Search results for "ALGORITHMS"

showing 10 items of 1716 documents

Indexing a sequence for mapping reads with a single mismatch

2014

Mapping reads against a genome sequence is an interesting and useful problem in computational molecular biology and bioinformatics. In this paper, we focus on the problem of indexing a sequence for mapping reads with a single mismatch. We first focus on a simpler problem where the length of the pattern is given beforehand during the data structure construction. This version of the problem is interesting in its own right in the context of the next generation sequencing. In the sequel, we show how to solve the more general problem. In both cases, our algorithm can construct an efficient data structure in time and space and can answer subsequent queries in time. Here, n is the length of the s…

Computer sciencegenome sequenceGeneral Mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]General Physics and AstronomyContext (language use)algorithmscomputer.software_genrePattern matchingSequenceSearch engine indexingGeneral EngineeringWildcard characterArticlescomputer.file_formatConstruct (python library)Data structuremapping readspattern matchingComputingMethodologies_DOCUMENTANDTEXTPROCESSINGData mining[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]Focus (optics)mismatchcomputerAlgorithmindexingPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
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An Online Observer for Minimization of Pulsating Torque in SMPM Motors.

2015

A persistent problem of surface mounted permanent magnet (SMPM) motors is the non-uniformity of the developed torque. Either the motor design or the motor control needs to be improved in order to minimize the periodic disturbances. This paper proposes a new control technique for reducing periodic disturbances in permanent magnet (PM) electro-mechanical actuators, by advancing a new observer/estimator paradigm. A recursive estimation algorithm is implemented for online control. The compensating signal is identified and added as feedback to the control signal of the servo motor. Compensation is evaluated for different values of the input signal, to show robustness of the proposed method.

Computer sciencelcsh:Medicine02 engineering and technologyBioinformaticsInfographics01 natural sciences0202 electrical engineering electronic engineering information engineeringlcsh:Science010302 applied physicsMultidisciplinaryFourier AnalysisPhysicsApplied MathematicsSimulation and ModelingClassical MechanicsSignal Processing Computer-AssistedEquipment DesignSignal FilteringRotorsPhysical SciencesMagnetsEngineering and TechnologyGraphsAlgorithmsResearch ArticleComputer and Information SciencesObserver (quantum physics)Materials ScienceServomotorResearch and Analysis MethodsOnline SystemsFeedbackMagneticsMotionRobustness (computer science)Control theory0103 physical sciencesTorqueEnginesMaterials by AttributeMechanical EngineeringData Visualization020208 electrical & electronic engineeringlcsh:RMotor controlModels TheoreticalBandpass FiltersVibrationTorqueDirect torque controlMagnetSignal Processinglcsh:QActuatorMathematicsPLoS ONE
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Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition

2019

Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…

Computer sciencelinked CP tensor decomposition (LCPTD)02 engineering and technologySignal-to-noise ratiotensor decompositionConvergence (routing)0202 electrical engineering electronic engineering information engineeringDecomposition (computer science)TensorHigh orderta113konvergenssiconvergencesignal to noise ratio020206 networking & telecommunicationsbrain modelinghierarchical alternating least squares (HALS)Alternating least squaresCore (graph theory)coupled tensor decomposition020201 artificial intelligence & image processingAlgorithmsignal processing algorithmselectroencephalographymathematical modelCurse of dimensionality
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Evaluation of the registration of temporal series of contrast-enhanced perfusion magnetic resonance 3D images of the liver.

2011

The registration of 2D and 3D images is one of the key tasks in medical image processing and analysis. Accurate registration is a crucial preprocessing step for many tasks; consequently, the evaluation of its accuracy becomes necessary. Unfortunately, this is a difficult task, especially when no golden pattern (true result) is available and when the signal values may have changed between successive images to be registered. This is the case this paper deals with: we have a series of 3D images, magnetic resonance images (MRI) of the liver and adjacent areas that have to be registered. They have been taken while a contrast is diffused through the liver tissue, so intensity of each observed poi…

Computer sciencemedia_common.quotation_subjectContrast MediaHealth InformaticsImage processingImaging Three-DimensionalLiver tissuemedicineContrast (vision)HumansComputer visionPoint (geometry)media_commonGround truthmedicine.diagnostic_testbusiness.industryProcess (computing)Magnetic resonance imagingMagnetic Resonance ImagingComputer Science ApplicationsLiverArtificial intelligencebusinessPerfusionSoftwareAlgorithmsComputer methods and programs in biomedicine
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Lead Reconstruction Using Artificial Neural Networks for Ambulatory ECG Acquisition

2021

One of the most powerful techniques to diagnose cardiovascular diseases is to analyze the electrocardiogram (ECG). To increase diagnostic sensitivity, the ECG might need to be acquired using an ambulatory system, as symptoms may occur during a patient’s daily life. In this paper, we propose using an ambulatory ECG (aECG) recording device with a low number of leads and then estimating the views that would have been obtained with a standard ECG location, reconstructing the complete Standard 12-Lead System, the most widely used system for diagnosis by cardiologists. Four approaches have been explored, including Linear Regression with ECG segmentation and Artificial Neural Networks (ANN). The b…

Computer sciencestandard 12-lead systemTP1-1185electrocardiogramBiochemistryArticlelead reconstructionAnalytical ChemistryElectrocardiographyLinear regressionHumansSegmentationSensitivity (control systems)cardiovascular diseasesElectrical and Electronic EngineeringLead (electronics)InstrumentationArtificial neural networkbusiness.industryChemical technologyReconstruction algorithmPattern recognitionSignal Processing Computer-AssistedAtomic and Molecular Physics and Opticscardiovascular diseasesambulatory monitoringAmbulatory ECGElectrocardiography AmbulatoryArtificial intelligenceNeural Networks ComputerEcg signalbusinessartificial neural networkAlgorithmsSensors (Basel, Switzerland)
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Morse Description and Geometric Encoding of Digital Elevation Maps

2004

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum …

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingData_CODINGANDINFORMATIONTHEORYSensitivity and SpecificityPattern Recognition AutomatedPhysics::GeophysicsImaging Three-DimensionalCompression (functional analysis)Image Interpretation Computer-AssistedComputer SimulationComputer visionMorse theoryMathematicsLossless compressionbusiness.industryReproducibility of ResultsNumerical Analysis Computer-AssistedSignal Processing Computer-AssistedData CompressionImage EnhancementTopographic mapComputer Graphics and Computer-Aided DesignArtificial intelligencebusinessAlgorithmAlgorithmsSoftwareData compressionImage compressionInterpolationIEEE Transactions on Image Processing
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Quasi-continuous-time impurity solver for the dynamical mean-field theory with linear scaling in the inverse temperature

2013

We present an algorithm for solving the self-consistency equations of the dynamical mean-field theory (DMFT) with high precision and efficiency at low temperatures. In each DMFT iteration, the impurity problem is mapped to an auxiliary Hamiltonian, for which the Green function is computed by combining determinantal quantum Monte Carlo (BSS-QMC) calculations with a multigrid extrapolation procedure. The method is numerically exact, i.e., yields results which are free of significant Trotter errors, but retains the BSS advantage, compared to direct QMC impurity solvers, of linear (instead of cubic) scaling with the inverse temperature. The new algorithm is applied to the half-filled Hubbard mo…

Condensed Matter::Quantum GasesModels StatisticalStrongly Correlated Electrons (cond-mat.str-el)Hubbard modelQuantum Monte CarloTemperatureExtrapolationFOS: Physical sciencesMott transitionCondensed Matter - Strongly Correlated Electronssymbols.namesakeMultigrid methodQuantum mechanicsLinear ModelssymbolsLinear scaleThermodynamicsComputer SimulationCondensed Matter::Strongly Correlated ElectronsStatistical physicsHamiltonian (quantum mechanics)ScalingAlgorithmsMathematicsPhysical Review E
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On general conditional prevision assessments

2009

In this paper we consider general conditional random quantities of the kind $X|Y$, where $X$ and $Y$ are finite discrete random quantities. Then, we introduce the notion of coherence for conditional prevision assessments on finite families of general conditional random quantities. Moreover, we give a compound prevision theorem and we examine the relation between the previsions of $X|Y$ and $Y|X$. Then, we give some results on random gains and, by a suitable alternative theorem, we obtain a characterization of coherence. We also propose an algorithm for the checking of coherence. Finally, we briefly examine the case of imprecise conditional prevision assessments by introducing the notions of…

Conditional random quantities; coherence; conditional prevision assessments; random gain; alternative theorems; algorithms; imprecise assessments; generalized and total coherence.Settore MAT/06 - Probabilita' E Statistica Matematicarandom gainConditional events general conditional random quantitiesgeneral conditional prevision assessments generalized compound prevision theorem generalized Bayes TheoremConditional random quantitiesalgorithmsimprecise assessmentsalternative theoremsgeneralized and total coherencecoherenceconditional prevision assessments
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Automated detection of patient movement during a CBCT scan based on the projection data.

2015

Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evalu…

Cone beam computed tomographyComputer scienceMovementOptical flowVideo RecordingSensitivity and SpecificityPathology and Forensic MedicineAccelerationSoftwareImaging Three-DimensionalHumansRadiology Nuclear Medicine and imagingDentistry (miscellaneous)Computer visionSensitivity (control systems)Projection (set theory)Pixelbusiness.industryPhantoms ImagingFrame (networking)Cone-Beam Computed TomographyFeasibility StudiesRadiographic Image Interpretation Computer-AssistedSurgeryArtificial intelligenceOral SurgerybusinessArtifactsAlgorithmsSoftwareOral surgery, oral medicine, oral pathology and oral radiology
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On the Robust Synthesis of Logical Consensus Algorithms for Distributed Intrusion Detection

2013

We introduce a novel consensus mechanism by which the agents of a network can reach an agreement on the value of a shared logical vector function depending on binary input events. Based on results on the convergence of finite--state iteration systems, we provide a technique to design logical consensus systems that minimize the number of messages to be exchanged and the number of steps before consensus is reached, and that can tolerate a bounded number of failed or malicious agents. We provide sufficient joint conditions on the input visibility and the communication topology for the method's applicability. We describe the application of our method to two distributed network intrusion detecti…

Consensus algorithmTheoretical computer scienceComputer scienceDistributed computingVisibility (geometry)Binary numberValue (computer science)Topology (electrical circuits)Computer Science::Multiagent SystemsSettore ING-INF/04 - AutomaticaControl and Systems EngineeringConsensus distributed algorithms intrusion detection security.Bounded functionConvergence (routing)Electrical and Electronic EngineeringVector-valued function
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