Search results for "UML"

showing 10 items of 407 documents

Functional analysis of Normal and CSNB a-wave ERG component

2009

The features of a-wave of the human electroretinogram are one of the more debated problems in electrophysiology since the a-wave reflects the functional integrity of the two photoreceptoral populations (rods and cones). Although different models concerning the contributions of the early photoreceptoral response are available in current literature, a fully comprehensive theory is difficult to formulate because of the large amount of individual photoreceptors. We study the kinetics of the photoreceptoral response through the analysis of the a-wave shape both in healthy and in patients affected by the Congenital Stationary Night Blindness, that interests the rod population only. The physiologi…

Congenital stationary night blindnessa-waveeducation.field_of_studygenetic structuresPopulationBiologySettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Congenital Stationary Night blindnessComponent (UML)sense organsSet (psychology)educationphotoreceptoral responseNeuroscienceFunctional analysis (psychology)ErgStatistical functionstatistical functionVisual phototransduction
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Extracting modular-based backbones in weighted networks

2021

Abstract Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major issue. In most cases, the so-called backbone extraction methods are based either on coarse-graining or filtering approaches. Coarse-graining techniques reduce the network size by gathering similar nodes into super-nodes, while filter-based methods eliminate nodes or edges according to a statistical property.In…

Connected componentInformation Systems and ManagementBridging (networking)business.industryComputer scienceDistributed computingComplex systemCommunity structureFilter (signal processing)Modular designComputer Science ApplicationsTheoretical Computer ScienceSet (abstract data type)Artificial IntelligenceControl and Systems EngineeringComponent (UML)businessSoftwareInformation Sciences
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A network model for the short-term prediction of the evolution of cocaine consumption in Spain

2010

Cocaine consumption is a social problem with acute consequences and its dependency can be regarded as a health concern of social transmission. This fact leads us to develop the idea that its transmission dynamics can be studied using epidemiological mathematical models. Under this point of view, in this paper we propose a network model to study the short-term evolution of the cocaine consumer subpopulations. The model parameters are obtained from data source and from an analogue continuous model. Sensitivity of the model parameters is studied. The parameters are associated with prevention and treatment policies and the sensitivity study gives us information about which parameters have more …

Consumption (economics)Dependency (UML)Mathematical modelOperations researchComputer scienceContinuous modellingComputer Science ApplicationsTerm (time)Transmission (telecommunications)Modelling and SimulationModeling and SimulationEconometricsSensitivity (control systems)Network modelMathematical and Computer Modelling
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Perceived-Value-driven Optimization of Energy Consumption in Smart Homes

2020

Residential energy consumption has been rising rapidly during the last few decades. Several research efforts have been made to reduce residential energy consumption, including demand response and smart residential environments. However, recent research has shown that these approaches may actually cause an increase in the overall consumption, due to the complex psychological processes that occur when human users interact with these energy management systems. In this article, using an interdisciplinary approach, we introduce a perceived-value driven framework for energy management in smart residential environments that considers how users perceive values of different appliances and how the us…

Consumption (economics)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDependency (UML)Computer Networks and CommunicationsComputer scienceEnergy managementHeuristic020209 energy02 engineering and technologyEnergy consumptionIndustrial engineeringComputer Science ApplicationsDemand responseHardware and Architecture020204 information systemsValue (economics)Smart homes energy consumption perceived-value driven optimization0202 electrical engineering electronic engineering information engineeringInteger programmingSoftwareInformation Systems
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Deep CNN-ELM Hybrid Models for Fire Detection in Images

2018

In this paper, we propose a hybrid model consisting of a Deep Convolutional feature extractor followed by a fast and accurate classifier, the Extreme Learning Machine, for the purpose of fire detection in images. The reason behind using such a model is that Deep CNNs used for image classification take a very long time to train. Even with pre-trained models, the fully connected layers need to be trained with backpropagation, which can be very slow. In contrast, we propose to employ the Extreme Learning Machine (ELM) as the final classifier trained on pre-trained Deep CNN feature extractor. We apply this hybrid model on the problem of fire detection in images. We use state of the art Deep CNN…

Contextual image classificationArtificial neural networkComputer sciencebusiness.industryPattern recognition02 engineering and technologyConvolutional neural networkBackpropagationSupport vector machine03 medical and health sciences0302 clinical medicineSoftmax function0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)030217 neurology & neurosurgeryExtreme learning machine
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Classification based on Iterative Object Symmetry Transform

2004

The paper shows an application of a new operator named the iterated object transform (IOT) for cell classification. The IOT has the ability to grasp the internal structure of a digital object and this feature can be usefully applied to discriminate structured images. This is the case of cells representing chondrocytes in bone tissue, giarda protozoan, and myeloid leukaemia. A tree classifier allows us to discriminate the three classes with a good accuracy.

Contextual image classificationSettore INF/01 - Informaticabusiness.industryIterative methodFeature extractionGRASPCognitive neuroscience of visual object recognitionPattern recognitionIterated functionComputer visionArtificial intelligencebusinessClassifier (UML)Classification Medical imaging clusteringMathematicsDigital object
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Finding essential features for tracking starfish in a video sequence

2004

The paper introduces a software system for detecting and tracking starfish in an underwater video sequence. The target of such a system is to help biologists in giving an estimate of the number of starfish present in a particular area of the sea-bottom. The nature of the input images is characterised by a low signal/noise ratio and by the presence of noisy background represented by pebbles; this makes the detection a non-trivial task. The procedure we use is a chain of several steps that starts from the extraction of the area of interest and ends with a classifier and a tracker providing the necessary information for counting the starfish present in the scene. © 2003 IEEE.

Contextual image classificationbiologySettore INF/01 - InformaticaEstimation theoryComputer sciencebusiness.industryStarfishFeature extractionbiology.organism_classificationObject detectionComputer visionArtificial intelligenceSoftware systemUnderwaterbusinessClassifier (UML)underwater video sequence starfish features extraction.
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Graph matching for efficient classifiers adaptation

2011

In this work we present an adaptation algorithm focused on the description of the measurement changes under different acquisition conditions. The adaptation is carried out by transforming the manifold in the first observation conditions into the corresponding manifold in the second. The eventually non-linear transform is based on vector quantization and graph matching. The transfer learning mapping is defined in an unsupervised manner. Once this mapping has been defined, the labeled samples in the first are projected into the second domain, thus allowing the application of any classifier in the transformed domain. Experiments on VHR series of images show the validity of the proposed method …

Contextual image classificationbusiness.industryImage matchingVector quantizationVector quantisationPattern recognitionManifoldSupport vector machineLife ScienceArtificial intelligenceTransfer of learningbusinessClassifier (UML)Mathematics
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The functional-psychological continuum in the cognitive image of a destination: A confirmatory analysis

2009

Abstract This paper analyses the cognitive component of the image of a destination from a dual perspective. Firstly, we study its composition by positing three positions on a continuum: functional, mixed and psychological, which are analysed using confirmatory factor analysis. Secondly, we study the influence of these components on tourists' overall image of the destination and on their future behaviour intentions, using structural equation analysis. The results show that the psychological and functional components exercise the greatest influence on the overall image of the destination. Overall image was found to influence future behaviour intentions consistently, while the functional compo…

Continuum (measurement)Strategy and Managementmedia_common.quotation_subjectPerspective (graphical)TransportationCognitionDevelopmentConfirmatory factor analysisImage (mathematics)Dual (category theory)Tourism Leisure and Hospitality ManagementPerceptionComponent (UML)PsychologySocial psychologymedia_commonTourism Management
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Model Based Design Optimization of Operational Reliability in Offshore Boom Cranes

2013

AbstractThis paper presents a model based approach for design of reliable electro-hydraulic motion control systems for offshore material handling cranes. The approach targets the system engineer and is based on steady-state computations, dynamic time domain simulation and numerical optimization.In general, the modelling takes into account the limited access to component data normally encountered by engineers working with system design. A system model is presented which includes the most important characteristics of both mechanical system and hydraulic components such as the directional control valve and the counterbalance valve.The model is used to optimize the performance of an initial des…

Control valvesEngineeringbusiness.industryMechanical EngineeringGeneral Physics and AstronomyControl engineeringMotion controlBoomSystem modelMechanical systemComponent (UML)Model-based designSystems designbusinessInternational Journal of Fluid Power
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