Search results for "Machine"

showing 10 items of 2592 documents

Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms.

2021

Plant Ecological Unit’s (PEUs) are the abstraction of vegetation communities that occur on a site which similarly respond to management actions and natural disturbances. Identification and monitoring of PEUs in a heterogeneous landscape is the most difficult task in medium resolution satellite images datasets. The main objective of this study is to compare pixel-based classification versus object-based classification for accurately classifying PEUs with four selected different algorithms across heterogeneous rangelands in Central Zagros, Iran. We used images of Landsat-8 OLI that were pan-sharpened to 15 m to classify four PEU classes based on a random dataset collected in the field (40%). …

PixelEcologyComputer scienceprincipal component analysisScienceQPerceptronObject (computer science)Field (computer science)Statistical classificationplant ecological units mappingmachine learning algorithmsPrincipal component analysisClassifier (linguistics)General Earth and Planetary Sciencesobject-based classificationTest dataRemote sensing
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Smartphone determination of fat in cured meat products

2017

Abstract A method has been developed to determine the fat content in different cold meat products by image processing using the camera of a mobile phone. Salchichon , chorizo , salami and cured ham pictures were taken with a Meizu M2 Mini mobile phone camera under fixed lighting conditions of the light emitting diode flash of the mobile phone. Images were treated with Matlab to obtain the mean pixels of average red, green and blue camera values colours (RGB) of the pixels and different data pretreatments were taken into account to correlate colour parameters with fat content values determined in a series of commercially available samples by the Soxhlet method. RGB values were used as input …

Pixelbusiness.industryFat content010401 analytical chemistryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONAnalytical chemistryImage processingPattern recognition04 agricultural and veterinary sciences040401 food science01 natural sciences0104 chemical sciencesAnalytical ChemistrySupport vector machine0404 agricultural biotechnologyPartial least squares regressionCalibrationRGB color modelArtificial intelligenceMobile phone camerabusinessSpectroscopyMathematicsMicrochemical Journal
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A platform-independent software for the design and analysis of windings of rotating electrical machines

2014

In this paper the Authors present a highly modular and platform-independent software, being based on the MATLAB® programming environment, which is proposed as a valuable aid in the design and analysis of the windings of rotating electrical machines. Unlike the major part of the commercial software, the cases of both symmetric and asymmetric (unbalanced) windings with any number of phases are here considered. The software can perform a considerable amount of calculations in order to determine automatically the optimal structure of the winding starting from its specifications. It is also able to draw the winding map and gives the results of calculation for the harmonic winding factors. The re…

Platform independentEngineeringMATLABbusiness.industryElectrical engineeringHarmonicCoilWindingAC MachineSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciPower electronicWindingsSoftwareElectromagnetic coilbusinessMotion controlHarmonic analysi
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Exploring Training Options for RF Sensing Using CSI

2018

This work analyzes human behavior recognition approaches using WiFi channel state information from the perhaps less usual point of view of training and calibration needs. With the help of selected literature examples, as well as with more detailed experimental insights on our own Doppler spectrum-based approach for physical motion/presence/cardinality detection, we first classify the diverse forms of training so far employed into three main categories (trained, trained-once, and training-free). We further discuss under which conditions it is possible to move toward lighter forms of calibration or even succeed in devising fully untrained model-based solutions. Our take home messages are main…

Point (typography)Settore ING-INF/03 - TelecomunicazioniComputer Networks and CommunicationsCalibration (statistics)Computer sciencebusiness.industry010401 analytical chemistryBehavioural sciences020206 networking & telecommunications02 engineering and technologyMachine learningcomputer.software_genreTraining Wireless fidelity Calibration Doppler effect Behavioral sciences Radio frequency Sensors Channel state estimation01 natural sciencesTraining (civil)Motion (physics)0104 chemical sciencesComputer Science ApplicationsPersonalization0202 electrical engineering electronic engineering information engineeringArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerIEEE Communications Magazine
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Towards an Immersive and Accessible Virtual Reconstruction of Theaters from the Early Modern

2020

This paper reports on the work being done towards achieving an immersive and accessible reconstruction of Historical and Cultural Heritage, focusing on Theaters of the Early Modern as use case. In particular, the paper presents and discusses potential possibilities to enable: 1) the acoustical reconstruction of the virtual (lost) environments – beyond the graphical reconstruction for the buildings, elements and performances; 2) effective interaction features and navigation within the virtual environment (e.g. by means of adaptive interfaces, guiding methods, insertion of Point of Interest); and 3) accessible experiences, by means of an innovative and personalized presentation modes for acce…

Point of interestMultimediaComputer sciencemedia_common.quotation_subjectAudio descriptionVirtual realitycomputer.software_genreCultural heritagePresentationWork (electrical)Virtual machinecomputerTourismmedia_commonACM International Conference on Interactive Media Experiences
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Combining Real-Time Segmentation and Classification of Rehabilitation Exercises with LSTM Networks and Pointwise Boosting

2020

Autonomous biofeedback tools in support of rehabilitation patients are commonly built as multi-tier pipelines, where a segmentation algorithm is first responsible for isolating motion primitives, and then classification can be performed on each primitive. In this paper, we present a novel segmentation technique that integrates on-the-fly qualitative classification of physical movements in the process. We adopt Long Short-Term Memory (LSTM) networks to model the temporal patterns of a streaming multivariate time series, obtained by sampling acceleration and angular velocity of the limb in motion, and then we aggregate the pointwise predictions of each isolated movement using different boosti…

PointwiseMultivariate statisticsBoosting (machine learning)Rehabilitationbusiness.industryComputer sciencemedicine.medical_treatmentmedicineSegmentationPattern recognitionGeneral MedicineArtificial intelligencebusinessProceedings of the AAAI Conference on Artificial Intelligence
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Design and use of a Fatigue Test Machine in Plane Bending for Composite Specimens and Bonded Joints

2011

Polymeric and composites materials are increasingly used in industry as structural parts, so that specific information on their mechanical properties "at long term" (creep, relaxation, fatigue) are requested. The design and implementation of these components also requires that they are permanently connected together to perform certain functions. The use of adhesives in structural joints has increased over recent years thanks to the continuous development by companies which provide the market with adhesive having better and better mechanical properties. The main areas relate to the aerospace, aeronautical and automotive industries, where requirements are required for lightness and reliabilit…

Polyester resinchemistry.chemical_classificationMaterials scienceBending (metalworking)business.industryFatigue Test Machinequasi isotropic compositeComposite numberStiffnessFracture mechanicsStructural engineeringEpoxySettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineCreepchemistryreinforced compositevisual_artglare bonded joints.medicinevisual_art.visual_art_mediumFormabilitymedicine.symptomComposite materialbusiness
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Machine Learning Regression Approaches for Colored Dissolved Organic Matter (CDOM) Retrieval with S2-MSI and S3-OLCI Simulated Data

2018

The colored dissolved organic matter (CDOM) variable is the standard measure of humic substance in waters optics. CDOM is optically characterized by its spectral absorption coefficient, a C D O M at at reference wavelength (e.g., ≈ 440 nm). Retrieval of CDOM is traditionally done using bio-optical models. As an alternative, this paper presents a comparison of five machine learning methods applied to Sentinel-2 and Sentinel-3 simulated reflectance ( R r s ) data for the retrieval of CDOM: regularized linear regression (RLR), random forest regression (RFR), kernel ridge regression (KRR), Gaussian process regression (GPR) and support vector machines (SVR). Two different datasets of radiative t…

Polynomial regression010504 meteorology & atmospheric sciencesArtificial neural networkbusiness.industry0211 other engineering and technologiesta117102 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesremote sensing; CDOM; optically complex waters; linear regression; machine learning; Sentinel 2; Sentinel 3RegressionRandom forestSupport vector machineColored dissolved organic matterKrigingLinear regressionGeneral Earth and Planetary SciencesArtificial intelligencebusinesscomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote Sensing
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Learning of regular expressions by pattern matching

1995

We consider the problem of restoring regular expressions from good examples. We describe a natural learning algorithm for obtaining a “plausible” regular expression from one example. The algorithm is based on finding the longest substring which can be matched by some part of the so far obtained expression. We believe that the algorithm to a certain extent mimics humans guessing regular expressions from the same sort of examples. We show that for regular expressions of bounded length successful learning takes time linear in the length of the example, provided that the example is “good”. Under certain natural restrictions the run-time of the learning algorithm is polynomial also in unsuccessf…

PolynomialFinite-state machineRegular languageComputer scienceBounded functionRegular expressionPattern matchingAlgorithmExpression (mathematics)Substring
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Distributed learning automata-based scheme for classification using novel pursuit scheme

2020

Learning Automata (LA) is a popular decision making mechanism to “determine the optimal action out of a set of allowable actions” (Agache and Oommen, IEEE Trans Syst Man Cybern-Part B Cybern 2002(6): 738–749, 2002). The distinguishing characteristic of automata-based learning is that the search for the optimising parameter vector is conducted in the space of probability distributions defined over the parameter space, rather than in the parameter space itself (Thathachar and Sastry, IEEE Trans Syst Man Cybern-Part B Cybern 32(6): 711–722, 2002). Recently, Goodwin and Yazidi pioneered the use of Ant Colony Optimisation (ACO) for solving classification problems (Goodwin and Yazidi 2016). In th…

PolynomialOptimization problemLearning automataComputer sciencePolygonsFeature vector02 engineering and technologyAnt colonyParameter spaceRandom walkLearning automataSupport vector machineKernel methodArtificial IntelligenceKernel (statistics)Polygon0202 electrical engineering electronic engineering information engineeringProbability distribution020201 artificial intelligence & image processingClassificationsVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550AlgorithmApplied Intelligence
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