Search results for " Mach"

showing 10 items of 1388 documents

A Saturation Avoidance Technique for Peer-to-Peer Distributed Virtual Environments

2007

This paper presents a multi-agent framework oriented to animate groups of synthetic humans that properly balance task-oriented and social behaviors. We mainly focus on the social model designed for BDI-agents to display socially acceptable decisions. This model is based on an auction mechanism used to coordinate the group activities derived from the character's roles. The model also introduces reciprocity relations between the members of a group and allows the agents to include social tasks to produce realistic behavioral animations. Furthermore, a conversational library provides the set of plans to manage social interactions and to animate from simple chats to more complex negotiations. Th…

Intelligent agentMultimediaHuman–computer interactionVirtual machineComputer scienceReciprocity (social psychology)Multi-agent systemcomputer.software_genreSet (psychology)computerComputer animationSocial behaviorTask (project management)2007 International Conference on Cyberworlds (CW'07)
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Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement

2022

Part of this research was funded by the project RTI2018-096224-J-I00 that has been cofounded by the Spanish Ministry of Science and Innovation, inside the National Program for Fostering Excellence in Scientific and Technical Research, National Subprogram of Knowledge Generation, 2018 call, in the framework of the Spanish National Plan for Scientific and Technical Research and Innovation 2017-2020, and by the European Union, through the European Regional Development Fund, with the main objective of Promoting technological development, innovation and quality research. Part of this work was financially supported by the Italian Ministry of University and Research with the research Grant PRIN 20…

Intel·ligència artificial - Aplicacions a la medicinaArtificial neural networks:Natural Science Disciplines::Mathematics::Data Analysis [DISCIPLINES AND OCCUPATIONS]:disciplinas de las ciencias naturales::matemáticas::análisis de datos [DISCIPLINAS Y OCUPACIONES]Asphalt pavementsIndirect tensile strengthBuilding and ConstructionHot mix asphaltReclaimed asphalt pavementMechanics of Materials:Mathematical Concepts::Algorithms::Artificial Intelligence::Machine Learning [PHENOMENA AND PROCESSES]Machine learningAprenentatge automàticDegree of binder activity:conceptos matemáticos::algoritmos::inteligencia artificial::aprendizaje automático [FENÓMENOS Y PROCESOS]AsfaltSettore ICAR/04 - Strade Ferrovie Ed AeroportiRecyclingGeneral Materials Science:Enginyeria civil::Infraestructures i modelització dels transports::Transport per carretera [Àrees temàtiques de la UPC]Hot mix asphalt Recycling Reclaimed asphalt pavement Degree of binder activity Machine learning Artificial neural networks Random forest Indirect tensile strengthRandom forestCivil and Structural Engineering
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Predicting lorawan behavior. How machine learning can help

2020

Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…

IoTComputer Networks and CommunicationsComputer scienceDecision treeChannel occupancy; cluster analysis; IoT; LoRa; LoRaWAN; machine learning; network optimization; prediction analysisMachine learningcomputer.software_genreChannel occupancyLoRalcsh:QA75.5-76.95network optimizationNetwork performanceProtocol (object-oriented programming)Profiling (computer programming)Artificial neural networkNetwork packetbusiness.industrySettore ING-INF/03 - TelecomunicazioniPipeline (software)LoRaWANHuman-Computer Interactionmachine learningprediction analysisArtificial intelligencelcsh:Electronic computers. Computer sciencebusinesscomputerCommunication channelcluster analysis
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Exploratory approach for network behavior clustering in LoRaWAN

2021

AbstractThe interest in the Internet of Things (IoT) is increasing both as for research and market perspectives. Worldwide, we are witnessing the deployment of several IoT networks for different applications, spanning from home automation to smart cities. The majority of these IoT deployments were quickly set up with the aim of providing connectivity without deeply engineering the infrastructure to optimize the network efficiency and scalability. The interest is now moving towards the analysis of the behavior of such systems in order to characterize and improve their functionality. In these IoT systems, many data related to device and human interactions are stored in databases, as well as I…

IoTGeneral Computer ScienceComputer sciencek-meansReliability (computer networking)02 engineering and technologyLoRaMachine LearningHome automation0202 electrical engineering electronic engineering information engineeringCluster AnalysisWirelessCluster analysisIoT LoRa LoRaWAN Machine Learning k-means Anomaly Detection Cluster AnalysisNetwork packetbusiness.industry020206 networking & telecommunicationsIoT; LoRa; LoRaWAN; Machine Learning; k-means; Anomaly Detection; Cluster AnalysisLoRaWANWireless network interface controllerScalabilityAnomaly Detection020201 artificial intelligence & image processingAnomaly detectionbusinessComputer networkJournal of Ambient Intelligence and Humanized Computing
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A Simulation Analysis of VSM Control for RES plants in a Small Mediterranean Island

2020

The paper presents an application of Virtual Synchronous Machine control for managing inverter-interfaced renewable energy sources in a small Mediterranean island not supplied by the main grid. In the proposed analysis, the island's renewables-based generators area assumed interfaced to the grid by voltage source converters with a swing controller and a vector-current controller with two different options for the reference current for regulating the voltage at the Point of Common Coupling and the active power output. The system, modeled in PScad environment, allows to verify the response of the renewables-based generators with VSM control in the presence of a fault in the grid.

Isolated SystemsSettore ING-IND/11 - Fisica Tecnica AmbientaleComputer sciencebusiness.industry020209 energy020208 electrical & electronic engineering02 engineering and technologyConvertersAC powerGridFault (power engineering)Voltage Source ConverterAutomotive engineeringRenewable energyCurrent ReferenceSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaControl theoryVirtual Synchronous Machines0202 electrical engineering electronic engineering information engineeringRenewable EnergyVoltage sourceSynchronous motorbusinessCurrent Vector Control2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
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Vēstures procesa izpratne Nikolo Makjavelli darbos

2018

Maģistra darbs "Vēstures procesa izpratne Nikolo Makjavelli darbos" ir veltīts vēstures teorijas jautājumiem Nikolo Makjavelli sacerējumos. Pētījuma ietvaros tiek analizēti Makjavelli nozīmīgākie darbi - "Pārdomas par Tita Līvija pirmo dekādi", "Valdnieks" un "Florences vēsture". Pētījuma mērķis ir atspoguļot un analizēt Nikolo Makjavelli darbos paustās idejas par vēstures procesu un to ietekmējošajiem faktoriem. Darba ievadošajā nodaļā ir sniegts ieskats Nikolo Makjavelli biogrāfijā, kā arī Itālijas reģiona un Florences republikas politiskajās un kulturālajās norisēs. Otrajā nodaļā tiek aplūkotas Nikolo Makjavelli politiskās un sociālās idejas. Trešajā nodaļā tiek analizēta metafizisko asp…

Itālijas renesanseFlorences republikaNiccolo MachiavelliNikolo MakjavelliVēstureVēstures process
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On relation between J-integral and heat energy dissipation at the crack tip in stainless steel specimens

2019

In this paper, an experimental procedure to evaluate the elastic-plastic J-integral at the tip of a fatigue crack is presented. According to this new approach, the elastic component of the J-integral is derived from Thermoelastic Stress Analysis, while the plastic component of the J-integral is derived from the heat energy loss. An analytical link is proposed to apply this new experimental technique. Therefore, the elastic-plastic J-integral range was evaluated starting from infrared temperature maps measured in situ during crack propagation tests of AISI 304L stainless steel specimens. It was found that the range of the infrared thermography-based J-integral correlated well the crack growt…

J-integralMaterials scienceInfraredCrack tip plasticityMechanical EngineeringFracture Mechanicslcsh:Mechanical engineering and machineryEnergy methodlcsh:TA630-695Fracture mechanicslcsh:Structural engineering (General)DissipationFracture MechanicFinite element methodStress (mechanics)Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineEnergy methodsThermoelastic dampingMechanics of MaterialsCrack tip plasticity; Energy methods; Fracture Mechanics; J-integral; Thermoelastic Stress AnalysisThermographyRange (statistics)Thermoelastic Stress Analysislcsh:TJ1-1570Composite materialFrattura ed Integrità Strutturale
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Da Harvard a Vienna: Prospettive dell'empirismo fra Mach e James.

2006

James empirismo MachSettore M-FIL/05 - Filosofia E Teoria Dei Linguaggi
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Thermodynamics of a Phase-Driven Proximity Josephson Junction

2019

We study the thermodynamic properties of a superconductor/normal metal/superconductor Josephson junction {in the short limit}. Owing to the proximity effect, such a junction constitutes a thermodynamic system where {phase difference}, supercurrent, temperature and entropy are thermodynamical variables connected by equations of state. These allow conceiving quasi-static processes that we characterize in terms of heat and work exchanged. Finally, we combine such processes to construct a Josephson-based Otto and Stirling cycles. We study the related performance in both engine and refrigerator operating mode.

Josephson effectsns junctionStirling enginesuprajohtavuusGeneral Physics and Astronomy02 engineering and technology01 natural sciences7. Clean energysuprajohteetlaw.inventionlawJosephson junctionMaxwell relationCondensed Matter::Superconductivityquasi-particles entropykvanttifysiikkalcsh:Scienceproximity effect; superconductivity; Josephson junction; SNS junction; Josephson thermodynamics; Maxwell relation; quasi-particles entropy; quantum thermodynamics; quantum machines; quantum coolersPhysicsSuperconductivityQuantum PhysicsCondensed matter physicssuperconductivitySupercurrent021001 nanoscience & nanotechnologyThermodynamic systemlcsh:QC1-999termodynamiikkaproximity effectjosephson thermodynamics0210 nano-technologyRefrigerator carFOS: Physical sciencesJosephson thermodynamicslcsh:AstrophysicsArticleSuperconductivity (cond-mat.supr-con)Entropy (classical thermodynamics)quantum coolers0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)lcsh:QB460-466010306 general physicsquantum machinesPhase differenceCondensed Matter - Mesoscale and Nanoscale PhysicsCondensed Matter - SuperconductivitySNS junctionjosephson junctionmaxwell relationquantum thermodynamicslcsh:QQuantum Physics (quant-ph)lcsh:PhysicsEntropy
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Deep learning for knowledge tracing in learning analytics: An overview

2021

Learning Analytics (LA) is a recent research branch that refers to methods for measuring, collecting, analyzing, and reporting learners’ data, in order to better understand and optimize the processes and the environments. Knowledge Tracing (KT) deals with the modeling of the evolution, during the time, of the students’ learning process. Particularly its aim is to predict students’ outcomes in order to avoid failures and to support both students and teachers. Recently, KT has been tackled by exploiting Deep Learning (DL) models and generating a new, ongoing, research line that is known as Deep Knowledge Tracing (DKT). This was made possible by the digitalization process that has simplified t…

Knowledge Tracing Machine Learning Deep Learning Learning Analytics Educational data Students skills
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