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2nd IEEE International conference on Data Science and Network Security, ICDSNS 2024

作者： Xiao, Houguo Tong, Xiaohua Sun, Xiaokun Wang, Shujuan City Institute Dalian University of Technology Liaoning Dalian China

ISBN: (纸本)9798350373110

In this paper, the nonlinear two-layer mathematical modeling based on Fuzzy mathematics is discussed, and the Fuzzy Logic Controlled Differential Evolution (FLC-DE) algorithm based on fuzzy logic control is proposed. Aiming at the limitations of traditional algorithms in dealing with fuzziness, nonlinearity and two-layer structure, this paper proposes a solution framework combining fuzzy theory and efficient optimization technology. This framework can not only describe and deal with fuzziness in decision process more accurately, but also solve complex nonlinear two-layer optimization problems effectively. In this paper, a series of experiments are conducted to evaluate the performance of differential evolution algorithm (FLC-DE) based on fuzzy logic control in solving nonlinear two-layer optimization problems based on fuzzy mathematics. In the comparison experiment of solving accuracy, the average solving accuracy of FLC-DE algorithm reaches 98.5%. It is obviously better than Standard Differential Evolution (Standard DE) and Particle Swarm optimization (PSO). In the calculation efficiency comparison experiment, the calculation time of FLC-DE, Standard DE and PSO is 4.6 seconds, 5.8 seconds and 5.1 seconds respectively, which shows the high efficiency of FLC-DE algorithm. In the stability and robustness analysis experiment, the FLC-DE algorithm has the highest median performance index (about 10) in 50 independent runs, and the least fluctuation, which can be seen that it has the best stability and robustness. From the above experimental results, it can be seen that FLC-DE algorithm has excellent performance in solving accuracy, computational efficiency, stability and robustness, and can be said to be an effective tool to solve such optimization problems. © 2024 IEEE.

关键词： optimization algorithms

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Memory management in embedded vision systems: optimization problems and solution methods

Memory management in embedded vision systems: Optimization p...

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2016 conference on Design and Architectures for Signal and Image Processing, DASIP 2016

作者： Hadj Salem, Khadija Kieffer, Yann Mancini, Stéphane LCIS Laboratory 50 rue Barthélémy de Laffemas BP 54 Valence26902 France TIMA Laboratory 46 avenue Félix Viallet Grenoble38031 France

ISBN: (纸本)9791092279153

Embedded vision systems design faces a memory-wall kind of challenge: images are big, and therefore memories containing them have high latency;and still, high performance is desired. For the case of non-linear processings, Mancini and Rousseau (Proc. DATE 2012) have designed a software generator of adhoc memory hierarchies, called Memory Management optimization (MMOpt). While the performance of the generated circuits is very good, design-time decisions have to be made regarding their operation in order to handle finely the compromise between the usual metrics of design area, energy consumption, and performance. This study tackles the optimization challenge set by the design of the operational behavior of the memory hierarchy generated by MMOpt. After a precise formulation as a 3-objective optimization problem is given, two algorithms are proposed, and their performance is analyzed on real-world processings against the previously proposed algorithms. The results show a reduction of the amount of transferred data by 17% on average, and of the computing times by 11.7%, for the same design area. © 2016 ECSI.

关键词： optimization

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PARC4: high performance Implementation of RC4 Cryptographic Algorithm using Parallelism

PARC4: High Performance Implementation of RC4 Cryptographic ...

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International conference on optimization, Reliabilty, and Information Technology (ICROIT)

作者： Handa, Disha Kapoor, Bhanu Chitkara Univ Comp Sci & Engn Dept Baddi India

ISBN: (纸本)9781479929955

In today's network-based cloud computing era, software applications are playing big role. The security of these software applications is paramount to the successful use of these applications. These applications utilize cryptographic algorithms to secure the data over the network through encryption and decryption processes. The use of parallel processors is now common in both mobile and cloud computing scenarios. Cryptographic algorithms are compute intensive and can significantly benefit from parallelism. This paper introduces a parallel approach to symmetric stream cipher security algorithm known as RC4. The algorithm is very popular and used in many key applications such the Wi-Fi connections, Skype, and Bit Torrent protocol systems. We present an efficient parallel implementation to the compute intensive PRGA that is pseudorandom generation algorithm portion of the RC4 algorithm and the resulted algorithm will be named as PARC4. The algorithm divides a message into fix sized large blocks and encrypts these blocks concurrently on multi core machine.

关键词： Parallel algorithms Encryption RC4 Symmetric WEP PRGA Stream Cipher

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optimization of Scan algorithms on Multi- and Many-core Processors 21

Optimization of Scan Algorithms on Multi- and Many-core Proc...

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21st International conference on high performance Computing (HiPC)

作者： Sun, Qiao Yang, Chao Chinese Acad Sci Inst Software Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci State Key Lab Comp Sci Beijing 100190 Peoples R China

ISBN: (纸本)9781479959754

Scan is a basic building block widely utilized in many applications. With the emergence of multi-core and many-core processors, the study of highly scalable parallel scan algorithms becomes increasingly important. In this paper, we first propose a novel parallel scan algorithm based on the fine grain dynamic task scheduling in QUARK, and then derive a cache-friendly framework for any parallel scan kernel. The QUARK-scan is superior to the fastest available counterpart proposed by Zhang in 2012 and many other parallel scans in several aspects, including the greatly improved load balance and the substantially reduced number of global barriers. On the other hand, the cache-friendly framework helps in improving the cache line usage and is flexible to apply to any parallel scan kernel. A variety of optimization techniques such as SIMD vectorization, loop unrolling, adjacent synchronization and thread affinity are exploited in QUARK-scan and the cache-friendly versions of both QUARK-scan and Zhang's scan. Experiments done on three typical multi-and many-core platforms indicate that the proposed QUARK-scan and the cache-friendly Zhang's scan are superior in different scenarios.

关键词： Parallel scan Multi-core Many-core QUARK-scan Dynamic task scheduling Cache-friendly

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Projected Gradient Descent algorithms for Solving nonlinear Inverse Problems with Generative Priors 31

Projected Gradient Descent Algorithms for Solving Nonlinear ...

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31st International Joint conference on Artificial Intelligence (IJCAI)

作者： Liu, Zhaoqiang Han, Jun Natl Univ Singapore Singapore Singapore Tencent PCG Shenzhen Peoples R China

ISBN: (纸本)9781956792003

In this paper, we propose projected gradient descent (PGD) algorithms for signal estimation from noisy nonlinear measurements. We assume that the unknown signal lies near the range of a Lipschitz continuous generative model with bounded inputs. In particular, we consider two cases when the nonlinear link function is either unknown or known. For unknown nonlinearity, we make the assumption of sub-Gaussian observations and propose a linear least-squares estimator. We show that when there is no representation error, the sensing vectors are Gaussian, and the number of samples is sufficiently large, with high probability, a PGD algorithm converges linearly to a point achieving the optimal statistical rate using arbitrary initialization. For known nonlinearity, we assume monotonicity, and make much weaker assumptions on the sensing vectors and allow for representation error. We propose a nonlinear least-squares estimator that is guaranteed to enjoy an optimal statistical rate. A corresponding PGD algorithm is provided and is shown to also converge linearly to the estimator using arbitrary initialization. In addition, we present experimental results on image datasets to demonstrate the performance of our PGD algorithms.

关键词： optimization

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high-Order equality constraint tracking algorithm for nonlinear optimization

High-Order equality constraint tracking algorithm for nonlin...

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作者： Turner, James D. Texas A and M University College Station TX 77843-3141 United States Dir. of Operations for Consortium for Autonomous Space Systems Aerospace Engineering 745 H.R. Bright Building United States

ISBN: (纸本)9781563479458

Optimal solutions for engineering and scientific systems frequently invoke optimization methods to improve designs that are measured by performance indices. Many successful algorithms exist that build on either linear or second order math models. More complicated problems involve constraint conditions, where equality constraints are most easily handled. This paper presents an equality constraint tracking algorithm that uses high-order Taylor expansions to maintain the current solution estimate on the constraint surfaces. Introduction of a high-order constraint following Taylor series eliminates the need for introducing Lagrange multipliers. A Davidenko-like embedding operator is introduced to simultaneously couple the performance index and constraint surface partials. The classical n-dimensional searching problem is replaced with a single parameter search. Computational differentiation provides first through fourth order mixed partial derivatives for all calculations. The algorithm begins with a basic feasible solution for the vector set of constraint conditions. Repeated differentiations of the embedding function provides a cascade of nonlinear partial derivative necessary conditions that linearly contain the linked performance index/ constraint surface partial derivatives. The solution vector is Taylor expanded in terms of the coupled performance index/constraint surface partials. Additional Taylor series approximations are obtained for the performance its derivative w.r.t. into the embedding operator coupling parameter;yielding polynomials that are easily solved for minima, maxima, and extrema values by using standard numerical software. Several examples are provided to demonstrate the effectiveness of the proposed approach. The proposed algorithm is expected to have a significant impact on knowledge discovery applications where equality constrained optimization is a critical step in the design of future advanced technology systems. Copyright © 2008 by James D. T

关键词： Lagrange multipliers

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MULTI-MODAL LEARNING WITH GENERALIZABLE nonlinear DIMENSIONALITY REDUCTION 26

MULTI-MODAL LEARNING WITH GENERALIZABLE NONLINEAR DIMENSIONA...

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26th IEEE International conference on Image Processing (ICIP)

作者： Kaya, Semih Vural, Elif METU Dept Elect & Elect Engn Ankara Turkey

ISBN: (纸本)9781538662496

In practical machine learning settings, there often exist relations or links between data from different modalities. The goal of multimodal learning algorithms is to efficiently use the information available in different modalities to solve multi-modal classification or retrieval problems. In this study, we propose a multi-modal supervised representation learning algorithm based on nonlinear dimensionality reduction. nonlinear embeddings often yield more flexible representations compared to linear counterparts especially in case of high dissimilarity between the data geometries in different modalities. Based on recent performance bounds on nonlinear dimensionality reduction, we propose an optimization objective aiming to improve the intra- and inter-modal within-class compactness and between-class separation, as well as the Lipschitz regularity of the interpolator that generalizes the embedding to the whole data space. Experiments in multi-view face recognition and image-text retrieval applications show that the proposed method yields promising performance in comparison with state-of-the-art multi-modal learning methods.

关键词： Cross-modal learning multi-view learning cross-modal retrieval nonlinear embeddings RBF interpolators

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System identification and machine setup of color xerographic machines using multivariate modeling and multiobjective optimization

System identification and machine setup of color xerographic...

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IEEE International conference on Control Applications

作者： Rai, S Xerox Corp Webster NY 14580 USA

ISBN: (纸本)078034104X

This paper describes an approach for performing system identification of the xerographic process and developing a model of the overall system. The experiment design is performed using orthogonal arrays. A nonlinear system model defining a vector mapping between the actuators and performance metrics is constructed using multivariate adaptive regression splines (MARS). These models provide a basis for providing automated and optimal machine setup on color machines. Multiobjective optimization techniques based on an underlying adaptive simulated annealing approach are discussed which are then used for determining the Pareto-optimal setpoints. The overall approach is applied to perform the automated setups of a high-end color machine, namely the Docucolor40. Experimental results show that high quality machine setups can be performed in an efficient and automated manner. The use of these setpoints as the basis of linearization about a nominal setpoint for use in linear control algorithms are also discussed.

关键词： xerography modeling optimization splines

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optimization Principles for Collective Neighborhood Communications

Optimization Principles for Collective Neighborhood Communic...

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25th ACM/IEEE International conference for high performance Computing, Networking, Storage and Analysis (SC)

作者： Hoefler, Torsten Schneider, Timo Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Univ Illinois Urbana IL 60680 USA

ISBN: (纸本)9781467308052;9781467308045

Many scientific applications operate in a bulk-synchronous mode of iterative communication and computation steps. Even though the communication steps happen at the same logical time, important patterns such as stencil computations cannot be expressed as collective communications in MPI. We demonstrate how neighborhood collective operations allow to specify arbitrary collective communication relations during runtime and enable optimizations similar to traditional collective calls. We show a number of optimization opportunities and algorithms for different communication scenarios. We also show how users can assert constraints that provide additional optimization opportunities in a portable way. We demonstrate the utility of all described optimizations in a highly optimized implementation of neighborhood collective operations. Our communication and protocol optimizations result in a performance improvement of up to a factor of two for small stencil communications. We found that, for some patterns, our optimization heuristics automatically generate communication schedules that are comparable to hand-tuned collectives. With those optimizations in place, we are able to accelerate arbitrary collective communication patterns, such as regular and irregular stencils with optimization methods for collective communications. We expect that our methods will influence the design of future MPI libraries and provide a significant performance benefit on large-scale systems.

关键词： application program interfaces iterative methods message passing parallel programming protocols software performance evaluation

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Optimal Design of Corona Ring on HV Composite Insulator Using PSO Approach with Dynamic Population Size

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IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION 2016年第2期23卷 1048-1057页

作者： M'hamdi, B. Teguar, M. Mekhaldi, A. Ecole Natl Polytech Lab Rech Electrotech 10 Ave Hassen BadiBP 182 Algiers 16200 Algeria

This paper deals with the use of corona ring at the HV end fitting for improving the electric field and potential distributions and then for minimizing the corona discharges on 230 kV AC transmission line composite insulator. A single corona ring is installed at the energized end side. Three-dimensional finite element method (FEM) software is employed to compute the electric field. As the performance of high voltage insulator strings closely depends on designs and locations of corona ring, the effects of the corona ring radius, the ring tube radius and the ring vertical position are examined. The minimization of the electric field necessitates the optimization of corona ring. For this purpose, new nonlinear mathematical objective function linking the electric field strength to the corona ring structure parameters is established. The optimization problem is achieved by minimizing the objective function using a modified particles swarm optimization (PSO) algorithm with a dynamic population size. The algorithm adjusts the size of population for each iteration. Based on the average value and the best solution of the objective function, we propose a new mathematical model to update the population size. This algorithm enables the population size reduction leading to computing time decrease. According to the results, FEM-PSO hybridization technique could be very helpful in optimization of corona ring design.

关键词： Composite insulator Corona ring Electric field distribution Finite element method (FEM) Insulator string Particles swarm optimization Dynamic population size

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