Search results for " Strategy"

showing 10 items of 764 documents

Synthesis and characterization of nanomaterial based on halloysite and hectorite clay minerals covalently bridged

2021

Halloysite is an aluminosilicate clay with a predominantly hollow tubular structure (HNTs) able to act as a nanocontainer for the encapsulation of several chemicals. However, HNTs possess low affinity for metal ions in their pristine form and they need to be modified for improving their adsorption capabilities. Therefore, to overcome this issue herein we report a straightforward approach for the covalent modification of the external surface of halloysite nanotubes with hectorite clay. Compared to halloysite, hectorite possesses a lamellar structure with higher cation exchange capacity. The covalent linkage between the two clays was verified by several techniques (FTIR spectroscopy, 13C CP-M…

Materials scienceHalloysite nanotubesGeneral Chemical EngineeringMetal ions in aqueous solutionSettore CHIM/06 - Chimica Organicaengineering.materialHalloysiteArticleNanomaterialslcsh:ChemistrySynthetic strategyAdsorptionlcsh:QD1-999Chemical engineeringCovalent linkageCovalent bondAluminosilicateHectoriteHectoriteengineeringGeneral Materials ScienceLamellar structureSettore CHIM/02 - Chimica Fisica
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Atomically Precise Gold Nanoclusters: Towards an Optimal Biocompatible System from a Theoretical-Experimental Strategy.

2021

Potential biomedical applications of gold nanoparticles have increasingly been reported with great promise for diagnosis and therapy of several diseases. However, for such a versatile nanomaterial, the advantages and potential health risks need to be addressed carefully, as the available information about their toxicity is limited and inconsistent. Atomically precise gold nanoclusters (AuNCs) have emerged to overcome this challenge due to their unique features, such as superior stability, excellent biocompatibility, and efficient renal clearance. Remarkably, the elucidation of their structural and physicochemical properties provided by theory-experiment investigations offers exciting opport…

Materials scienceNanoparticleMetal NanoparticlesNanotechnology02 engineering and technologyGeneral Chemistry010402 general chemistry021001 nanoscience & nanotechnologyBiocompatible material01 natural sciences0104 chemical sciencesNanoclustersNanostructuresBiomaterialsExperimental strategyColloidal goldNanomedicineGeneral Materials ScienceGold0210 nano-technologyBiotechnologyClearanceSmall (Weinheim an der Bergstrasse, Germany)
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Intelligent Multi-Start Methods

2018

Heuristic search procedures aimed at finding globally optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored, which constitutes a multi-start procedure. In this chapter we describe the best known multi-start methods for solving optimization problems. We also describe their connections with other metaheuristic methodologies. We propose classifying these methods in terms of their use of randomization, memory and degree of rebuild. We also present a computational comparison of these methods on solvi…

Mathematical optimization021103 operations researchOptimization problemDegree (graph theory)Computer sciencemedia_common.quotation_subject0211 other engineering and technologiesCombinatorial optimization problem020206 networking & telecommunications02 engineering and technologyDiversification (marketing strategy)0202 electrical engineering electronic engineering information engineeringQuality (business)Metaheuristicmedia_common
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Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper System

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/709027 Open access We propose a method to improve the performance of evolutionary algorithms (EA). The proposed approach defines operators which can modify the performance of EA, including Levy distribution function as a strategy parameters adaptation, calculating mean point for finding proper region of breeding offspring, and shifting strategy parameters to change the sequence of these parameters. Thereafter, a set of benchmark cost functions is utilized to compare the results of the proposed method with some other well-known algorithms.…

Mathematical optimizationEngineeringSequenceArticle Subjectbusiness.industryGeneral Mathematicslcsh:MathematicsLévy distributionGeneral EngineeringEvolutionary algorithmfuzzy controlFuzzy control systemFunction (mathematics)lcsh:QA1-939shifting strategyVDP::Mathematics and natural science: 400::Mathematics: 410Set (abstract data type)lcsh:TA1-2040improving performanceBenchmark (computing)Point (geometry)trucksevolutionary algorithmsbusinesslcsh:Engineering (General). Civil engineering (General)Mathematical Problems in Engineering
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An improved sampling strategy based on trajectory design for application of the Morris method to systems with many input factors

2012

[EN] In this paper, a revised version of the Morris approach, which includes an improved sampling strategy based on trajectory design, has been adapted to the screening of the most influential parameters of a fuzzy controller applied to WWTPs. Due to the high number of parameters, a systematic approach has been proposed to apply this improved sampling strategy with low computational demand. In order to find out the proper repetition number of elementary effects of each input factor on model output (EEi) calculations, an iterative and automatic procedure has been applied. The results show that the sampling strategy has a significant effect on the parameter significance ranking and that rando…

Mathematical optimizationEnvironmental EngineeringComputer scienceEcological ModelingFuzzy controllersSampling (statistics)Parameter spaceRepetition NumberFuzzy logicSampling strategyRankingControl theoryTrajectoryMorris methodMorris screeningSensitivity analysisSoftwareTECNOLOGIA DEL MEDIO AMBIENTE
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An Island Strategy for Memetic Discrete Tomography Reconstruction

2014

In this paper we present a parallel island model memetic algorithm for binary discrete tomography reconstruction that uses only four projections without any further a priori information. The underlying combination strategy consists in separated populations of agents that evolve by means of different processes. Agents progress towards a possible solution by using genetic operators, switch and a particular compactness operator. A guided migration scheme is applied to select suitable migrants by considering both their own and their sub-population fitness. That is, from time to time, we allow some individuals to transfer to different subpopulations. The benefits of this paradigm were tested in …

Mathematical optimizationInformation Systems and ManagementCorrectnessSettore INF/01 - InformaticaComputationMigration strategyBinary numberIterative reconstructionMemetic island modelNoisy projectionStability problemComputer Science ApplicationsTheoretical Computer ScienceOperator (computer programming)Artificial IntelligenceControl and Systems EngineeringImage reconstructionA priori and a posterioriMemetic algorithmAlgorithmDiscrete tomographySoftwareParallel discrete tomographyMathematics
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Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

2011

Part 1: - PE-CRN 2011 Workshop; International audience; In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.

Mathematical optimizationMathematical modelComputer science020209 energycontinuous time Markov chain modelsAggregate (data warehouse)Cognitive radio networks020206 networking & telecommunications02 engineering and technologyMarkov modelchannel aggregation strategyperformance evaluationContinuous-time Markov chain[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Cognitive radio0202 electrical engineering electronic engineering information engineeringDynamic channel[INFO]Computer Science [cs]SimulationComputer Science::Information TheoryCommunication channel
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Multi-Start Methods

2006

Heuristic search procedures that aspire to find global optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored. In this chapter we describe the best known multi-start methods for solving optimization problems. We propose classifying these methods in terms of their use of randomization, memory and degree of rebuild. We also present a computational comparison of these methods on solving the linear ordering problem in terms of solution quality and diversification power.

Mathematical optimizationOptimization problemDegree (graph theory)Computer sciencemedia_common.quotation_subjectCombinatorial optimization problemQuality (business)Diversification (marketing strategy)Linear orderingGlobal optimalmedia_common
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Advanced Multi-start Methods

2010

Heuristic search procedures that aspire to find globally optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored. In this chapter we describe the best known multi-start methods for solving optimization problems. We propose classifying these methods in terms of their use of randomization, memory, and degree of rebuild. We also present a computational comparison of these methods on solving the maximum diversity problem in terms of solution quality and diversification power.

Mathematical optimizationOptimization problemDegree (graph theory)media_common.quotation_subjectCombinatorial optimization problemQuality (business)Diversification (marketing strategy)Mathematicsmedia_common
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On multi-objective optimal reconfiguration of MV networks in presence of different grounding

2015

The present work faces the traditional multi-objective optimal reconfiguration problem of a distribution grid including the safety issue in the objective functions. Actually, in many medium voltage networks still transformers with ungrounded neutral and with resonant grounded neutral coexist in the same area. This may be sometimes cause of problems during a single-line-to-ground fault if the ground electrodes of one or more cabins, initially designed for satisfying the safety conditions in a resonant grounded neutral network, after the reconfiguration are in a grounded neutral one or vice versa. In the paper a safety objective function is defined and the Non dominated Sorting Genetic Algori…

Mathematical optimizationOptimization problemGeneral Computer ScienceComputer science020209 energyDistribution gridGlobal grounding02 engineering and technologyFuzzy logiclaw.inventionMetallawMV network0202 electrical engineering electronic engineering information engineeringTransformerReconfiguration;MV network;Global grounding;Distribution grid;Genetic algorithmGroundbusiness.industryComputer Science (all)Control reconfigurationEarthing systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaGenetic algorithmvisual_artEmbedded systemElectrodeReconfigurationvisual_art.visual_art_mediumEvolution strategybusiness
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