Search results for " mac"

showing 10 items of 3066 documents

Sensorless Speed Control for Double-Sided Linear Induction Motor Applications

2019

In this work, a flux and speed observer for double-sided linear induction motor applications is presented and experimentally validated. More in detail, from a Double-Sided Linear Induction Motor (DLIM) prototype, the complete modelling and the determination of the related parameters are here reported. Furthermore, the equations for a d-flux and q-flux observer are conceived and several simulation tests are performed. From the good agreements between the trends over time of the speed estimated by the observer and the simulated one, it can be stated that the observer is well designed. Moreover, in order to experimentally validate the proposed observer, a test bench is set-up for the DLIM/obse…

0209 industrial biotechnologyTest benchElectronic speed controlObserver (quantum physics)Computer scienceSpeed control020208 electrical & electronic engineeringWork (physics)DLIM02 engineering and technologySettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciDynamic modelFlux observerSettore ING-IND/31 - Elettrotecnica020901 industrial engineering & automationControl theoryLinear induction motor0202 electrical engineering electronic engineering information engineeringDSPACEFlux observer2019 8th International Conference on Renewable Energy Research and Applications (ICRERA)
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Adjusted bat algorithm for tuning of support vector machine parameters

2016

Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…

0209 industrial biotechnologyWake-sleep algorithmActive learning (machine learning)Computer scienceStability (learning theory)Linear classifier02 engineering and technologySemi-supervised learningcomputer.software_genreCross-validationRelevance vector machineKernel (linear algebra)020901 industrial engineering & automationLeast squares support vector machine0202 electrical engineering electronic engineering information engineeringMetaheuristicBat algorithmStructured support vector machinebusiness.industrySupervised learningOnline machine learningParticle swarm optimizationPattern recognitionPerceptronGeneralization errorSupport vector machineKernel methodComputational learning theoryMargin classifierHyperparameter optimization020201 artificial intelligence & image processingData miningArtificial intelligenceHyper-heuristicbusinesscomputer2016 IEEE Congress on Evolutionary Computation (CEC)
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Design of a telescopic tower for wind energy production with reduced environmental impact

2019

A prototype of a telescopic pole for wind energy production with low environmental impact and its lifting system for a 60 to 250 kW turbine and a height of 30 m have been designed and manufactured. A telescopic tower, which is raised and lowered by automation or by remote control, allows to differentiate the presence of the generator within the landscape over time. The technology currently available for lifting and lowering wind turbines is made up of telescopic poles of heights of less than 10 meters and with tilting posts of height below 30 m. Without a state of the art to refer to, the telescopic pole and its lifting system have been designed starting from scratch and solving with innova…

0209 industrial biotechnologyWind powerRenewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industryMechanical Engineering02 engineering and technology021001 nanoscience & nanotechnologyTurbineAutomationIndustrial and Manufacturing Engineeringlaw.inventionSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationlawManagement of Technology and InnovationTelescopic tower wind turbine tower mechanical design finite element methodGeneral Materials ScienceEnvironmental impact assessment0210 nano-technologybusinessRemote controlDecoupling (electronics)Efficient energy useMarine engineering
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MFNet: Multi-feature convolutional neural network for high-density crowd counting

2020

The crowd counting task involves the issue of security, so now more and more people are concerned about it. At present, the most difficult problem of population counting consists in: how to make the model distinguish human head features more finely in the densely populated area, such as head overlap and how to find a small-scale local head feature in an image with a wide range of population density. Facing these challenges, we propose a network for multiple feature convolutional neural network, which is called MFNet. It aims to get high-quality density maps in the high-density crowd scene, and at the same time to perform the task of the count and estimation of the crowd. In terms of crowd c…

0209 industrial biotechnologyeducation.field_of_studyHuman headComputer sciencebusiness.industryPopulationPattern recognition02 engineering and technologyConvolutional neural networkImage (mathematics)Support vector machineTask (computing)Range (mathematics)020901 industrial engineering & automationFeature (computer vision)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceeducationbusiness2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
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Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

0209 industrial biotechnologyrandom projectionlcsh:Computer engineering. Computer hardwareComputational complexity theoryComputer scienceRandom projectionlcsh:TK7885-789502 engineering and technologyMachine learningcomputer.software_genresupervised learningapproximate algorithmsSet (abstract data type)regressioanalyysi020901 industrial engineering & automationdistance–based regressionalgoritmit0202 electrical engineering electronic engineering information engineeringordinary least–squaresbusiness.industrySupervised learningsingular value decompositionminimal learning machineMultilaterationprojektioRandomized algorithmkoneoppiminenmachine learningScalabilityFeedforward neural network020201 artificial intelligence & image processingArtificial intelligenceapproksimointibusinesscomputerMachine Learning and Knowledge Extraction
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Me, My Bot and His Other (Robot) Woman? Keeping Your Robot Satisfied in the Age of Artificial Emotion

2018

With a backdrop of action and science fiction movie horrors of the dystopian relationship between humans and robots, surprisingly to date-with the exception of ethical discussions-the relationship aspect of humans and sex robots has seemed relatively unproblematic. The attraction to sex robots perhaps is the promise of unproblematic affectionate and sexual interactions, without the need to consider the other&rsquo

0209 industrial biotechnologyuskottomuusControl and Optimizationlcsh:Mechanical engineering and machinery02 engineering and technologytekoälyemotions050105 experimental psychology020901 industrial engineering & automationtunteetsex0501 psychology and cognitive scienceslcsh:TJ1-1570Artificial emotionsRelation (history of concept)ta113Dystopiabusiness.industryMechanical Engineering05 social sciencesInformation technologyRoboticsartificial intelligencePreferenceAction (philosophy)seksirobotitRobotrobotsArtificial intelligenceinfidelitybusinessPsychologyCognitive psychology
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An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery

2018

This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…

021103 operations researchArtificial neural networkComputer science0211 other engineering and technologies02 engineering and technologyArtificial bee colony algorithmSupport vector machineStatistical classificationAbc modelComputingMethodologies_PATTERNRECOGNITIONDiscriminant0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingDegree of a polynomialClassifier (UML)Remote sensing2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
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PolyACO+: a multi-level polygon-based ant colony optimisation classifier

2017

Ant Colony Optimisation for classification has mostly been limited to rule based approaches where artificial ants walk on datasets in order to extract rules from the trends in the data, and hybrid approaches which attempt to boost the performance of existing classifiers through guided feature reductions or parameter optimisations. A recent notable example that is distinct from the mainstream approaches is PolyACO, which is a proof of concept polygon-based classifier that resorts to ant colony optimisation as a technique to create multi-edged polygons as class separators. Despite possessing some promise, PolyACO has some significant limitations, most notably, the fact of supporting classific…

021103 operations researchArtificial neural networkComputer sciencebusiness.industryPolygonsTraining timeMulti-levelling0211 other engineering and technologiesPattern recognition02 engineering and technologyAnt colonySupport vector machineArtificial IntelligenceMultiple time dimensionsPolygonAnt colony optimisation0202 electrical engineering electronic engineering information engineeringArtificial Ants020201 artificial intelligence & image processingArtificial intelligenceClassificationsbusinessClassifier (UML)
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A flexible robotic cell for in-process inspection of multi-pass welds

2020

Welds are currently only inspected after all the passes are complete and after allowing sufficient time for any hydrogen cracking to develop, typically over several days. Any defects introduced between passes are therefore unreported until fully buried, greatly complicating rework and also delaying early corrections to the weld process parameters. In-process inspection can provide early intervention but involves many challenges, including operation at high temperatures with significant gradients affecting acoustic velocities and, hence, beam directions. Reflections from the incomplete parts of the weld would also be flagged as lack-of-fusion defects, requiring the region of interest (ROI) t…

021103 operations researchComputer scienceTKMechanical EngineeringGas tungsten arc welding0211 other engineering and technologiesMetals and AlloysReworkProcess (computing)Mechanical engineering02 engineering and technologyWeldingWork in process01 natural scienceslaw.inventionSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineMechanics of MaterialslawRegion of interest0103 physical sciencesMaterials ChemistryRobotUltrasonic sensorRobotics In-process inspection Multi-pass welds010301 acoustics
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A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm

2013

Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…

021103 operations researchComputer scienceVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 4220211 other engineering and technologiesClass (philosophy)02 engineering and technologyField (computer science)Term (time)Support vector machineSet (abstract data type)Identification (information)Bayes' theoremCardinality0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingVDP::Mathematics and natural science: 400::Mathematics: 410::Algebra/algebraic analysis: 414InformationSystems_MISCELLANEOUSAlgorithm
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