Search results for "Linear Algebra."

showing 10 items of 552 documents

On the ‘expanded local mode’ approach applied to the methane molecule: isotopic substitution CH2D2←CH4

2011

On the basis of a compilation of the ‘expanded local mode’ model and the general isotopic substitution theory, sets of simple analytical relations between different spectroscopic parameters (harmonic frequencies, ωλ, anharmonic coefficients, x λμ, ro-vibrational coefficients, , different kinds of Fermi- and Coriolis-type interaction parameters) of the CH2D2 molecule are derived. All of them are expressed as simple functions of a few initial spectroscopic parameters of the mother, CH4, molecule. Test calculations with the derived isotopic relations show that, in spite of a total absence of initial information about the CH2D2 species, the numerical results of the calculations have a very good…

010304 chemical physicsBasis (linear algebra)ChemistrySubstitution (logic)AnharmonicityBiophysicsThermodynamics010402 general chemistryCondensed Matter Physics01 natural sciences0104 chemical sciencesComputational chemistryAb initio quantum chemistry methodsSimple (abstract algebra)Simple function0103 physical sciencesMoleculePhysics::Chemical PhysicsPhysical and Theoretical ChemistryMolecular BiologyFermi Gamma-ray Space TelescopeMolecular Physics
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Survival and gene expression under different temperature and humidity regimes in ants

2017

Short term variation in environmental conditions requires individuals to adapt via changes in behavior and/or physiology. In particular variation in temperature and humidity are common, and the physiological adaptation to changes in temperature and humidity often involves alterations in gene expression, in particular that of heat-shock proteins. However, not only traits involved in the resistance to environmental stresses, but also other traits, such as immune defenses, may be influenced indirectly by changes in temperature and humidity. Here we investigated the response of the ant F. exsecta to two temperature regimes (20 degrees C & 25 degrees C), and two humidity regimes (50% & 75%), for…

0106 biological sciences0301 basic medicineAtmospheric ScienceympäristöAcclimatizationGene Expressionlcsh:MedicinemuutosALFALFA LEAFCUTTING BEEBiochemistryImmune Receptors01 natural sciencesEndocrinologyACCLIMATIONmuurahaisetGene expressionMedicine and Health SciencesIMMUNE-RESPONSEInsulinTRANSCRIPTIONgeeniekspressiolcsh:SciencePOPULATIONHeat-Shock ProteinsProtein MetabolismsopeutuminenPrincipal Component Analysiseducation.field_of_studyImmune System ProteinsMultidisciplinaryBehavior AnimalEcologyolosuhteetTemperaturefood and beveragesANThumanitiesInsectsimmuunijärjestelmä1181 Ecology evolutionary biologyPhysical SciencesMEGACHILE-ROTUNDATAlämpötilaympäristönmuutoksetResearch ArticleNutrient and Storage ProteinsSignal TransductionArthropodaImmunologyPopulationZoologyBiology010603 evolutionary biologyAcclimatization03 medical and health sciencesMeteorologyTwo temperatureStress PhysiologicalGeneticsAnimalseducationGeneProportional Hazards ModelsDiabetic EndocrinologyAntsBEAUVERIA-BASSIANAGene Expression Profilinglcsh:ROrganismshumidityBiology and Life SciencesProteinsHumiditytemperatureHumidityEigenvaluesCell BiologyDESICCATIONInvertebratesHymenopteraHormonesMetabolismAlgebra030104 developmental biologyGene Expression RegulationLinear AlgebraDROSOPHILA-MELANOGASTERkosteusEarth Sciencesgene expressionta1181lcsh:QFormica exsectaDesiccationRESISTANCEMathematics
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Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

0209 industrial biotechnologyComputer scienceCognitive Neuroscienceneuraalilaskentaneuroverkot02 engineering and technologyrandomized learning machinesSet (abstract data type)extreme learning machine020901 industrial engineering & automationArtificial Intelligenceextreme minimal learning machine0202 electrical engineering electronic engineering information engineeringExtreme learning machineta113Training setBasis (linear algebra)Model selectionminimal learning machineOverlearningComputer Science ApplicationskoneoppiminenTransformation (function)020201 artificial intelligence & image processingAlgorithmNeurocomputing
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A theoretical framework for product relationships description over space and time in integrated design

2016

ABSTRACTThis paper presents a novel qualitative description theory in the context of integrated design, which here incorporates assembly sequence planning in the early product design stages (also called assembly oriented design – AOD). Based on a literature review of current AOD approaches, product models and mereotopology-based theories, the authors introduce a promising mereotopological theory which enables the formal product relationships description in integrated design by introducing an emerging framework, four-dimensionalism (i.e. perdurantism in philosophy). The proposed efforts aim at providing a concrete basis for describing the evolution of spatial entities (i.e. product parts) an…

0209 industrial biotechnologyIntegrated designInterpretation (logic)Basis (linear algebra)Product designComputer scienceGeneral EngineeringContext (language use)02 engineering and technology020901 industrial engineering & automationProduct (mathematics)0202 electrical engineering electronic engineering information engineeringSystems engineering020201 artificial intelligence & image processingPerdurantismMereotopologyJournal of Engineering Design
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Periodic Controls in Step 2 Strictly Convex Sub-Finsler Problems

2020

We consider control-linear left-invariant time-optimal problems on step 2 Carnot groups with a strictly convex set of control parameters (in particular, sub-Finsler problems). We describe all Casimirs linear in momenta on the dual of the Lie algebra. In the case of rank 3 Lie groups we describe the symplectic foliation on the dual of the Lie algebra. On this basis we show that extremal controls are either constant or periodic. Some related results for other Carnot groups are presented. peerReviewed

0209 industrial biotechnologyPure mathematicsRank (linear algebra)variaatiolaskenta02 engineering and technology01 natural sciencesdifferentiaaligeometriaoptimal controlsymbols.namesake020901 industrial engineering & automationMathematics (miscellaneous)sub-Finsler geometryPontryagin maximum principleLie algebra0101 mathematicsMathematicsLie groups010102 general mathematicsLie groupBasis (universal algebra)matemaattinen optimointiFoliationsäätöteoriasymbolsCarnot cycleConvex functionSymplectic geometryRegular and Chaotic Dynamics
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Pipeline Monitoring Architecture Based on Observability and Controllability Analysis

2019

Recently many techniques with different applicability have been developed for damage detection in the pipeline. The pipeline system is designed as a distributed parameter system, where the state space of the distributed parameter system has infinite dimension. This paper is dedicated to the problem of observability as well as controllability analysis in the pipeline systems. Some theorems are presented in order to test the observability and controllability of the system. Computing the rank of the controllability and observability matrix is carried out using Matlab.

0209 industrial biotechnologyRank (linear algebra)Computer sciencePipeline (computing)020208 electrical & electronic engineering02 engineering and technologyPipeline transportControllability020901 industrial engineering & automationControl theoryDistributed parameter system0202 electrical engineering electronic engineering information engineeringState spaceObservabilityMATLABcomputercomputer.programming_language2019 IEEE International Conference on Mechatronics (ICM)
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Adjusted bat algorithm for tuning of support vector machine parameters

2016

Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…

0209 industrial biotechnologyWake-sleep algorithmActive learning (machine learning)Computer scienceStability (learning theory)Linear classifier02 engineering and technologySemi-supervised learningcomputer.software_genreCross-validationRelevance vector machineKernel (linear algebra)020901 industrial engineering & automationLeast squares support vector machine0202 electrical engineering electronic engineering information engineeringMetaheuristicBat algorithmStructured support vector machinebusiness.industrySupervised learningOnline machine learningParticle swarm optimizationPattern recognitionPerceptronGeneralization errorSupport vector machineKernel methodComputational learning theoryMargin classifierHyperparameter optimization020201 artificial intelligence & image processingData miningArtificial intelligenceHyper-heuristicbusinesscomputer2016 IEEE Congress on Evolutionary Computation (CEC)
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Comparison of fully non-stationary artificial accelerogram generation methods in reproducing seismicity at a given site

2020

Abstract Seismic input modelling is a crucial step when Non-Linear Time-History Analyses (NLTHAs) are performed, the seismic response of structures being highly responsive to the input employed. When natural accelerograms able to represent local seismicity are not available, the use of generated accelerograms is an efficient solution for input modelling. The aim of the present paper is to compare four methods for generating fully non-stationary artificial accelerograms on the basis of a target spectrum, identified using seven recorded accelerograms registered in the neighbourhood of the construction site during a single event, assumed as target accelerograms. For each method, seven accelero…

0211 other engineering and technologiesSoil Science020101 civil engineeringSpectrum-compatible02 engineering and technologyInduced seismicity0201 civil engineeringSet (abstract data type)Intensity measure parametermedicinePoint (geometry)Seismic site characteristic021101 geological & geomatics engineeringCivil and Structural EngineeringEvent (probability theory)Basis (linear algebra)business.industryFully non-stationaryStiffnessStructural engineeringGeotechnical Engineering and Engineering GeologySettore ICAR/09 - Tecnica Delle CostruzioniArtificial accelerogrammedicine.symptombusinessEnergy (signal processing)GeologySoil Dynamics and Earthquake Engineering
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A Novel Intelligent Technique for Product Acceptance Process Optimization on the Basis of Misclassification Probability in the Case of Log-Location-S…

2019

In this paper, to determine the optimal parameters of the product acceptance process under parametric uncertainty of underlying models, a new intelligent technique for optimization of product acceptance process on the basis of misclassification probability is proposed. It allows one to take into account all possible situations that may occur when it is necessary to optimize the product acceptance process. The technique is based on the pivotal quantity averaging approach (PQAA) which allows one to eliminate the unknown parameters from the problem and to use available statistical information as completely as possible. It is conceptually simple and easy to use. One of the most important featur…

021110 strategic defence & security studiesGeneralityMathematical optimizationBasis (linear algebra)Computer scienceScale (chemistry)0211 other engineering and technologiesProcess (computing)02 engineering and technologyPivotal quantityProduct (mathematics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingProcess optimizationParametric statistics
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Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative.

2016

In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall's subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgrap…

0301 basic medicinePharmacologyVertex (graph theory)Discrete mathematicsBasis (linear algebra)Bioinformatics01 natural sciences0104 chemical sciences010404 medicinal & biomolecular chemistry03 medical and health scienceschemistry.chemical_compoundMatrix (mathematics)030104 developmental biologychemistryModels ChemicalMolecular descriptorDrug DiscoveryPath (graph theory)Molecular graphRepresentation (mathematics)FuransAlgorithmsSoftwareEvent (probability theory)Current pharmaceutical design
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