimization Displacement Topology Compliant mechanisms optimization algorithms Modeling

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Minimizing Mobility and Communication Energy in Robotic Networks: an Optimal Control Approach

Minimizing Mobility and Communication Energy in Robotic Netw...

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American Control Conference

作者： Jaleel, H. Wardi, Y. Egerstedt, M. Univ Engn & Technol Dept Elect Engn Lahore Pakistan

ISBN: (纸本)9781479932740

This paper concerns the problem of minimizing the sum of motion energy and communication energy in a network of mobile robots. The robotic network is charged with the task of transmitting sensor information from a given object to a remote station, and it has to arrange itself in a serial (tandem) configuration for point-to-point transmission, where each robot acts as a relay node. The problem is formulated in a dynamic setting where the robots move and communicate at the same time, and it is cast in the framework of optimal control. The paper proposes an effective algorithm for solving this problem and demonstrates its efficacy on a simulation example. In order to highlight the salient features of the algorithm the network is assumed to be one-dimensional, and the case of planar movement with obstacles is deferred to future research.

关键词： Convergence Equations Mobile communication Optimal control Robot sensing systems Trajectory optimization algorithms Switched systems

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