Search results for "NR"

showing 10 items of 6911 documents

A Review of Recent Range Image Registration Methods with Accuracy Evaluation

2007

International audience; The three-dimensional reconstruction of real objects is an important topic in computer vision. Most of the acquisition systems are limited to reconstruct a partial view of the object obtaining in blind areas and occlusions, while in most applications a full reconstruction is required. Many authors have proposed techniques to fuse 3D surfaces by determining the motion between the different views. The first problem is related to obtaining a rough registration when such motion is not available. The second one is focused on obtaining a fine registration from an initial approximation. In this paper, a survey of the most common techniques is presented. Furthermore, a sampl…

0209 industrial biotechnologyRegistrationComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registration02 engineering and technologycomputer.software_genre[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Motion (physics)020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringRange imageComputer vision3D reconstructionComputingMilieux_MISCELLANEOUSbusiness.industry3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Object (computer science)Sample (graphics)Range (mathematics)Signal ProcessingOutlier020201 artificial intelligence & image processingComputer visionComputer Vision and Pattern RecognitionNoise (video)Data miningArtificial intelligencebusinesscomputer
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Design of a robust controller for DC/DC converter–electrolyzer systems supplied by μWECSs subject to highly fluctuating wind speed

2020

Abstract A buck-based, isolated, high-voltage-ratio DC/DC converter that allows supplying a proton exchange membrane (PEM) electrolyzer from a micro-wind energy conversion system ( μ WECS) has been recently presented. It exhibits low ripple at the switching frequency on the output voltage and current and represents an attractive solution for low-cost hydrogen production. In this paper, a more accurate mathematical model of such a converter is derived and discussed. Then, a model-based robust controller is designed in the frequency domain using the Internal Model Control structure and in the context of H 2 ∕ H ∞ optimal control. The controller satisfies the condition of robust stability and …

0209 industrial biotechnologyRippleRobust controlInternal modelFull-bridge converter02 engineering and technology7. Clean energy[SPI.AUTO]Engineering Sciences [physics]/Automatic020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaElectrolyzerControl theoryRobustness (computer science)Model-based control techniques0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSParametric statisticsPhysicsBuck converterApplied Mathematics[SPI.NRJ]Engineering Sciences [physics]/Electric power020208 electrical & electronic engineeringOptimal controlComputer Science ApplicationsInductanceControl and Systems EngineeringFrequency domainStand-alone wind generatorVoltageControl Engineering Practice
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A proposed mapping method for aligning machine execution data to numerical control code

2019

The visions of the digital thread and smart manufacturing have boosted the potential of relating downstream data to upstream decisions in design. However, to date, the tools and methods to robustly map across the related data representations is significantly lacking. In response, we propose a mapping technique for standard manufacturing data representations. Specifically, we focus on relating controller data from machining tools in the form of MTConnect, an emerging standard that defines the vocabulary and semantics as well as communications protocols for execution data, and G-Code, the most widely used standard for numerical control (NC) instructions. We evaluate the efficacy of our mappin…

0209 industrial biotechnologyVocabulary021103 operations researchComputer sciencemedia_common.quotation_subject0211 other engineering and technologies02 engineering and technologyThread (computing)computer.software_genreData mappingData modeling020901 industrial engineering & automationMachiningMTConnectNumerical controlData miningCommunications protocolcomputermedia_common2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
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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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Exploring Virtual Reality as an Integrated Development Environment for Cyber-Physical Systems

2019

Cyber Physical Systems (CPS) development approaches tend to start from the physical (hardware) perspective, and the software is the final element in the process. However, this approach is unfit for the more software-intensive world that is increasingly iterative, connected, and constantly online. Many constraints prevent the application of iterative, incremental, and agile development methodologies, which now are the norm for many other fields of software. Time-consuming system validation can only start when both hardware and software components are ready, which implies that the software delivery and quality is almost always the final bottleneck in the CPS development and integration. Also …

0209 industrial biotechnologybusiness.industryComputer scienceProcess (engineering)Integrated softwareeducationCyber-physical system020207 software engineering02 engineering and technologyVirtualizationcomputer.software_genre113 Computer and information sciencesBottleneck020901 industrial engineering & automationSoftwareComponent-based software engineering0202 electrical engineering electronic engineering information engineeringbusinessSoftware engineeringcomputerAgile software development
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Modeling Energy Demand Aggregators for Residential Consumers

2013

International audience; Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by conside…

0209 industrial biotechnologydemand-response paradigm020209 energyEnergy current02 engineering and technologycomputer.software_genre7. Clean energyNews aggregatorload regulation[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]020901 industrial engineering & automationdemand side management; load regulation; queueing theory; smart power grids; demand-response paradigm; energy consumers; energy demand aggregator modeling; greedy energy consumers; home users; industrial plants; power load control; queuing theory; residential consumers; smart grids; Delays; Home appliances; Load modeling; Power demand; Sociology; Statistics; Switchesresidential consumerSociologySettore ING-INF/04 - Automatica0202 electrical engineering electronic engineering information engineeringindustrial plantenergy demand aggregator modelingDemand loadSimulationStatisticQueueing theoryDelayLoad modelingdemand side managementSettore ING-INF/03 - Telecomunicazionigreedy energy consumerpower load controlLoad balancing (electrical power)Poisson processEnvironmental economicsGridenergy consumerHome applianceSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSmart gridQueueing theorymart gridLoad regulationqueuing theoryPower demandEnergy demand aggregatorsmart power gridcomputerSwitcheshome user
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Input Selection Methods for Soft Sensor Design: A Survey

2020

Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …

0209 industrial biotechnologylcsh:T58.5-58.64lcsh:Information technologyComputer Networks and CommunicationsComputer scienceFeature selectionprediction02 engineering and technologyFunction (mathematics)input selectionSoft sensorcomputer.software_genresoft sensor; inferential model; input selection; feature selection; regression; predictionfeature selection020901 industrial engineering & automationinferential model0202 electrical engineering electronic engineering information engineeringsoft sensorregression020201 artificial intelligence & image processingData miningInput selectioncomputerSelection (genetic algorithm)Future Internet
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DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

2021

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …

0209 industrial biotechnologylineaarinen optimointiPareto optimizationGeneral Computer Sciencemulti-criteria decision makingComputer sciencepäätöksentekoevoluutiolaskenta02 engineering and technologyData-driven multiobjective optimizationcomputer.software_genrenonlinear optimizationMulti-objective optimizationData modelingopen source softwareavoin lähdekoodi020901 industrial engineering & automationSoftwareoptimointi0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceUse casecomputer.programming_languageGraphical user interfacepareto-tehokkuusbusiness.industryGeneral Engineeringinteractive methodsModular designPython (programming language)monitavoiteoptimointiTK1-9971Software frameworkdata-driven multiobjective optimizationevolutionary computation020201 artificial intelligence & image processingElectrical engineering. Electronics. Nuclear engineeringbusinessSoftware engineeringcomputerIEEE Access
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P-FCM: a proximity-based fuzzy clustering for user-centered web applications

2003

Abstract In last years, the Internet and the web have been evolved in an astonishing way. Standard web search services play an important role as useful tools for the Internet community even though they suffer from a certain difficulty. The web continues its growth, making the reliability of Internet-based information and retrieval systems more complex. Nevertheless there has been a substantial analysis of the gap between the expected information and the returned information, the work of web search engine is still very hard. There are different problems concerning web searching activity, one among these falls in the query phase. Each engine provide an interface which the user is forced to le…

0209 industrial biotechnologymedicine.medical_specialtyComputer science02 engineering and technologyWeb engineeringcomputer.software_genreSimilarityTheoretical Computer ScienceWorld Wide Web020901 industrial engineering & automationArtificial IntelligenceWeb query classificationWeb design0202 electrical engineering electronic engineering information engineeringmedicineWeb navigationWeb search queryInformation retrievalHuman–computer interactionApplied MathematicsFuzzy logicSearch enginesWeb search engine020201 artificial intelligence & image processingWeb servicecomputerWeb modelingSoftwareFuzzy C-mean algorithmInternational Journal of Approximate Reasoning
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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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