Search results for "Nuclear engineering"

showing 10 items of 533 documents

Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

2020

Despite significant effort, building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of the underlying inference. Using a linear combination of conjunctive clauses in propositional logic, Tsetlin Machines (TMs) have shown competitive performance on diverse benchmarks. However, to do so, many clauses are needed, which impacts interpretability. Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights. The resulting Integer Weighted TM (…

FOS: Computer and information sciencesBoosting (machine learning)Theoretical computer scienceinteger-weighted Tsetlin machineGeneral Computer ScienceComputer scienceComputer Science - Artificial Intelligence0206 medical engineeringNatural language understandingInference02 engineering and technologycomputer.software_genre0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceTsetlin machineVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550InterpretabilityArtificial neural networkLearning automatabusiness.industryDeep learningGeneral Engineeringinterpretable machine learningrule-based learninginterpretable AIPropositional calculusSupport vector machineArtificial Intelligence (cs.AI)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESXAIPattern recognition (psychology)020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligencebusinesslcsh:TK1-9971computer020602 bioinformaticsInteger (computer science)
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Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications

2019

Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…

FOS: Computer and information sciencesComputer Science - Machine LearningGeneral Computer ScienceComputer sciencetext categorizationNatural language understandingDecision treeMachine Learning (stat.ML)02 engineering and technologyVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Annen informasjonsteknologi: 559Machine learningcomputer.software_genresupervised learningMachine Learning (cs.LG)Naive Bayes classifierText miningStatistics - Machine Learning0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceTsetlin machinehealth informaticsInterpretabilityPropositional variableClassification algorithmsArtificial neural networkbusiness.industryDeep learning020208 electrical & electronic engineeringGeneral EngineeringRandom forestSupport vector machinemachine learningCategorization020201 artificial intelligence & image processingArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringbusinessPrecision and recallcomputerlcsh:TK1-9971
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A Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions

2020

The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic …

FOS: Computer and information sciencesComputer science02 engineering and technologylcsh:Technology01 natural sciencesArticleComputational Engineering Finance and Science (cs.CE)0103 physical sciencesCluster (physics)Effective methodGeneral Materials ScienceComputer Science - Computational Engineering Finance and Sciencelcsh:Microscopy010306 general physicslcsh:QC120-168.85lcsh:QH201-278.5Pixellcsh:Tmulti-scale entropic descriptorsrandom heterogeneous materials021001 nanoscience & nanotechnologyMicrostructureStandard techniqueCement pastetwo-stage reconstructionlcsh:TA1-2040simulated annealing for clustersSimulated annealinglcsh:Descriptive and experimental mechanicslcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:Engineering (General). Civil engineering (General)0210 nano-technologylcsh:TK1-9971AlgorithmMaterials
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Modeling Networks of Probabilistic Memristors in SPICE

2021

Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…

FOS: Computer and information sciencesHardware_MEMORYSTRUCTURESCondensed Matter - Mesoscale and Nanoscale PhysicsFOS: Physical sciencesComputer Science - Emerging TechnologiesComputer Science::Hardware ArchitectureEmerging Technologies (cs.ET)Computer Science::Emerging TechnologiesmemristorsspicenetworksMesoscale and Nanoscale Physics (cond-mat.mes-hall)lcsh:Electrical engineering. Electronics. Nuclear engineeringprobabilistic computinglcsh:TK1-9971Radioengineering
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Acoustic Scene Classification with Squeeze-Excitation Residual Networks

2020

Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene location (e. g. park, airport, etc.). Many state-of-the-art solutions to ASC incorporate data augmentation techniques and model ensembles. However, considerable improvements can also be achieved only by modifying the architecture of convolutional neural networks (CNNs). In this work we propose two novel squeeze-excitation blocks to improve the accuracy of a CNN-based ASC framework based on residual learning. The main idea of squeeze-excitation blocks is to learn spatial and channel-wise feature maps independently…

FOS: Computer and information sciencesSound (cs.SD)Computer Science - Machine LearningGeneral Computer ScienceCalibration (statistics)Computer scienceResidualConvolutional neural networkField (computer science)Computer Science - SoundMachine Learning (cs.LG)030507 speech-language pathology & audiology03 medical and health sciencesAudio and Speech Processing (eess.AS)Acoustic scene classificationFeature (machine learning)FOS: Electrical engineering electronic engineering information engineeringGeneral Materials ScienceBlock (data storage)Artificial neural networkbusiness.industrypattern recognitionGeneral Engineeringdeep learningPattern recognitionmachine listeningsqueeze-excitationArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineering0305 other medical sciencebusinesslcsh:TK1-9971Electrical Engineering and Systems Science - Audio and Speech Processing
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Ohmic Contacts on p-Type Al-Implanted 4H-SiC Layers after Different Post-Implantation Annealings

2019

This paper reports on the electrical activation and Ohmic contact properties on p-type Al-implanted silicon carbide (4H-SiC). In particular, the contacts were formed on 4H-SiC-implanted layers, subjected to three different post-implantation annealing processes, at 1675 &deg

FabricationMaterials science4H-SiCAnnealing (metallurgy)02 engineering and technology01 natural scienceslcsh:TechnologyArticlechemistry.chemical_compound0103 physical sciencesSilicon carbideGeneral Materials ScienceComposite materiallcsh:MicroscopyOhmic contactlcsh:QC120-168.85010302 applied physicsion-implantationDopantlcsh:QH201-278.5lcsh:TContact resistanceohmic contacts021001 nanoscience & nanotechnologyAcceptor3. Good healthIon implantationchemistrylcsh:TA1-2040lcsh:Descriptive and experimental mechanicslcsh:Electrical engineering. Electronics. Nuclear engineering0210 nano-technologylcsh:Engineering (General). Civil engineering (General)lcsh:TK1-9971Materials
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Toward Optimal LSTM Neural Networks for Detecting Algorithmically Generated Domain Names

2021

Malware detection is a problem that has become particularly challenging over the last decade. A common strategy for detecting malware is to scan network traffic for malicious connections between infected devices and their command and control (C&C) servers. However, malware developers are aware of this detection method and begin to incorporate new strategies to go unnoticed. In particular, they generate domain names instead of using static Internet Protocol addresses or regular domain names pointing to their C&C servers. By using a domain generation algorithm, the effectiveness of the blacklisting of domains is reduced, as the large number of domain names that must be blocked g…

Feature engineeringGeneral Computer ScienceArtificial neural networkComputer sciencebusiness.industrymalwareDeep learningGeneral EngineeringDeep learningdomain generation algorithmscomputer.software_genreBlacklistDomain (software engineering)TK1-9971ServerMalwareGeneral Materials ScienceNetwork performanceArtificial intelligenceData miningElectrical engineering. Electronics. Nuclear engineeringbusinessLSTMcomputerIEEE Access
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Optical sectioning microscopy through single-shot Lightfield protocol

2020

Optical sectioning microscopy is usually performed by means of a scanning, multi-shot procedure in combination with non-uniform illumination. In this paper, we change the paradigm and report a method that is based in the light field concept, and that provides optical sectioning for 3D microscopy images after a single-shot capture. To do this we fi rst capture multiple orthographic perspectives of the sample by means of Fourier-domain integral microscopy (FiMic). The second stage of our protocol is the application of a novel refocusing algorithm that is able to produce optical sectioning in real time, and with no resolution worsening, in the case of sparse f luorescent samples.We provide the…

FiMicGeneral Computer ScienceOptical sectioningComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology3d microscopy01 natural sciences010309 opticsOptics0103 physical sciencesMicroscopyGeneral Materials ScienceProtocol (object-oriented programming)Fourier integral microscopebusiness.industryResolution (electron density)Orthographic projectionGeneral EngineeringSingle shotfourier lightfield microscopeGPU computingÒptica021001 nanoscience & nanotechnologySample (graphics)Microscòpialightfield microscopeoptical sectioninglcsh:Electrical engineering. Electronics. Nuclear engineering0210 nano-technologybusinesslcsh:TK1-9971
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Numerical simulation of the transient thermal-hydraulic behaviour of the ITER blanket cooling system under the draining operational procedure

2015

Abstract Within the framework of the research and development activities supported by the ITER Organization on the blanket system issues, an intense analysis campaign has been performed at the University of Palermo with the aim to investigate the thermal-hydraulic behaviour of the cooling system of a standard 20° sector of ITER blanket during the draining transient operational procedure. The analysis has been carried out following a theoretical-computational approach based on the finite volume method and adopting the RELAP5 system code. In a first phase, attention has been focused on the development and validation of the finite volume models of the cooling circuits of the most demanding mod…

Finite volume methodRELAP5Computer simulationMechanical EngineeringNuclear engineeringBlanketCoolantThermal hydraulicsblanketNuclear Energy and EngineeringThermal-hydraulicWater coolingThermal-hydraulic RELAP5 Draining BlanketEnvironmental scienceGeneral Materials ScienceTransient (oscillation)drainingSettore ING-IND/19 - Impianti NucleariCivil and Structural EngineeringElectronic circuit
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Analysis of steady state thermal-hydraulic behaviour of the DEMO Divertor cassette body cooling circuit

2017

Abstract Within the framework of the Work Package DIV 1 – “Divertor Cassette Design and Integration” of the EUROfusion action, a research campaign has been jointly carried out by ENEA and University of Palermo to investigate the thermal-hydraulic performances of the DEMO divertor cassette cooling system. A comparative evaluation study has been performed considering the two different options under consideration for the divertor cassette body coolant, namely subcooled pressurized water and helium. The research activity has been carried out following a theoretical-computational approach based on the finite volume method and adopting a qualified Computational Fluid-Dynamic (CFD) code. CFD analy…

Finite volume methodSteady statebusiness.industryMechanical EngineeringNuclear engineeringDivertorComputational fluid dynamicsDEMO Divertor Cassette body CFD analysisThermofluid-dynamics7. Clean energy01 natural sciences010305 fluids & plasmasCoolantSubcoolingThermal hydraulicsMaterials Science(all)Nuclear Energy and Engineering0103 physical sciencesWater coolingEnvironmental scienceGeneral Materials Science010306 general physicsbusinessSettore ING-IND/19 - Impianti NucleariCivil and Structural Engineering
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