Search results for " machine"

showing 10 items of 1317 documents

Monitoring internet trade to inform species conservation actions

2017

Specimens, parts and products of threatened species are now commonly traded on the internet. This could threaten the survival of some wild populations if inadequately regulated. We outline two methods to monitor internet sales of threatened species in order to assess potential threats and inform conservation actions. Our first method combines systematic monitoring of online offers of plants for sale over the internet with consultation by experts experienced in identifying plants collected from the wild based on images of the specimens, species identity and details of the trade. Our second method utilises a computational model, trained using Bayesian techniques to records that have been clas…

0106 biological sciencesSettore BIO/07 - EcologiaEcologybusiness.industry010604 marine biology & hydrobiologyInternet privacyfood and beverages010603 evolutionary biology01 natural scienceslcsh:QK1-989Geographylcsh:Botanylcsh:ZoologySettore BIO/03 - Botanica Ambientale E ApplicataThe InternetAdenia Commiphora Operculicarya Uncarina Machine learning Infer.NET Naive Bayes classifierlcsh:QL1-991businessNature and Landscape Conservation
researchProduct

Ecophysiological Modeling of Grapevine Water Stress in Burgundy Terroirs by a Machine-Learning Approach

2016

13 pages; International audience; In a climate change scenario, successful modeling of the relationships between plant-soil-meteorology is crucial for a sustainable agricultural production, especially for perennial crops. Grapevines (Vitis vinifera L. cv Chardonnay) located in eight experimental plots (Burgundy, France) along a hillslope were monitored weekly for 3 years for leaf water potentials, both at predawn (Ψpd) and at midday (Ψstem). The water stress experienced by grapevine was modeled as a function of meteorological data (minimum and maximum temperature, rainfall) and soil characteristics (soil texture, gravel content, slope) by a gradient boosting machine. Model performance was a…

0106 biological sciences[ SDV.BV ] Life Sciences [q-bio]/Vegetal BiologySoil texture[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil studyContext (language use)Plant Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studylcsh:Plant culture01 natural sciencesVineyardwater stressWater balancewater balance[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/Agronomygradient boosting machine (GBM)Climate change scenarioBotany[SDV.BV]Life Sciences [q-bio]/Vegetal Biologylcsh:SB1-1110Original ResearchTerroir2. Zero hungerHydrologymachine-learninggrapevine (Vitis vinifera L.)temperature04 agricultural and veterinary sciences15. Life on landcarbon isotope discrimination δ13Cplant-soil water relationships040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceGradient boostingScale (map)carbon isotope discrimination d13Ccarbon isotopic discrimination (δ13C)010606 plant biology & botanyFrontiers in Plant Science
researchProduct

Broker and Federation Based Cloud Networking Architecture for IaaS and NaaS QoS Guarantee

2016

International audience; Today, the Cloud networking aspect is a critical factor for adopting the Cloud computing approach. The main drawback of Cloud networking consists in the lack of Quality of Service (QoS) guarantee and management in conformance with a corresponding Service Level Agreement (SLA). This paper presents a framework for resource allocation according to an end-to-end SLA established between a Cloud Service User (CSU) and several Cloud Service Providers (CSPs) in a Cloud networking environment. We focus on QoS parameters for Network as a Service (NaaS) and Infrastructure as a Service (IaaS) services. In addition, we propose algorithms for the best CSPs selection to allocate Vi…

020203 distributed computing[SPI] Engineering Sciences [physics]business.industryComputer scienceQuality of service020207 software engineeringCloud computing02 engineering and technologyMobile QoScomputer.software_genre[SPI.TRON] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI]Engineering Sciences [physics]Service-level agreementNetwork as a serviceVirtual machineCloud testing0202 electrical engineering electronic engineering information engineering[ SPI ] Engineering Sciences [physics]Resource allocationbusinesscomputerSimulationComputer network
researchProduct

Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder

2020

This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed c…

0209 industrial biotechnologyAdaptive controlFluid PowerComputer sciencemotion controlComputer Science::Neural and Evolutionary Computationhydraulicsdifferential cylinder02 engineering and technologyAdaptiv reguleringadaptive controllcsh:TechnologyRoot mean squarelcsh:Chemistry020901 industrial engineering & automationControl theoryConvergence (routing)feedforwardCylinderGeneral Materials ScienceVDP::Andre maskinfag: 579Instrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processeslcsh:TProcess Chemistry and TechnologyGeneral EngineeringFeed forwardVDP::Other machinery sciences: 579021001 nanoscience & nanotechnologyMotion controllcsh:QC1-999BevegelsesstyringComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Hydraulikk0210 nano-technologyReduction (mathematics)lcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsApplied Sciences
researchProduct

Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons

2016

The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.

0209 industrial biotechnologyBoosting (machine learning)business.industryComputer scienceAnt colony optimization algorithmsDecision treePattern recognition02 engineering and technologyAnt colonycomputer.software_genreSwarm intelligenceSupport vector machineComputingMethodologies_PATTERNRECOGNITION020901 industrial engineering & automationKernel method0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceData miningbusinesscomputer
researchProduct

Use of second-order sliding mode observer for low-accuracy sensing in hydraulic machines

2018

Low-accuracy sensing is very common for the large hydraulic machines and does not allow for directly measuring the relative velocity which can be, otherwise, required for the control and monitoring purposes. This paper provides a case study of designing the second-order sliding mode observer based on the super-twisting robust exact differentiator. The nominal part of the system dynamics is derived from the simple available system measurements and incorporated into the observer structure. Parasitic by-effects, arising from the sensor sampling, quantization, and non-modeled distortions due to mechanical sensor interface, are shown as the main causes of hampering the final (steady-state) conve…

0209 industrial biotechnologyComputer science020208 electrical & electronic engineeringRelative velocity02 engineering and technologySystem dynamicsDifferentiator020901 industrial engineering & automationControl theoryRobustness (computer science)0202 electrical engineering electronic engineering information engineeringChirpHydraulic machineryExcitationMotion system
researchProduct

Adding Active Damping to Energy-Efficient Electro-Hydraulic Systems for Robotic Manipulators — Comparing Pressure and Acceleration Feedback

2020

The growing interest in energy efficiency, plug-and-play commissioning, and reduced maintenance for heavy-duty robotic manipulators directs towards self-contained, electro-hydraulic cylinders. These drives are characterized by extremely low damping that causes unwanted oscillations of the mechanical structure. Adding active damping to this class of energy-efficient architectures is essential. Hence, this paper bridges a literature gap by presenting a systematic comparison grounded on a model-based tuning of both pressure and acceleration feedback. It is shown that both approaches increase the system damping hugely and improve the performance of the linear system. Acceleration feedback shoul…

0209 industrial biotechnologyComputer science020209 energyLinear systemRobot manipulatorPressure feedback02 engineering and technologyElectro hydraulicAcceleration020901 industrial engineering & automationControl theory0202 electrical engineering electronic engineering information engineeringHydraulic machineryEfficient energy use2020 5th International Conference on Robotics and Automation Engineering (ICRAE)
researchProduct

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
researchProduct

Minimal-model for robust control design of large-scale hydraulic machines

2018

Hydraulic machines are in use where the large forces, at relatively low velocities, are required by varying loads and often hazardous and hard-to-reach environments, like e.g. offshore, mining, forestry, cargo logistics, and others industries. Cranes and excavators equipped with multiple hydraulic cylinders are typical examples for that. For design of the robust feedback controls of hydraulic cylinders, already installed into large-scale machines, there is a general lack of reliable dynamic models. Also the suitable and feasible identification techniques, especially in frequency domain, yield limited. This paper pro­poses a minimal-modeling approach for determining the most relevant open-lo…

0209 industrial biotechnologyComputer scienceComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technologySystem dynamicsLoaderHydraulic cylinderExcavator020901 industrial engineering & automation020401 chemical engineeringControl theoryControl systemFrequency domain0204 chemical engineeringHydraulic machineryRobust control2018 IEEE 15th International Workshop on Advanced Motion Control (AMC)
researchProduct

Accelerated bearing life-Time test rig development for low speed data acquisition

2017

Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…

0209 industrial biotechnologyComputer scienceCondition monitoring and bearing and low-speed machinery and fault diagnosis and test rig; Software; Control and Systems Engineering; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern RecognitionTest rig02 engineering and technologyLow-speed Machinerylcsh:QA75.5-76.95Automotive engineeringlaw.inventionModeling and simulationTest Rig020901 industrial engineering & automationData acquisitionSoftwarelaw0202 electrical engineering electronic engineering information engineeringBearing (mechanical)business.industryCondition monitoring and bearing and low-speed machinery and fault diagnosis and test rig020208 electrical & electronic engineeringLife timeComputer Science Applications1707 Computer Vision and Pattern RecognitionFault DiagnosisComputer Science ApplicationsLow speedControl and Systems EngineeringEmbedded systemModeling and SimulationBearinglcsh:Electronic computers. Computer sciencebusinessCondition MonitoringSoftware
researchProduct