Search results for "Multiplication"

showing 10 items of 83 documents

Micropropagation of Sicilian cultivars with an aim to preserve genetic diversity in hazelnut (Corylus avellana L.)

2018

The use of a small number of cultivars in agriculture can lead to a loss of agrobiodiversity. Since in vitro techniques are valuable tools for conserving plant biodiversity, an efficient micropropagation protocol for four Italian hazelnut cultivars, ‘Carrello’, ‘Ghirara’, ‘Minnulara’, and ‘Panottara’, was developed. The highest axillary bud survival was obtained after decontamination with 40 min 1% sodium hypochlorite followed by 40 min 0.1% sodium merthiolate in ‘Minnulara’ and ‘Ghirara’, while the 35þ35 min treatment was the best for ‘Carrello’ and ‘Panottara’. Shoot multiplication was higher in ‘Minnulara’ and ‘Ghirara’ when 6.6 lM N6-benzyladenine was used, even if some hyperhydric shoo…

0106 biological sciences0301 basic medicineBiodiversityindole-3-butyric acidPlant ScienceBiology01 natural sciences03 medical and health scienceschemistry.chemical_compoundCultivarN6-benzyladenineEcology Evolution Behavior and SystematicsDecontamination timeGenetic diversityshoot multiplicationbusiness.industryIndole-3-butyric acidlanguage.human_languageSettore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeHorticulture030104 developmental biologyMicropropagationchemistryrooting inductionAgriculturemetatopolinlanguageAgricultural biodiversitybusinessSicilian010606 plant biology & botanyPlant Biosystems - An International Journal Dealing with all Aspects of Plant Biology
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FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures

2020

Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…

020203 distributed computingSource codeIterative methodComputer sciencebusiness.industrymedia_common.quotation_subjectDeep learningInference02 engineering and technologyParallel computingConvolutional neural networkMatrix multiplicationARM architectureComputational Theory and MathematicsHardware and ArchitectureSignal Processing0202 electrical engineering electronic engineering information engineeringArtificial intelligencebusinessmedia_commonIEEE Transactions on Parallel and Distributed Systems
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Terrorism in the Website

2020

Without any doubt, terrorism causes higher levels of anxiety and very well enhances our fears as never before. The post 9/11 context witnesses the multiplication of xenophobic expressions, such as Islamophobia or tourist-phobia, only to name a few. These expressions result from a culture of intolerance, which not only was enrooted in the ideological core of western capitalism but was accelerated just after 9/11. Some voices emphasize the needs of employing technology to make this world a safer place. This chapter goes in a contradictory direction. The authors focus on the ethical limitations of technologies when they are subordinated to the ideals of zero-risk society. Echoing Sunstein and …

021110 strategic defence & security studiesInformation Systems and ManagementScrutinyComputer Networks and Communications05 social sciences0211 other engineering and technologiesContext (language use)02 engineering and technologyCriminology0506 political scienceHardware and ArchitecturePolitical scienceFundamentalismTerrorism050602 political science & public administrationmedicineAnxietyMultiplicationmedicine.symptomSafety Risk Reliability and QualitySafety ResearchSoftwareInternational Journal of Cyber Warfare and Terrorism
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Reverse-safe data structures for text indexing

2021

We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…

050101 languages & linguisticsComputer sciencedata structure02 engineering and technologyprivacySet (abstract data type)combinatoric0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesPattern matchingSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionialgorithmSettore INF/01 - Informatica05 social sciencesSearch engine indexingINF/01 - INFORMATICAdata miningData structureMatrix multiplicationcombinatoricsExponent020201 artificial intelligence & image processingdata structure; algorithm; combinatorics; de Bruijn graph; data mining; privacyAlgorithmAdversary modelde Bruijn graphInteger (computer science)
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Structure of locally convex quasi C * -algebras

2008

There are examples of C*-algebras A that accept a locally convex *-topology τ coarser than the given one, such that Ã[τ] (the completion of A with respect to τ) is a GB*-algebra. The multiplication of A[τ] may be or not be jointly continuous. In the second case, Ã[*] may fail being a locally convex *-algebra, but it is a partial *-algebra. In both cases the structure and the representation theory of Ã[τ] are investigated. If Ã+ τ denotes the τ-closure of the positive cone A+ of the given C*-algebra A, then the property Ā+ τ ∩ (-Ā+ τ) = {0} is decisive for the existence of certain faithful *-representations of the corresponding *-algebra Ã[τ]

46L05quasi *-algebrasGeneral Mathematicslocally convex quasi $C^*$-algebrasRegular polygonStructure (category theory)FOS: Physical sciencesContext (language use)Mathematical Physics (math-ph)quasi-positivityCombinatoricsunbounded *-representationsMultiplicationquasi ∗-algebras quasi-positivity locally convex quasi C ∗ -algebras unbounded ∗-representations.46K10Algebra over a field46K70Settore MAT/07 - Fisica MatematicaMathematical PhysicsTopology (chemistry)47L60MathematicsJournal of the Mathematical Society of Japan
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Does the left inferior parietal lobule contribute to multiplication facts?

2005

We report a single case, who presents with a selective and severe impairment for multiplication and division facts. His ability to retrieve subtraction and addition facts was entirely normal. His brain lesion affected the left superior temporal and to lesser extent in the left middle temporal gyri and the left precentral gyrus extending inferiorly to the pars opercularis of the left frontal lobe. Interestingly, the left supramarginal and angular gyri (SMG/AG) were spared. This finding realised a double dissociation with a previously reported patient, who despite lesions in the SMG/AG did not have a multiplication impairment (van Harskamp et al., 2002). The previously suggested crucial role …

AdultMaleCognitive NeuroscienceExperimental and Cognitive PsychologyLeft frontal lobeNeuropsychological Testsbehavioral disciplines and activitiesFunctional LateralityMental ProcessesLeft precentral gyrusParietal LobeHumansNeurologic ExaminationSettore M-PSI/02 - Psicobiologia E Psicologia FisiologicaLeft inferior parietal lobuledyscalculia arithmetical fact retrieval multiplication and division impairment left inferior parietal lobulesupramarginal and angular gyriParietal lobeSubtractionAnatomyMagnetic Resonance ImagingNeuropsychology and Physiological PsychologyReadingBrain InjuriesMultiplicationLeft superiorPsychologyMathematicsCognitive psychologyPars opercularisCortex; a journal devoted to the study of the nervous system and behavior
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Complex multiplication, Griffiths-Yukawa couplings, and rigidity for families of hypersurfaces

2003

Let M(d,n) be the moduli stack of hypersurfaces of degree d > n in the complex projective n-space, and let M(d,n;1) be the sub-stack, parameterizing hypersurfaces obtained as a d fold cyclic covering of the projective n-1 space, ramified over a hypersurface of degree d. Iterating this construction, one obtains M(d,n;r). We show that M(d,n;1) is rigid in M(d,n), although the Griffiths-Yukawa coupling degenerates for d<2n. On the other hand, for all d>n the sub-stack M(d,n;2) deforms. We calculate the exact length of the Griffiths-Yukawa coupling over M(d,n;r), and we construct a 4-dimensional family of quintic hypersurfaces, and a dense set of points in the base, where the fibres ha…

Algebra and Number TheoryDegree (graph theory)Mathematics - Complex Variables14D0514J3214D07Complex multiplicationYukawa potentialRigidity (psychology)14J70ModuliCombinatoricsAlgebraMathematics - Algebraic Geometry14J70; 14D05; 14D07; 14J32HypersurfaceMathematics::Algebraic GeometryMathematikFOS: MathematicsGeometry and TopologyComplex Variables (math.CV)Algebraic Geometry (math.AG)Stack (mathematics)Mathematics
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Partial $\ast$-algebras of distributions

2005

The problem of multiplying elements of the conjugate dual of certain kind of commutative generalized Hilbert algebras, which are dense in the set of C ∞ -vectors of a self-adjoint operator, is considered in the framework of the so-called duality method. The multiplication is defined by identifying each distribution with a multiplication operator acting on the natural rigged Hilbert space. Certain spaces, that are an

AlgebraDistribution (number theory)Multiplication operatorHermitian adjointGeneral MathematicsOperator (physics)Rigged Hilbert spaceUnitary operatorCommutative propertySelf-adjoint operatorMathematicsPublications of the Research Institute for Mathematical Sciences
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Bicausative matrices to measure structural change: Are they a good tool?

1999

The causative-matrix method to analyze temporal change assumes that a matrix transforms one Markovian transition matrix into another by a left multiplication of the first matrix; the method is demand-driven when applied to input-output economics. An extension is presented without assuming the demand-driven or supply-driven hypothesis. Starting from two flow matrices X and Y, two diagonal matrices are searched, one premultiplying and the second postmultiplying X, to obtain a result the closer as possible to Y by least squares. The paper proves that the method is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. Keywords : Input-Output ; Ch…

BiproportionBicausativePure mathematicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63jel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisLeast squaresMeasure (mathematics)Interpretation (model theory)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingSylvester's law of inertiaMatrix (mathematics)Diagonal matrixStatisticsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelseconomic theoryhumanities social sciencessciences humaines et socialesStochastic matrixStructural ChangeGeneral Social Scienceseconomics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57CausativeJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingChaosMultiplicationThe Annals of Regional Science
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Iterative sparse matrix-vector multiplication for accelerating the block Wiedemann algorithm over GF(2) on multi-graphics processing unit systems

2012

SUMMARY The block Wiedemann (BW) algorithm is frequently used to solve sparse linear systems over GF(2). Iterative sparse matrix–vector multiplication is the most time-consuming operation. The necessity to accelerate this step is motivated by the application of BW to very large matrices used in the linear algebra step of the number field sieve (NFS) for integer factorization. In this paper, we derive an efficient CUDA implementation of this operation by using a newly designed hybrid sparse matrix format. This leads to speedups between 4 and 8 on a single graphics processing unit (GPU) for a number of tested NFS matrices compared with an optimized multicore implementation. We further present…

Block Wiedemann algorithmComputer Networks and CommunicationsComputer scienceGraphics processing unitSparse matrix-vector multiplicationGPU clusterParallel computingGF(2)Computer Science ApplicationsTheoretical Computer ScienceGeneral number field sieveMatrix (mathematics)Computational Theory and MathematicsFactorizationLinear algebraMultiplicationComputer Science::Operating SystemsSoftwareInteger factorizationSparse matrixConcurrency and Computation: Practice and Experience
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