Search results for "Encoder"

showing 10 items of 61 documents

Observation and Processing of Instantaneous Frequency Variations During Bearing Tests

2020

Laboratory experiments have been performed on medium sized roller bearings with two levels of artificial damage. Recordings of long time series from accelerometers at a wide range of different radial loads and rotation speeds has been performed. Probably due to non-perfect performance of the control systems for the rotational speed or frequency, significant fluctuations were observed at all rotation speeds. The highest relative variation was observed at the lowest rotational speeds. These variations were recorded using a rotary encoder, which allows order tracking of the vibration signal. In real life condition monitoring, tachometers or rotary encoders are not always present, this can be d…

VibrationRotary encoderTachometerBearing (mechanical)Computer sciencelawAcousticsCondition monitoringRotational speedInstantaneous phaseOrder trackinglaw.invention
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Hierarchical Parallelization of an H.264/AVC Video Encoder

2006

Last generation video encoding standards increase computing demands in order to reach the limits on compression efficiency. This is particularly the case of H.264/AVC specification that is gaining interest in industry. We are interested in applying parallel processing to H.264 encoders in order to fulfill the computation requirements imposed by stressing applications like video on demand, videoconference, live broadcast, etc. Given a delivered video quality and bit rate, the main complexity parameters are image resolution, frame rate and latency. These parameters can still be pushed forward in such a way that special purpose hardware solutions are not available. Parallel processing based on…

VideoconferencingComputer scienceComputationMessage passingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONParallel computingLatency (engineering)computer.software_genreVideo qualityFrame rateEncoderImage resolutioncomputerInternational Symposium on Parallel Computing in Electrical Engineering (PARELEC'06)
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Using of a uncertainty model of an polyarticulated coordinates measuring arm to validate the measurement in a manufacturing processsus

2014

International audience; Coordinates Measuring Arms (CMA) are increasingly used to control industrial parts and are often an alternative to CMM controls that require conditions of laboratory measurement and involve significant costs. However, the control of uncertainties is often not guaranteed because the measurement process is complex and there is no standard for setting a framework qualification process of the measurement process.The proposed study, in this paper, is a first approach to model the measurement uncertainties of a CMA with contact sensor. The problem is complex because there are many sources of uncertainty, largely due to variability in the handling carried out by the operato…

[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]0209 industrial biotechnologyEngineeringMonte Carlo method02 engineering and technologyMetrology01 natural sciences010309 opticsCMA Modelling020901 industrial engineering & automationOperator (computer programming)Control theory0103 physical sciencesCalibration[SPI.MECA.GEME] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]SimulationGeneral Environmental Sciencebusiness.industryProcess (computing)UncertaintyCovarianceMetrology[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]NoiseGeneral Earth and Planetary SciencesbusinessEncoderMonte Carlo Method
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Presentations of constrained systems with unconstrained positions

2005

International audience; We give a polynomial-time construction of the set of sequences that satisfy a finite-memory constraint defined by a finite list of forbidden blocks, with a specified set of bit positions unconstrained. Such a construction can be used to build modulation/error-correction codes (ECC codes) like the ones defined by the Immink-Wijngaarden scheme in which certain bit positions are reserved for ECC parity. We give a lineartime construction of a finite-state presentation of a constrained system defined by a periodic list of forbidden blocks. These systems, called periodic-finite-type systems, were introduced by Moision and Siegel. Finally, we present a linear-time algorithm for con…

[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]finite-memory systemperiodic-finite-type (PFT) system[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]0102 computer and information sciences02 engineering and technologyLibrary and Information Sciences01 natural sciencesModulation coding0202 electrical engineering electronic engineering information engineeringMathematicsDiscrete mathematicsChannel codefinite-state encodermodulation codeDAWG020206 networking & telecommunicationsDirected graphDirected acyclic graphforbidden blockComputer Science ApplicationsFinite sequence010201 computation theory & mathematicscodeError detection and correctionrun-length limited (RLL) codesInformation SystemsCoding (social sciences)maximum transition run (MTR)
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Anomaly Detection and Classification of Household Electricity Data : A Time Window and Multilayer Hierarchical Network Approach

2022

With the increasing popularity of the smart grid, huge volumes of data are gathered from numerous sensors. How to classify, store, and analyze massive datasets to facilitate the development of the smart grid has recently attracted much attention. In particular, with the popularity of household smart meters and electricity monitoring sensors, a large amount of data can be obtained to analyze household electricity usage so as to better diagnose the leakage and theft behaviors, identify man-made tampering and data fraud, and detect powerline loss. In this paper, the time window method is first proposed to obtain the features and potential periodicity of household electricity data. Combining th…

autoencoderMains electricityComputer Networks and CommunicationsComputer sciencemultilayer hierarchical networkkotitaloudetverkot (järjestelmät)computer.software_genreanomaly detectionComputer Science Applicationshousehold electricitysähkönkulutussähködataclassificationHardware and ArchitectureTime windowspoikkeavuusSignal ProcessingAnomaly detectionData miningcomputerNetwork approachfeedforward networkInformation Systems
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Data Mining for the Security of Cyber Physical Systems Using Deep-Learning Methods

2022

Cyber Physical Systems (CPSs) have become widely popular in recent years, and their applicability have been growing exponentially. A CPS is an advanced system that incorporates a computation unit along with a hardware unit, allowing for computing processes to interact with the physical world. However, this increased usage has also led to the security concerns in them, as they allow potential attack vendors to exploit the possibilities of committing misconduct for their own benefit. It is of paramount importance that these systems have comprehensive security mechanisms to mitigate these security threats. A typical attack vector for a CPS is malicious data supplied by compromised sensors that…

autoencodercyber physical systemsyväoppiminensupport vector machinefault tolerancetiedonlouhintakyberturvallisuusverkkohyökkäyksetsensor datacyber attacktietojärjestelmätInternational Conference on Cyber Warfare and Security
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Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems

2020

Vehicle Routing Problems (VRP) are computationally challenging, constrained optimization problems, which have central role in logistics management. Usually different solvers are being developed and applied for different kind of problems. However, if descriptive and general features could be extracted to describe such problems and their solution attempts, then one could apply data mining and machine learning methods in order to discover general knowledge on such problems. The aim then would be to improve understanding of the most important characteristics of VRPs from both efficient solution and utilization points of view. The purpose of this article is to address these challenges by proposi…

autoencoderreititysbusiness.industryComputer scienceProcess (engineering)capacitated vehicle routing problemsfeature extractionFeature extractionLogistics managementknowledge discoveryRobust statisticsMachine learningcomputer.software_genreAutoencoderkoneoppiminenKnowledge extractionoptimointirobust statisticsVehicle routing problemlogistiikkaGeneral knowledgeArtificial intelligencetiedonlouhintabusinesscomputer
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Classification of Sound Scenes and Events in Real-World Scenarios with Deep Learning Techniques

2021

La clasificación de los eventos sonoros es un campo de la audición por computador que se está volviendo cada vez más interesante debido al gran número de aplicaciones que podrían beneficiarse de esta tecnología. A diferencia de otros campos de la audición por computador relacionados con la recuperación de información musical o el reconocimiento del habla, la clasificación de eventos sonoros tiene una serie de problemas intrínsecos. Estos problemas son la naturaleza polifónica de la mayoría de las grabaciones de sonido ambiental, la diferencia en la naturaleza de cada sonido, la falta de estructura temporal y la adición de ruido de fondo y reverberación en el proceso de grabación. Estos prob…

autoencodertécnicas de compresión y excitación:CIENCIAS TECNOLÓGICAS [UNESCO]aprendizaje residualreconocimiento del conjunto abiertoclasificicación de eventos sonorossoluciones end-to-endUNESCO::CIENCIAS TECNOLÓGICASaprendizaje con pocas muestras
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Encryption and Generation of Images for Privacy-Preserving Machine Learning in Smart Manufacturing

2023

Current advances in machine (deep) learning and the exponential growth of data collected by and shared between smart manufacturing processes give a unique opportunity to get extra value from that data. The use of public machine learning services actualizes the issue of data privacy. Ordinary encryption protects the data but could make it useless for the machine learning objectives. Therefore, “privacy of data vs. value from data” is the major dilemma within the privacy preserving machine learning activity. Special encryption techniques or synthetic data generation are being in focus to address the issue. In this paper, we discuss a complex hybrid protection algorithm, which assumes sequenti…

data privacyIndustry 4.0anonymizationimage processingtietosuojakoneoppiminensalausautoencoderssyntetic data generationGeneral Earth and Planetary SciencesvalmistustekniikkakonenäköteollisuusanonymiteettiGeneral Environmental ScienceProcedia Computer Science
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A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders

2017

Menetelmä poikkeavuuksien havaitsemiseen hyperspektrikuvista käyttäen syviä konvolutiivisia autoenkoodereita. Poikkeavuuksien havaitseminen kuvista, erityisesti hyperspektraalisista kuvista, on hankalaa. Kun ongelmaan yhdistetään ennalta tuntematon data ja poikkeavuudet, muodostuu ongelma vielä laajemmaksi. Spektraalisten poikkeavuuksien havaitsemiseen on kehitetty useita eri menetelmiä, mutta spatiaalisten poikkeavuuksien havaitseminen on huomattavasti hankalempaa. Tässä työssä esitellään uudenkaltainen menetelmä sekä spatiaalisten että spektraalisten poikkeavuuksien samanaikaiseen havaitsemiseen. Menetelmä on suunniteltu erityisesti spektraaliselle datalle, mutta soveltuu myös perinteisil…

hyperspectral imagesautoencoderautoenkooderithdbscanSCAEconvolutional neural networkdeep learninghavaitseminenneuroverkotanomaly detectionconvolutional autoencodermachine learningkoneoppiminenpoikkeavuuskonvoluutioälytekniikkaCAEhyperspektrikuvatautoenkooderi
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