Search results for "HIDDEN"

showing 10 items of 210 documents

Hidden Pursuits: Evaluating Gaze-selection via Pursuits when the Stimuli's Trajectory is Partially Hidden

2018

The idea behind gaze interaction using Pursuits is to leverage the human's smooth pursuit eye movements performed when following moving targets. However, humans can also anticipate where a moving target would reappear if it temporarily hides from their view. In this work, we investigate how well users can select targets using Pursuits in cases where the target's trajectory is partially invisible (HiddenPursuits): e.g., can users select a moving target that temporarily hides behind another object? Although HiddenPursuits was not studied in the context of interaction before, understanding how well users can perform HiddenPursuits presents numerous opportunities, particularly for small interfa…

Computer scienceContext (language use)ComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technologySmooth pursuitsilmänliikkeetUser experience designLeverage (negotiation)Human–computer interactiondisplays0202 electrical engineering electronic engineering information engineeringSelection (linguistics)0501 psychology and cognitive sciencesmotion correlation050107 human factorsta113business.industry05 social sciences020207 software engineeringGazeObject (philosophy)näyttölaitteethidden trajectorysmooth pursuitTrajectorykatsebusinessärsykkeet
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Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

2017

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation bo…

Computer scienceGeneral Physics and AstronomySolverCondensed Matter - Soft Condensed Matter01 natural sciencesThermostatBottleneck010305 fluids & plasmaslaw.invention010101 applied mathematicsMolecular dynamicsHardware and ArchitectureDiscontinuous Galerkin methodlaw0103 physical sciencesSoft matterStatistical physics0101 mathematicsShear flowHidden Markov model
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Joint Usage of Dynamic Sensitivity Control and Time Division Multiple Access in Dense 802.11ax Networks

2016

It is well known that in case of high density deployments, Wi-Fi networks suffer from serious performance impairments due to hid- den and exposed nodes. The problem is explicitly considered by the IEEE 802.11ax developers in order to improve spectrum efficiency. In this pa- per, we propose and evaluate the joint usage of dynamic sensitivity con- trol (DSC) and time division multiple access (TDMA) for improving the spectrum allocation among overlapping 802.11ax BSSs. To validate the solution, apart from simulation, we used a testbed based on the Wireless MAC Processor (WMP), a prototype of a programmable wireless card.

Computer scienceReal-time computingTime division multiple access050801 communication & media studies02 engineering and technologyFrequency allocation0508 media and communications0202 electrical engineering electronic engineering information engineeringWirelessDense deploymentIEEE 802.11axHidden node problembusiness.industryExposed node problemSettore ING-INF/03 - TelecomunicazioniDynamic sensitivity control05 social sciencesTestbedSpectral efficiencyExposed node problemIEEE 802.11axTDMA020201 artificial intelligence & image processingHidden node problembusinessComputer network
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Algorithmic Aspects of Speech Recognition: A Synopsis

2000

Speech recognition is an area with a sizable literature, but there is little discussion of the topic within the computer science algorithms community. Since many of the problems arising in speech recognition are well suited for algorithmic studies, we present them in terms familiar to algorithm designers. Such cross fertilization can breed fresh insights from new perspectives. This material is abstracted from A. L. Buchsbaum and R. Giancarlo, Algorithmic Aspects of Speech Recognition: An Introduction, ACM Journal of Experimental Algorithmics, Vol. 2, 1997, http://www.jea.acm.org.

Computer scienceSpeech recognitionSpeech corpusHidden Markov modelGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)
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A Bayesian-optimal principle for learner-friendly adaptation in learning games

2010

Abstract Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predic…

Computer sciencebusiness.industryApplied MathematicsE-learning (theory)05 social sciencesBayesian probability050301 educationMulti-task learningMachine learningcomputer.software_genre050105 experimental psychologyTask (project management)0501 psychology and cognitive sciencesAdaptive learningArtificial intelligenceHidden Markov modelAdaptation (computer science)business0503 educationcomputerGeneral PsychologyDynamic Bayesian networkJournal of Mathematical Psychology
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Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks

2019

Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in …

Computer sciencebusiness.industryAssociation (object-oriented programming)Reliability (computer networking)05 social sciences050801 communication & media studiesMachine learningcomputer.software_genreNetwork congestion0508 media and communicationsEnodeB0502 economics and business050211 marketingArtificial intelligenceState (computer science)Hidden Markov modelbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550computer5GData transmissionICC 2019 - 2019 IEEE International Conference on Communications (ICC)
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Automatic place detection and localization in autonomous robotics

2007

This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as …

Computer sciencebusiness.industryFeature extractionRoboticsComputer Science Applications1707 Computer Vision and Pattern RecognitionMixture modelMachine learningcomputer.software_genreObject detectionsymbols.namesakeControl and Systems EngineeringsymbolsRobotUnsupervised learningArtificial intelligenceHidden Markov modelbusinessGaussian processcomputerSoftware1707
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A Sub-Symbolic Approach to Word Modelling for Domain Specific Speech Recognition

2006

In this work a sub-symbolic technique for automatic, data driven language models construction is presented. Such a technique can be used to arrange a language-modelling module, which can be easily integrated in existing speech recognition architectures, such as the well-found HTK architecture. The proposed technique takes advantages from both the traditional LSA approach and from a novel application of a probability space metric known as "Hellinger's distance". Experimental trials are also presented, in order to validate the proposed approach.

Computer sciencebusiness.industrySpeech recognitionMachine learningcomputer.software_genreDomain (software engineering)Speech enhancementMetric (mathematics)Artificial intelligenceLanguage modelHellinger distanceHidden Markov modelbusinesscomputerNatural languageWord (computer architecture)Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)
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Detection of TV commercials

2004

This paper presents a system that labels TV shots either as commercial or program shots. The system uses two observations: logo presence and shot duration. These observations are modeled using HMMs, and a Viterbi decoder is finally used for shot labeling. The system has been tested on several hours of real video, achieving more than 99% correct labeling.

Computer sciencebusiness.industrySpeech recognitionShot (filmmaking)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONViterbi algorithmsymbols.namesakeComputingMethodologies_PATTERNRECOGNITIONViterbi decoderPattern recognition (psychology)symbolsComputer visionArtificial intelligenceHidden Markov modelbusinessDecoding methods2004 IEEE International Conference on Acoustics, Speech, and Signal Processing
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Hidden attractors on one path : Glukhovsky-Dolzhansky, Lorenz, and Rabinovich systems

2017

In this report, by the numerical continuation method we visualize and connect hidden chaotic sets in the Glukhovsky-Dolzhansky, Lorenz and Rabinovich systems using a certain path in the parameter space of a Lorenz-like system.

Computer sciencechaosChaoticFOS: Physical sciencesPhysics::Data Analysis; Statistics and ProbabilityParameter space01 natural sciences010305 fluids & plasmasRabinovich systemLorenz system0103 physical sciencesAttractorGlukhovsky–Dolzhansky systemApplied mathematics010301 acousticsEngineering (miscellaneous)kaaosteoriaApplied Mathematicsta111Lorenz-like systemNonlinear Sciences - Chaotic DynamicsNonlinear Sciences::Chaotic DynamicsNumerical continuationModeling and SimulationPath (graph theory)numeerinen analyysiChaotic Dynamics (nlin.CD)hidden attractorInternational Journal of Bifurcation and Chaos
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