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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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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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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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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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On the Calibration of Stochastic Volatility Models: A Comparison Study

On the Calibration of Stochastic Volatility Models: A Compar...

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IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr)

作者： Zhai, Jia Cao, Yi Univ Ulster Dept Accounting Finance & Econ Jordanstown North Ireland Univ Ulster Sch Comp & Intelligent Syst Coleraine BT52 1SA Londonderry North Ireland

ISBN: (纸本)9781479923809

We studied the application of gradient based optimization methods for calibrating stochastic volatility models. In this study, the algorithmic differentiation is proposed as a novel approach for Greeks computation. The "payoff function independent" feature of algorithmic differentiation offers a unique solution cross distinct models. To this end, we derived, analysed and compared Monte Carlo estimators for computing the gradient of a certain payoff function using four different methods: algorithmic differentiation, Pathwise delta, likelihood ratio and finite differencing. We assessed the accuracy and efficiency of the four methods and their impacts into the optimisation algorithm. Numerical results are presented and discussed.

关键词： Biologicalsystemmodeling Calibration Europe Mathematicalmodel MonteCarlomethods Sensitivity Stochasticprocesses Calibration Volatility optimization algorithms Stochastic Greek Europe optimization methods differentiation Differentiation Individualized Instruction

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Hot-start efficiency of Quadratic Programming algorithms for fast Model Predictive Control: A comparison via an Adaptive Optics case study 4

Hot-start efficiency of Quadratic Programming algorithms for...

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4th Australian Control Conference (AUCC)

作者： Konnik, Mikhail De Dona, Jose Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia Univ Newcastle Fac Engn & Built Environm Callaghan NSW 2308 Australia

ISBN: (纸本)9781922107398

Model Predictive Control (MPC) with fast sampling rates can be extremely demanding in terms of the required computational time. However, the control problem in some cases does not change much from one sampling instance to the next, and therefore hot-start can be used to considerably accelerate the solution of an online optimisation problem. An adaptive optics system is used in this work as an example of such a control system to evaluate the benefits of hot-start for different families of optimisation algorithms. A comparison of the computational times and a discussion of hot-start efficiency for Interior Point, Active Set, Gradient-based and Augmented Lagrangian algorithms are provided in this contribution.

关键词： Actuators Algorithm design and analysis Atmospheric modeling Couplings IP networks Quadratic programming Algorithm design and analysis quadratic programming Atmospheric models Internet Protocol networks hot start Couplings actuators Model predictive control coupling optimization algorithms Predictive control control systems computational time

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Dynamic Railway Junction Rescheduling using Population Based Ant Colony Optimisation 14

Dynamic Railway Junction Rescheduling using Population Based...

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14th UK Annual Workshop on Computational Intelligence (UKCI)

作者： Eaton, Jayne Yang, Shengxiang De Montfort Univ Sch Comp Sci & Informat Ctr Computat Intelligence Leicester LE1 9BH Leics England

ISBN: (纸本)9781479955381

Efficient rescheduling after a perturbation is an important concern of the railway industry. Extreme delays can result in large fines for the train company as well as dissatisfied customers. The problem is exacerbated by the fact that it is a dynamic one;more timetabled trains may be arriving as the perturbed trains are waiting to be rescheduled. The new trains may have different priorities to the existing trains and thus the rescheduling problem is a dynamic one that changes over time. The aim of this research is to apply a population-based ant colony optimisation algorithm to address this dynamic railway junction rescheduling problem using a simulator modelled on a real-world junction in the UK railway network. The results are promising: the algorithm performs well, particularly when the dynamic changes are of a high magnitude and frequency.

关键词： Cities and towns Delays Heuristic algorithms Junctions optimization Rail transportation Tracking Rail transportation Cities and towns Heuristic algorithms Junction Device Component Rescheduling railway junctions TRAIN tracking delay railway industry Ant colony optimization railway network optimization algorithms Dissatisfaction

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Optimal Number of Rotor Parameters for the Automatic Design of Synchronous Reluctance Machines 21

Optimal Number of Rotor Parameters for the Automatic Design ...

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International Conference on Electrical Machines (ICEM)

作者： Gamba, Matteo Pellegrino, Gianmario Cupertino, Francesco Politecn Torino Dept Energy Turin Italy Politecn Bari Dept Elect & Elect Engn Bari Italy

ISBN: (纸本)9781479943883

The automatic design of Synchronous Reluctance machines is proposed, based on Multi-Objective optimization and Finite-Element Analysis. An original description of the rotor geometry in the simple terms of three parameters per flux barrier is formalized and tested with finite elements and experiments. The results obtained with the proposed geometry are compared to the ones previously obtained applying the same automatic design procedure to simpler geometries. Plus, a state of the art rotor, designed with no restrictions in terms of geometric degrees of freedom is also used as a further benchmark for the comparison. The paper demonstrates that three variables per barrier is the appropriate number of parameters to be used for a fast and yet accurate description of multi-barrier Synchronous Reluctance machine rotors.

关键词： AC Motors Variable Speed Drives Synchronous Reluctance Machines optimization algorithms Finite Element Analysis

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