Search results for "OPTIMIZATION"

Using FOCAP tool for teaching microarchitecture simulation and optimization

2013

This paper presents our new developed FOCAP tool (Framework for optimizing the Computer Architecture Performance) in order to gain a better understanding and familiarity of the students with new advanced learning methods and tools in the Microarchitecture Simulation and Optimization. At this stage, FOCAP allows a mono-objective automatic design space exploration (DSE) of a superscalar processor by varying several architectural parameters. Such DSE tools are very useful, since it is impossible to simulate all the configurations of a highly parameterized microarchitecture. Therefore, heuristic methods, local search algorithms and advanced machine learning methods are good candidates to find n…

Improving programming skills of Mechanical Engineering students by teaching in C# multi-objective optimizations methods

2017

Designing an optimized suspension system that meet the main functions of comfort, safety and handling on poor quality roads is a goal for researchers. This paper represents a software development guide for designers of suspension systems with less programming skills that will enable them to implement their own optimization methods that improve traditional methods by using their domain knowledge.

Constructive Optimization of Vulcanization Installations in Order to Improve the Performance of Conveyor Belts

2019

Conveyor belts of special importance must have superior mechanical characteristics. The joining by vulcanization of the conveyor belts allows to obtain superior performances, but it has been found that at the vulcanizing joint of the conveyor belts, there is a &ldquo

Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization

2018

Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.

An abstract inf-sup problem inspired by limit analysis in perfect plasticity and related applications

2021

This paper is concerned with an abstract inf-sup problem generated by a bilinear Lagrangian and convex constraints. We study the conditions that guarantee no gap between the inf-sup and related sup-inf problems. The key assumption introduced in the paper generalizes the well-known Babuška–Brezzi condition. It is based on an inf-sup condition defined for convex cones in function spaces. We also apply a regularization method convenient for solving the inf-sup problem and derive a computable majorant of the critical (inf-sup) value, which can be used in a posteriori error analysis of numerical results. Results obtained for the abstract problem are applied to continuum mechanics. In particular…

Efficient linear fusion of partial estimators

2018

Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…

A New Technique for Education Process Optimization via the Dual Control Approach

2018

Energy Efficient Consensus Over Directed Graphs

2018

Consensus algorithms are iterative methods that represent a basic building block to achieve superior functionalities in increasingly complex sensor networks by facilitating the implementation of many signal-processing tasks in a distributed manner. Due to the heterogeneity of the devices, which may present very different capabilities (e.g. energy supply, transmission range), the energy often becomes a scarce resource and the communications turn into directed. To maximize the network lifetime, a magnitude that in this work measures the number of consensus processes that can be executed before the first node in the network runs out of battery, we propose a topology optimization methodology fo…

Krill herd algorithm-based neural network in structural seismic reliability evaluation

2018

ABSTRACTIn this research work, the relative displacement of the stories has been determined by means of a feedforward Artificial Neural Network (ANN) model, which employs one of the novel methods for the optimization of the artificial neural network weights, namely the krill herd algorithm. For the purpose of this work, the area, elasticity, and load parameters were the input parameters and the relative displacement of the stories was the output parameter. To assess the precision of the feedforward (FF) model optimized using the Krill Herd Optimization (FF-KH) algorithm, comparison of results has been performed relative to the results obtained by the linear regression model, the Genetic Alg…

Register data in sample allocations for small-area estimation

2018

The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and t…