Search results for "Fluid flow"

showing 10 items of 405 documents

Microemulsion encapsulated into halloysite nanotubes and their applications for cleaning of a marble surface

2018

Halloysite nanotubes were used to incorporate anionic surfactant micelles and an organic solvent to generate a cleaning system to be applied in Cultural Heritage restoration. The targeted adsorption is driven by electrostatic interactions based on the nanotubes peculiar charge separation. Namely anionic species are driven to the positively charged inner surface while being prevented from interacting with the halloysite outer surface that possesses a positive charge density. The hybrid organic/inorganic emulsion was characterized by dynamic light scattering. Analysis of the autocorrelation function allowed us to define the presence of surfactant aggregates inside/outside the nanotube lumen a…

Cleaning agentNanotubeMaterials scienceCultural heritages; Halloysite nanotubes; Polyacrylonitrile; SurfactantHalloysite nanotube02 engineering and technologyhalloysite nanotubesengineering.materialPolyacrylonitrile010402 general chemistry01 natural sciencesMicelleHalloysitelcsh:Technologylcsh:ChemistryPulmonary surfactantSurfactantGeneral Materials ScienceMicroemulsionInstrumentationlcsh:QH301-705.5Settore CHIM/02 - Chimica FisicaFluid Flow and Transfer Processeslcsh:TProcess Chemistry and TechnologyGeneral Engineeringcultural heritages021001 nanoscience & nanotechnologyElectrospinninglcsh:QC1-9990104 chemical sciencesComputer Science ApplicationsChemical engineeringlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040EmulsionengineeringCultural heritage0210 nano-technologylcsh:Engineering (General). Civil engineering (General)lcsh:Physics
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Project Management Information Systems (PMISs): A Statistical-Based Analysis for the Evaluation of Software Packages Features

2021

Project Managers (PMs) working in competitive markets are finding Project Management Information Systems (PMISs) useful for planning, organizing and controlling projects of varying complexity. A wide variety of PMIS software is available, suitable for projects differing in scope and user needs. This paper identifies the most useful features found in PMISs. An extensive literature review and analysis of commercial software is made to identify the main features of PMISs. Afterwards, the list is reduced by a panel of project management experts, and a statistical analysis is performed on data acquired by means of two different surveys. The relative importance of listed features is properly comp…

Clustering; Conjoint analysis; Design of Experiment (DoE); Project Management Information System (PMIS); Ranking method; Surveyranking methodTechnologyComputer scienceQH301-705.5QC1-999SoftwareSettore ING-IND/17 - Impianti Industriali MeccaniciGeneral Materials SciencesurveyProject managementBiology (General)Cluster analysisInstrumentationQD1-999Fluid Flow and Transfer ProcessesCommercial softwareScope (project management)business.industryProcess Chemistry and TechnologyTPhysicsGeneral EngineeringProject Management Information System (PMIS); survey; Design of Experiment (DoE); conjoint analysis; ranking method; clusteringClustering Conjoint analysis Design of Experiment (DoE) Project Management Information System (PMIS) Ranking method SurveyProject Management Information System (PMIS)Engineering (General). Civil engineering (General)Data scienceDesign of Experiment (DoE)Computer Science ApplicationsConjoint analysisVariety (cybernetics)ChemistryRespondentconjoint analysisTA1-2040businessclusteringApplied Sciences; Volume 11; Issue 23; Pages: 11233
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Deep CNN for IIF Images Classification in Autoimmune Diagnostics

2019

The diagnosis and monitoring of autoimmune diseases are very important problem in medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An indirect immunofluorescence (IIF) test performed by Human Epithelial type 2 (HEp-2) cells as substrate antigen is the most common methods to determine ANA. In this paper we present an automatic HEp-2 specimen system based on a convolutional neural network method able to classify IIF images. The system consists of a module for features extraction based on a pre-trained AlexNet network and a classification phase for the cell-pattern association using six support vector machines and a k-nearest neighbors classifier. The class…

Computer science02 engineering and technologyConvolutional neural networklcsh:TechnologyIIF imageAlexNetlcsh:Chemistry03 medical and health sciencesconvolutional neural networks (CNNs)Autoimmune diseaseClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringGeneral Materials Scienceautoimmune diseasesInstrumentationlcsh:QH301-705.5030304 developmental biologyIIF imagesFluid Flow and Transfer Processes0303 health sciencesDeep cnnIndirect immunofluorescenceaccuracybusiness.industrylcsh:TProcess Chemistry and Technologyk-nearest neighbors (KNN)General EngineeringPattern recognitionIIfClass (biology)lcsh:QC1-999Computer Science ApplicationsSupport vector machinelcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040System parameters020201 artificial intelligence & image processingsupport vector machine (SVM)Artificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsApplied Sciences
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A Damage Identification Approach for Offshore Jacket Platforms Using Partial Modal Results and Artificial Neural Networks

2018

This paper presents a damage identification method for offshore jacket platforms using partially measured modal results and based on artificial intelligence neural networks. Damage identification indices are first proposed combining information of six modal results and natural frequencies. Then, finite element models are established, and damages in structural members are assumed by reducing the structural elastic modulus. From the finite element analysis for a training sample, both the damage identification indices and the damages are obtained, and neural networks are trained. These trained networks are further tested and used for damage prediction of structural members. The calculation res…

Computer science020101 civil engineering02 engineering and technologylcsh:Technology0201 civil engineeringWaterlinejacket platformlcsh:Chemistrysymbols.namesake0203 mechanical engineeringGeneral Materials Sciencenatural frequenciesInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processesdamage identification indexfinite element modelArtificial neural networkbusiness.industrylcsh:TProcess Chemistry and Technologymodal shapesGeneral EngineeringStructural engineeringFinite element methodlcsh:QC1-999Computer Science ApplicationsIdentification (information)020303 mechanical engineering & transportsModallcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040symbolsSubmarine pipelinebusinesslcsh:Engineering (General). Civil engineering (General)artificial neural networkslcsh:Physics
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A review of thermochemical energy storage systems for power grid support

2020

Power systems in the future are expected to be characterized by an increasing penetration of renewable energy sources systems. To achieve the ambitious goals of the “clean energy transition”, energy storage is a key factor, needed in power system design and operation as well as power-to-heat, allowing more flexibility linking the power networks and the heating/cooling demands. Thermochemical systems coupled to power-to-heat are receiving an increasing attention due to their better performance in comparison with sensible and latent heat storage technologies, in particular, in terms of storage time dynamics and energy density. In this work, a comprehensive review of the state of art of theore…

Computer science020209 energyPower-to-heat02 engineering and technologyThermal energy storagelcsh:TechnologyEnergy storagelcsh:ChemistryElectric power systemLoad managementVariable renewable energy0202 electrical engineering electronic engineering information engineeringGeneral Materials SciencePower grid supportProcess engineeringThermochemical storageInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer ProcessesFlexibility (engineering)Settore ING-IND/11 - Fisica Tecnica Ambientalebusiness.industrylcsh:TProcess Chemistry and TechnologyGeneral Engineering021001 nanoscience & nanotechnologylcsh:QC1-999Computer Science ApplicationsRenewable energythermochemical storage sorption heat storage power-to-heat power grid supportlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040System integration0210 nano-technologybusinesslcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsSorption heat storage
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Effect of Demand Side Management on the Operation of PV-Integrated Distribution Systems

2020

In this new era of high electrical energy dependency, electrical energy must be abundant and reliable, thus smart grids are conducted to deliver load demands. Hence, smart grids are implemented alongside distributed generation of renewable energies to increase the reliability and controllability of the grid, but, with the very volatile nature of the Distributed Generation (DG), Demand Side Management (DSM) helps monitor and control the load shape of the consumed power. The interaction of DSM with the grid provides a wide range of mutual benefits to the user, the utility and the market. DSM methodologies such as Conservation Voltage Reduction (CVR) and Direct Load Control (DLC) collaborate i…

Computer science020209 energyReliability (computer networking)conservation voltage reductiondistribution systems02 engineering and technologylcsh:TechnologyReduction (complexity)lcsh:Chemistry0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceInstrumentationlcsh:QH301-705.5distribution systemFluid Flow and Transfer Processesdistributed generationdemand side managementVoltage reductionbusiness.industrylcsh:TProcess Chemistry and Technology020208 electrical & electronic engineeringPhotovoltaic systemGeneral Engineeringdirect load controlGridlcsh:QC1-999Computer Science ApplicationsReliability engineeringRenewable energySettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSmart gridlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Distributed generationbusinesslcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsApplied Sciences
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Explainable Post-Occupancy Evaluation Using a Humanoid Robot

2020

The paper proposes a new methodological approach for evaluating the comfort condition using the concept of explainable post occupancy to make the user aware of the environmental state in which (s)he works. Such an approach was implemented on a humanoid robot with social capabilities that aims to enforce human engagement to follow recommendations. The humanoid robot helps the user to position the sensors correctly to acquire environmental measures corresponding to the temperature, humidity, noise level, and illuminance. The distribution of the last parameter due to its high variability is also retrieved by the simulation software Dialux. Using the post occupancy evaluation method, the robot …

Computer science0211 other engineering and technologieslighting simulation software02 engineering and technologyPost-occupancy evaluationlcsh:Technologylcsh:Chemistry021105 building & constructionGeneral Materials Science021108 energyInstrumentationlcsh:QH301-705.5SimulationFluid Flow and Transfer Processeshumanoid robotlcsh:TProcess Chemistry and TechnologyGeneral Engineeringlcsh:QC1-999Computer Science ApplicationsExplainable post occupancy Humanoid robot Lighting simulation softwarelcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040lcsh:Engineering (General). Civil engineering (General)Humanoid robotlcsh:Physicsexplainable post occupancy
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Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things

2021

In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, we study the application of a WASN for room acoustic measurements. To evaluate the acoustic characteristics, a set of Raspberry Pi 3 (RPi) has been used. One is used to play different acoustic signals and four are used to record at different points in the room simultaneously. The signals are sent wirelessly to a computer connected to a server, where using MATLAB we calculate both the impulse response (IR…

Computer scienceAcoustics01 natural scienceslcsh:TechnologySet (abstract data type)lcsh:Chemistry030507 speech-language pathology & audiology03 medical and health sciencesWASNroom acousticsWirelessGeneral Materials ScienceMATLABInstrumentationlcsh:QH301-705.5Impulse responsecomputer.programming_languageFluid Flow and Transfer ProcessesMeasure (data warehouse)room parameters estimationbusiness.industrylcsh:TProcess Chemistry and Technology010401 analytical chemistryGeneral Engineeringspeech intelligibility indexRoom acousticslcsh:QC1-9990104 chemical sciencesComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999Asynchronous communicationlcsh:TA1-2040impulse response0305 other medical scienceInternet of Thingsbusinesslcsh:Engineering (General). Civil engineering (General)computerlcsh:PhysicsApplied Sciences
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Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks

2019

Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor networks (WASNs) can be an interesting solution for monitoring subjective annoyance in certain soundscapes, since they can be used to register the evolution of such parameters in time and space. Unfortunately, the calculation of the psycho-acoustic parameters involved in common annoyance models implies a significant computational cost, and makes difficult the acquisition and transmission of these parameters at the nodes. As a result, monitoring psycho-acoustic annoyance becomes an expensive and inefficient task. Thi…

Computer scienceComputationsubjective annoyanceContext (language use)Annoyance02 engineering and technologycomputer.software_genre01 natural sciencesConvolutional neural networklcsh:TechnologyReduction (complexity)lcsh:Chemistryconvolutional neural networks0202 electrical engineering electronic engineering information engineeringWirelessGeneral Materials Sciencewireless acoustic sensor networksInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processesbusiness.industrylcsh:TProcess Chemistry and Technology010401 analytical chemistryGeneral EngineeringRegression analysislcsh:QC1-9990104 chemical sciencesComputer Science Applicationspsycho-acoustic parametersTransmission (telecommunications)lcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingData miningbusinesslcsh:Engineering (General). Civil engineering (General)Zwicker modelcomputerlcsh:PhysicsApplied Sciences
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Improving Lossless Image Compression with Contextual Memory

2019

With the increased use of image acquisition devices, including cameras and medical imaging instruments, the amount of information ready for long term storage is also growing. In this paper we give a detailed description of the state-of-the-art lossless compression software PAQ8PX applied to grayscale image compression. We propose a new online learning algorithm for predicting the probability of bits from a stream. We then proceed to integrate the algorithm into PAQ8PX&rsquo

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONgeometric weightingData_CODINGANDINFORMATIONTHEORY02 engineering and technologylcsh:TechnologylosslessGrayscale030218 nuclear medicine & medical imagingImage (mathematics)lcsh:Chemistry03 medical and health sciences0302 clinical medicineProbabilistic methodSoftware0202 electrical engineering electronic engineering information engineeringprobabilistic methodGeneral Materials Sciencelcsh:QH301-705.5InstrumentationFluid Flow and Transfer ProcessesLossless compressioncontextual informationlcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringEnsemble learninglcsh:QC1-999image compressionComputer Science ApplicationsTerm (time)lcsh:Biology (General)lcsh:QD1-999Computer engineeringlcsh:TA1-2040ensemble learning020201 artificial intelligence & image processinglcsh:Engineering (General). Civil engineering (General)businesslcsh:PhysicsImage compressionApplied Sciences
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