Search results for "meme"

showing 10 items of 101 documents

Pisteis in Comparison: Examples and Enthymemes in the Rhetoric to Alexander and in Aristotle's Rhetoric

2011

Today it is generally accepted that the main differences between the "Rhetoric to Alexander" and Aristotle’s "Rhetoric" depend on the different aims of each work’s author: essentially practical in the first case, theoretical in the second one. The difference is clearly visible in the classification of pisteis (proofs). Our basic assumption is that this difference depends on the two majors elements of novelty in Aristotle's Rhetoric: 1. the introduction in the rhetorical field of the logico-dialectical apparatus (above all, the concept of syllogismos); 2. the consideration of ethos and pathos as entechnoi pisteis. In order to specify this general consideration, the paper focuses on enthymema…

Linguistics and Languagemedia_common.quotation_subjectPhilosophypistis enthymemeexample Aristotle Rhetoric to AlexanderRhetoricHumanitiesSettore M-FIL/05 - Filosofia E Teoria Dei LinguaggiLanguage and Linguisticsmedia_commonRhetorica
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Genetic risk profiles for Alzheimer's disease: Integration of APOE genotype and variants that up-regulate inflammation

2007

BACKGROUND: A number of studies associate Alzheimer's disease with APOE polymorphism and alleles which favor the increased expression of immunological mediators such as cytokines or acute phase proteins. We integrated this information to better define risk and determine the relative importance of APOE and immunological mediators. METHODS: We investigated functional gene variants for APOE, IL-10 (3 loci), ACT (2 loci), HMGCR, IL-1alpha, IL-1beta, TNF-alpha, IFN-gamma, and IL-6 found for 260 AD patients and 190 controls enrolled in Northern Italy. A fuzzy latent classification approach, namely grade-of-membership analysis (GoM), was taken to identify extreme pure type risk sets, or profiles. …

MaleApolipoprotein EAgingGenotypeDiseaseBiologyApolipoproteins EAlzheimer DiseaseRisk FactorsGenotypeHumansGenetic Predisposition to DiseaseCognitive declineAlleleGeneAgedAged 80 and overGeneticsPolymorphism GeneticGeneral NeuroscienceAge FactorsAcute-phase proteinGenetic VariationAPOE IL-10 ACT HMGCR IL-1alpha IL-1beta TNF-alpha IFN-gamma IL-6 SNPs Grade of memebership Genetic risk profile Alzheimer's diseaseMiddle AgedUp-RegulationFemaleNeurology (clinical)Gene polymorphismInflammation MediatorsGeriatrics and GerontologyDevelopmental Biology
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Multi-objective memetic optimization for the bi-objective obnoxious p -median problem

2018

Abstract Location problems have been studied extensively in the optimization literature, the p-median being probably one of the most tackled models. The obnoxious p-median is an interesting variant that appears in the context of hazardous location. The aim of this paper is to formally introduce a bi-objective optimization model for this problem, in which a solution consists of a set of p locations, and two conflicting objectives arise. On the one hand, the sum of the minimum distance between each client and their nearest open facility and, on the other hand, the dispersion among facilities. Both objective values should be kept as large as possible for a convenient location of dangerous faci…

Mathematical optimization021103 operations researchInformation Systems and Managementbusiness.industryComputer scienceCrossoverFeasible region0211 other engineering and technologiesContext (language use)02 engineering and technologySpace (commercial competition)Management Information SystemsSet (abstract data type)Artificial IntelligenceMutation (genetic algorithm)0202 electrical engineering electronic engineering information engineeringMemetic algorithm020201 artificial intelligence & image processingLocal search (optimization)businessSoftwareKnowledge-Based Systems
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Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem

2015

Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…

Mathematical optimizationComputer scienceAnt colony optimization algorithmsMathematicsofComputing_NUMERICALANALYSISMemetic algorithmAnt colony2-optComputingMethodologies_ARTIFICIALINTELLIGENCESwarm intelligenceMetaheuristicTravelling salesman problemParallel metaheuristic
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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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Lower and upper bounds for the mixed capacitated arc routing problem

2006

This paper presents a linear formulation, valid inequalities, and a lower bounding procedure for the mixed capacitated arc routing problem (MCARP). Moreover, three constructive heuristics and a memetic algorithm are described. Lower and upper bounds have been compared on two sets of randomly generated instances. Computational results show that the average gaps between lower and upper bounds are 0.51% and 0.33%, respectively.

Mathematical optimizationLower boundGeneral Computer Science0211 other engineering and technologiesMixed graphHeuristic02 engineering and technologyManagement Science and Operations ResearchUpper and lower boundsBounding overwatchMixed graph0502 economics and businessCapacitated arc routing problemConstructive heuristicMathematics050210 logistics & transportation021103 operations researchWaste collectionHeuristic05 social sciencesMemetic algorithm[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Cutting plane[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModeling and SimulationMemetic algorithmArc routingCutting-plane method
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Memetic Variation Local Search vs. Life-Time Learning in Electrical Impedance Tomography

2009

In this article, various metaheuristics for a numerical optimization problem with application to Electric Impedance Tomography are tested and compared. The experimental setup is composed of a real valued Genetic Algorithm, the Differential Evolution, a self adaptive Differential Evolution recently proposed in literature, and two novel Memetic Algorithms designed for the problem under study. The two proposed algorithms employ different algorithmic philosophies in the field of Memetic Computing. The first algorithm integrates a local search into the operations of the offspring generation, while the second algorithm applies a local search to individuals already generated in the spirit of life-…

Mathematical optimizationMeta-optimizationOptimization problembusiness.industryFitness landscapeDifferential evolutionComputer Science::Neural and Evolutionary ComputationGenetic algorithmMemetic algorithmLocal search (optimization)businessMetaheuristicMathematics
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Memetic Algorithms in Engineering and Design

2012

When dealing with real-world applications, one often faces non-linear and nondifferentiable optimization problems which do not allow the employment of exact methods. In addition, as highlighted in [104], popular local search methods (e.g. Hooke-Jeeves, Nelder Mead and Rosenbrock) can be ill-suited when the real-world problem is characterized by a complex and highly multi-modal fitness landscape since they tend to converge to local optima. In these situations, population based meta-heuristics can be a reasonable choice, since they have a good potential in detecting high quality solutions. For these reasons, meta-heuristics, such as Genetic Algorithms (GAs), Evolution Strategy (ES), Particle …

Mathematical optimizationOptimization problemLocal optimumbusiness.industryComputer scienceAnt colony optimization algorithmsMathematicsofComputing_NUMERICALANALYSISParticle swarm optimizationMemetic algorithmLocal search (optimization)businessEvolution strategyTabu search
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A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows

2010

In this paper, we present an effective memetic algorithm for the vehicle routing problem with time windows (VRPTW). The paper builds upon an existing edge assembly crossover (EAX) developed for the capacitated VRP. The adjustments of the EAX operator and the introduction of a novel penalty function to eliminate violations of the time window constraint as well as the capacity constraint from offspring solutions generated by the EAX operator have proven essential to the heuristic's performance. Experimental results on Solomon's and Gehring and Homberger benchmarks demonstrate that our algorithm outperforms previous approaches and is able to improve 184 best-known solutions out of 356 instance…

Mathematical optimizationSDG 16 - PeaceGeneral Computer ScienceHeuristic (computer science)EconomicsSDG 16 - Peace Justice and Strong InstitutionsCrossoverMemetic algorithmManagement Science and Operations ResearchEAX mode/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsPenalty functionVehicle routingJustice and Strong InstitutionsModeling and SimulationVehicle routing problemMemetic algorithmPenalty methodEnhanced Data Rates for GSM EvolutionRouting (electronic design automation)AlgorithmTime windowsMathematicsComputers and Operations Research
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Differential Evolution with Scale Factor Local Search for Large Scale Problems

2010

This chapter proposes the integration of fitness diversity adaptation techniques within the parameter setting of Differential Evolution (DE). The scale factor and crossover rate are encoded within each genotype and self-adaptively updated during the evolution by means of a probabilistic criterion which takes into account the diversity properties of the entire population. The population size is also adaptively controlled by means of a novel technique based on a measurement of the fitness diversity. An extensive experimental setup has been implemented by including multivariate problems and hard to solve fitness landscapes. A comparison of the performance has been conducted by considering a st…

Mathematical optimizationScale (ratio)Computer sciencebusiness.industryRobustness (computer science)Differential evolutionMemetic algorithmLocal search (optimization)Scale factorbusinessMetaheuristicEvolutionary computation
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