Search results for "MINI"

showing 10 items of 14043 documents

Cross-Layer MAC Protocol for Unbiased Average Consensus Under Random Interference

2019

Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which constitutes a building block to perform many inference tasks in an efficient and distributed manner. From the theoretical designs proposed in most previous work, this algorithm requires instantaneous symmetric links in order to reach average consensus. However, in a realistic scenario wireless communications are subject to interferences and other environmental factors, which results in random instantaneous topologies that are, in general, asymmetric. Consequently, the estimat…

0209 industrial biotechnologyComputer Networks and CommunicationsComputer sciencebusiness.industryEstimator020206 networking & telecommunications02 engineering and technologyExpected valueNetwork topology020901 industrial engineering & automationMinimum-variance unbiased estimatorBias of an estimatorSignal Processing0202 electrical engineering electronic engineering information engineeringWirelessbusinessAlgorithmWireless sensor networkRandom variableInformation SystemsIEEE Transactions on Signal and Information Processing over Networks
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Summarizing Large Scale 3D Mesh

2018

International audience; Recent progress in 3D sensor devices and in semantic mapping allows to build very rich HD 3D maps very useful for autonomous navigation and localization. However , these maps are particularly huge and require important memory capabilities as well computational resources. In this paper, we propose a new method for summarizing a 3D map (Mesh) as a set of compact spheres in order to facilitate its use by systems with limited resources (smartphones, robots, UAVs, ...). This vision-based summarizing process is applied in a fully automatic way using jointly photometric, geometric and semantic information of the studied environment. The main contribution of this research is…

0209 industrial biotechnologyComputer science020206 networking & telecommunications02 engineering and technologycomputer.software_genreVisualization[SPI.AUTO]Engineering Sciences [physics]/Automatic020901 industrial engineering & automation[SPI.AUTO] Engineering Sciences [physics]/AutomaticSemantic mapping0202 electrical engineering electronic engineering information engineeringEntropy (information theory)Polygon meshData miningcomputer
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Re-forming end-of-life components through single point incremental forming

2020

Abstract Applying Circular Economy strategies is mandatory to face material demand while minimizing the environmental impact. Manufacturing processes are to be thought as means to enable material/component reuse strategies. This paper presents the suitability of Single Point Incremental Forming (SPIF) to re-form End-of-life sheet metal components. Deep drawing followed by SPIF process on aluminium alloys were carried out to simulate reforming processes chain. The resulting thinning and strain distributions were experimentally analysed for different configurations. The research proves that the local action and enhanced formability nature of SPIF allow non-homogeneously thinned and reduced fo…

0209 industrial biotechnologyComputer scienceAluminium alloychemistry.chemical_elementMechanical engineering02 engineering and technologyReuseIndustrial and Manufacturing Engineering020901 industrial engineering & automationAluminiumComponent (UML)FormabilityDeep drawingProcess (computing)Reshaping021001 nanoscience & nanotechnologyIncremental sheet formingchemistryMechanics of Materialsvisual_artStrain analysevisual_art.visual_art_medium0210 nano-technologySheet metalThinningIncremental sheet forming
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Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

0209 industrial biotechnologyComputer scienceCognitive Neuroscienceneuraalilaskentaneuroverkot02 engineering and technologyrandomized learning machinesSet (abstract data type)extreme learning machine020901 industrial engineering & automationArtificial Intelligenceextreme minimal learning machine0202 electrical engineering electronic engineering information engineeringExtreme learning machineta113Training setBasis (linear algebra)Model selectionminimal learning machineOverlearningComputer Science ApplicationskoneoppiminenTransformation (function)020201 artificial intelligence & image processingAlgorithmNeurocomputing
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Autonomous ultrasonic inspection using Bayesian optimisation and robust outlier analysis

2020

The use of robotics is beginning to play a key role in automating the data collection process in Non Destructive Testing (NDT). Increasing the use of automation quickly leads to the gathering of large quantities of data, which makes it inefficient, perhaps even infeasible, for a human to parse the information contained in them. This paper presents a solution to this problem by making the process of NDT data acquisition an autonomous one as opposed to an automatic one. In order to achieve this, the robotic data acquisition task is treated as an optimisation problem, where one seeks to find locations with the highest indication of damage. The resulting algorithm combines damage detection tech…

0209 industrial biotechnologyComputer scienceTKAerospace Engineering02 engineering and technologycomputer.software_genre01 natural sciencesField (computer science)Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationData acquisitionNon-destructive testing (NDT)0103 physical sciencesUltrasoundUncertainty quantificationOutlier analysis010301 acousticsCivil and Structural EngineeringData collectionbusiness.industryMechanical EngineeringProbabilistic logicBayesian optimisationAutomationComputer Science ApplicationsControl and Systems EngineeringSignal ProcessingOutlierStructural health monitoringData miningbusinesscomputerGaussian process (GP) regression
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Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing

2018

International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…

0209 industrial biotechnologyDesignComputer sciencecomputer.internet_protocol02 engineering and technologycomputer.software_genreBayesian inferenceIndustrial and Manufacturing EngineeringArticle[SPI]Engineering Sciences [physics]020901 industrial engineering & automationPMML0202 electrical engineering electronic engineering information engineeringanalyticsUncertainty quantificationMonte-Carlouncertaintycomputer.programming_languageParsingBayesian networkInformationSystems_DATABASEMANAGEMENTstandardPython (programming language)XMLComputer Science ApplicationsmanufacturingComputingMethodologies_PATTERNRECOGNITIONBayesian networksControl and Systems EngineeringSurface-RoughnessData analysisPredictive Model Markup Language020201 artificial intelligence & image processingData miningcomputerXML
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Detection of algorithmically generated malicious domain names using masked N-grams

2019

Abstract Malware detection is a challenge that has increased in complexity in the last few years. A widely adopted strategy is to detect malware by means of analyzing network traffic, capturing the communications with their command and control (C&C) servers. However, some malware families have shifted to a stealthier communication strategy, since anti-malware companies maintain blacklists of known malicious locations. Instead of using static IP addresses or domain names, they algorithmically generate domain names that may host their C&C servers. Hence, blacklist approaches become ineffective since the number of domain names to block is large and varies from time to time. In this paper, we i…

0209 industrial biotechnologyDomain generation algorithmComputer scienceGeneral Engineering02 engineering and technologycomputer.software_genreBlacklistComputer Science ApplicationsRandom forestDomain (software engineering)020901 industrial engineering & automationArtificial IntelligenceServer0202 electrical engineering electronic engineering information engineeringMalware020201 artificial intelligence & image processingData miningcomputerHost (network)Block (data storage)Expert Systems with Applications
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Energy demand reduction of aluminum alloys recycling through friction stir extrusion processes implementation

2019

Abstract Aluminum alloys are characterized by high-energy demands for primary production. Recycling is a well-documented strategy to lower the environmental impact of light alloys production. Despite that, conventional recycling processes are still energy-intensive with a low energy efficiency. Also, permanent material losses occur during remelting because of oxidation. Recently, several solid-state recycling approaches have been analyzed; in fact, by avoiding the remelting step both energy and material can be saved and, therefore, the embodied energy of secondary production can be substantially reduced. In this paper, the solid-state approach Friction Stir Extrusion (FSE) is analyzed for a…

0209 industrial biotechnologyEnergy demandMaterials scienceAluminum alloyPrimary energyComparative analysiMetallurgychemistry.chemical_element02 engineering and technologyFSEIndustrial and Manufacturing EngineeringSolid state recycling020303 mechanical engineering & transports020901 industrial engineering & automationLow energy0203 mechanical engineeringchemistryArtificial IntelligenceAluminiumExtrusionReduction (mathematics)Embodied energySettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Opportunities for the Use of Business Data Analysis Technologies

2016

Abstract The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.

0209 industrial biotechnologyEngineeringHF5001-6182Big dataonline analytical processing02 engineering and technologyAnalytics platformsbusiness intelligenceTerminologyBusiness data020901 industrial engineering & automationBusiness analytics0502 economics and businessanalytics platformsBusinessHB71-74business.industryManagement scienceOnline analytical processing05 social sciencesbusiness analyticsdata miningpredictive modelling.Data scienceEconomics as a scienceAnalyticsBusiness intelligencebusinesspredictive modelling050203 business & managementPredictive modelling
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On the impact of recycling strategies on energy demand and CO2 emissions when manufacturing Al-based components

2016

Abstract The industrial world is facing the challenge of reducing emissions by means of energy- and resource-efficient manufacturing strategies. In some cases, the exerted emissions and the energy demands related to conventional manufacturing processes are not as intensive as those required to extract and produce the raw materials of which the workpieces are made. Therefore, the consciousness of the impact of material usage and the eco-informed choice of the end-of-life scenarios are both needed in view of sustainable development. Aim of this paper is to offer a contribution to a better understanding of the environmental impact of forming and machining processes, for the production of Al-ba…

0209 industrial biotechnologyEngineeringSustainable manufacturingSustainable manufacturing; Recycling; Aluminum; Machining; Forming.02 engineering and technology010501 environmental sciencesRaw material01 natural sciencesSustainable manufacturing; Recycling; Aluminum; Machining; Forming020901 industrial engineering & automationMachiningProduction (economics)Environmental impact assessmentRecyclingSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione0105 earth and related environmental sciencesGeneral Environmental ScienceSustainable developmentEnergy demandbusiness.industrySustainable manufacturingAluminium recyclingForming.Environmental economicsMachiningManufacturing engineeringGeneral Earth and Planetary SciencesbusinessFormingAluminum
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