Search results for "binary [black hole]"

showing 10 items of 170 documents

Integral binary Hamiltonian forms and their waterworlds

2018

We give a graphical theory of integral indefinite binary Hamiltonian forms $f$ analogous to the one by Conway for binary quadratic forms and the one of Bestvina-Savin for binary Hermitian forms. Given a maximal order $\mathcal O$ in a definite quaternion algebra over $\mathbb Q$, we define the waterworld of $f$, analogous to Conway's river and Bestvina-Savin's ocean, and use it to give a combinatorial description of the values of $f$ on $\mathcal O\times\mathcal O$. We use an appropriate normalisation of Busemann distances to the cusps (with an algebraic description given in an independent appendix), and the $\operatorname{SL}_2(\mathcal O)$-equivariant Ford-Voronoi cellulation of the real …

Mathematics - Differential GeometryPure mathematicsBinary number01 natural sciences[MATH.MATH-GR]Mathematics [math]/Group Theory [math.GR]waterworlddifferentiaaligeometriamaximal orderhyperbolic 5-space0103 physical sciences0101 mathematicsAlgebraic numberreduction theoryMathematicslukuteoriaMathematics - Number TheoryQuaternion algebra010102 general mathematicsHamilton-Bianchi groupryhmäteoriaOrder (ring theory)Mathematics::Geometric TopologyHermitian matrix[MATH.MATH-NT]Mathematics [math]/Number Theory [math.NT][MATH.MATH-DG]Mathematics [math]/Differential Geometry [math.DG]Binary quadratic form010307 mathematical physicsGeometry and Topologyrational quaternion algebraMathematics - Group Theorybinary Hamiltonian formHamiltonian (control theory)Conformal Geometry and Dynamics of the American Mathematical Society
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Matrix Shuffle- Exchange Networks for Hard 2D Tasks

2021

Convolutional neural networks have become the main tools for processing two-dimensional data. They work well for images, yet convolutions have a limited receptive field that prevents its applications to more complex 2D tasks. We propose a new neural model, called Matrix Shuffle-Exchange network, that can efficiently exploit long-range dependencies in 2D data and has comparable speed to a convolutional neural network. It is derived from Neural Shuffle-Exchange network and has O(log N) layers and O(N ^ 2 log N) total time and O(N^2) space complexity for processing a NxN data matrix. We show that the Matrix Shuffle-Exchange network is well-suited for algorithmic and logical reasoning tasks on …

Matrix (mathematics)Dependency (UML)ExploitComputer scienceReceptive fieldBinary logarithmConvolutional neural networkAlgorithmData matrix (multivariate statistics)Data modeling2021 International Joint Conference on Neural Networks (IJCNN)
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Autocorrelation in meter induction: the role of accent structure.

2006

The performance of autocorrelation-based meter induction was tested with two large collections of folk melodies, consisting of approximately 13 000 melodies for which the correct meters were available. The performance was measured by the proportion of melodies whose meter was correctly classified by a discriminant function. Furthermore, it was examined whether including different melodic accent types would improve the classification performance. By determining the components of the autocorrelation functions that were significant in the classification it was found that periodicity in note onset locations was the most important cue for the determination of meter. Of the melodic accents includ…

MelodyTime FactorsAcoustics and Ultrasonicsbusiness.industryVoice QualityAutocorrelationDiscriminant AnalysisPattern recognitionLinear discriminant analysisMusical acousticsAccent (music)Arts and Humanities (miscellaneous)Binary classificationDiscriminant function analysisTime PerceptionAuditory PerceptionVoiceMetreHumansArtificial intelligencebusinessPitch PerceptionMusicMathematicsThe Journal of the Acoustical Society of America
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A Nondifferentiable Optimization Approach to Ratio-Cut Partitioning

2003

We propose a new method for finding the minimum ratio-cut of a graph. Ratio-cut is NP-hard problem for which the best previously known algorithm gives an O(log n)-factor approximation by solving its dually related maximum concurrent flow problem.We formulate the minimum ratio-cut as a certain nondifferentiable optimization problem, and show that the global minimum of the optimization problem is equal to the minimum ratio-cut. Moreover, we provide strong symbolic computation based evidence that any strict local minimum gives an approximation by a factor of 2. We also give an efficient heuristic algorithm for finding a local minimum of the proposed optimization problem based on standard nondi…

Minimum k-cutMathematical optimizationOptimization problemSpatial networkCutBinary logarithmSymbolic computationConcurrent flowMathematicsRunning time
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Hemostatic agents in endodontic surgery of maxillary molars : a randomized controlled pilot study of polytetrafluoroethylene (PTFE) strips as an adju…

2019

Background Hemostasis is of critical importance in endodontic surgery. Studies on bleeding control in maxillary molars are scarce. The present study compares the efficacy of two hemostatic techniques in controlling bleeding in endodontic surgery. Material and Methods A randomized two-arm pilot study involving 30 patients with peri-radicular lesions in maxillary molars (first and second molars) was carried out including the following hemostatic agents: polytetrafluoroethylene (PTFE) strips as an adjunct to epinephrine impregnated gauze (test group; n = 15) and aluminum chloride (Expasyl™) (control; n = 15). Bleeding control was independently assessed by the surgeon and by two blinded observe…

MolarEpinephrineDentistryPilot ProjectsHemostaticsMandibular second molar03 medical and health scienceschemistry.chemical_compound0302 clinical medicinemedicineAluminum ChlorideHumansBinary logistic regression analysisGeneral DentistryPolytetrafluoroethyleneHemostatic AgentPolytetrafluoroethylenebusiness.industryHemostatic TechniquesResearch030206 dentistry:CIENCIAS MÉDICAS [UNESCO]MolarEndodontic surgeryEpinephrineOtorhinolaryngologychemistryHemostasisUNESCO::CIENCIAS MÉDICASSurgeryOral Surgerybusinessmedicine.drug
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Ion-ion correlation and charge reversal at titrating solid interfaces

2009

Confronting grand canonical titration Monte Carlo simulations (MC) with recently published titration and charge reversal (CR) experiments on silica surfaces by Dove et al. and van der Heyden it et al, we show that ion-ion correlations quantitatively explain why divalent counterions strongly promote surface charge which, in turn, eventually causes a charge reversal (CR). Titration and CR results from simulations and experiments are in excellent agreement without any fitting parameters. This is the first unambiguous evidence that ion-ion correlations are instrumental in the creation of highly charged surfaces and responsible for their CR. Finally, we show that charge correlations result in "a…

Monte Carlo methodFOS: Physical sciencesBinary compoundThermodynamics02 engineering and technologyCondensed Matter - Soft Condensed Matter010402 general chemistry01 natural sciencesIonchemistry.chemical_compoundComputational chemistryElectrochemistryTheoretical chemistryGeneral Materials ScienceSurface chargeSpectroscopyCondensed Matter - Statistical Mechanicschemistry.chemical_classificationStatistical Mechanics (cond-mat.stat-mech)Charge (physics)Surfaces and Interfaces021001 nanoscience & nanotechnologyCondensed Matter Physics0104 chemical sciences[ PHYS.PHYS.PHYS-CHEM-PH ] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]chemistryddc:540Soft Condensed Matter (cond-mat.soft)Titration[PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]Counterion0210 nano-technology
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Deep 3D Convolution Neural Network for Alzheimer’s Detection

2020

One of the most well-known and complex applications of artificial intelligence (AI) is Alzheimer’s detection, which lies in the field of medical imaging. The complexity in this task lies in the three-dimensional structure of the MRI scan images. In this paper, we propose to use 3D Convolutional Neural Networks (3D-CNN) for Alzheimer’s detection. 3D-CNNs have been a popular choice for this task. The novelty in our paper lies in the fact that we use a deeper 3D-CNN consisting of 10 layers. Also, with effectively training our model consisting of Batch Normalization layers that provide a regularizing effect, we don’t have to use any transfer learning. We also use the simple data augmentation te…

Multiclass classificationBinary classificationComputer sciencebusiness.industryDeep learningNormalization (image processing)Pattern recognitionApplications of artificial intelligenceArtificial intelligencebusinessTransfer of learningConvolutional neural networkField (computer science)
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Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logisti…

2018

In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an…

Multivariate Adaptive Regression Splines (MARS)hurricane IdaMultivariate adaptive regression splines010504 meteorology & atmospheric sciencesSettore GEO/04 - Geografia Fisica E GeomorfologiaBinary Logistic Regression (BLR)0208 environmental biotechnologyGeography Planning and Developmentlcsh:G1-92202 engineering and technologyMars Exploration ProgramDebris flowLogistic regression01 natural sciences020801 environmental engineeringDebris flowdebris flowsStatisticsEl SalvadorGeneral Earth and Planetary Scienceslandslide susceptibilitySettore GEO/05 - Geologia Applicatalcsh:Geography (General)Geology0105 earth and related environmental sciencesHungarian Geographical Bulletin
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GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM ap…

2019

Abstract In arid and semi-arid areas, groundwater resource is one of the most important water sources by the humankind. Knowledge of groundwater distribution over space, associated flow and basic exploitation measures can play a significant role in planning sustainable development, especially in arid and semi-arid areas. Groundwater potential mapping (GWPM) fits in this context as the tool used to predict the spatial distribution of groundwater. In this research we tested four GIS-based models for GWPM, consisting of: i) random forest (RF); ii) weight of evidence (WoE); iii) binary logistic regression (BLR); and iv) technique for order preference by similarity to ideal solution (TOPSIS) mul…

Multivariate statisticsEnvironmental EngineeringGeographic information system010504 meteorology & atmospheric sciencesContext (language use)Land coverBinary logistic regression010501 environmental sciences01 natural sciencesStatisticsEnvironmental ChemistrySemi-arid regionWaste Management and Disposal0105 earth and related environmental sciencesbusiness.industryTOPSISWeight of evidencePollution22/4 OA procedureWater resourcesThematic mapITC-ISI-JOURNAL-ARTICLEEnvironmental sciencebusinessDecision makingGroundwaterRandom forest
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ChemInform Abstract: Nb2Te3, a Niobium Sesquitelluride with Te22- Groups.

2010

The new binary compound Nb2Te3 was synthesized by reduction of NbTe2 with Ga metal; different from the formally analogous Ta2Te3 it crystallizes in the Mo2As3 structure type; based on the results of band structure calculations Nb2Te3 is metallic with quasi one-dimensional metal electronic properties.

NiobiumBinary compoundchemistry.chemical_elementGeneral MedicineStructure typeReduction (complexity)Metalchemistry.chemical_compoundchemistryvisual_artvisual_art.visual_art_mediumPhysical chemistryCondensed Matter::Strongly Correlated ElectronsElectronic band structureElectronic propertiesChemInform
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