Search results for "intelligence"

showing 10 items of 6959 documents

Discrete Tomography Reconstruction Through a New Memetic Algorithm

2008

Discrete tomography is a particular case of computerized tomography that deals with the reconstruction of objects made of just one homogeneous material, where it is sometimes possible to reduce the number of projections to no more than four. Most methods for standard computerized tomography cannot be applied in the former case and ad hoc techniques must be developed to handle so few projections.

Tomographic reconstructionSettore INF/01 - Informaticabusiness.industryBinary imageGenetic algorithmInstrumental noiseMemetic algorithmComputer visionTomographyArtificial intelligenceDiscrete Tomography Memetic Algorithms Evolutionary methods.businessDiscrete tomographyMathematics
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Blind Radio Tomography

2018

From the attenuation measurements collected by a network of spatially distributed sensors, radio tomography constructs spatial loss fields (SLFs) that quantify absorption of radiofrequency waves at each location. These SLFs can be used for interference prediction in (possibly cognitive) wireless communication networks, for environmental monitoring or intrusion detection in surveillance applications, for through-the-wall imaging, for survivor localization after earthquakes or fires, etc. The cornerstone of radio tomography is to model attenuation as the bidimensional integral of the SLF of interest scaled by a weight function. Unfortunately, existing approaches (i) rely on heuristic assumpti…

Tomographic reconstructionbusiness.industryComputer scienceAttenuationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020206 networking & telecommunications02 engineering and technologyInterference (wave propagation)Signal Processing0202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingTomographyElectrical and Electronic EngineeringbusinessAlgorithmRadio tomography
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Multi-label Classification Using Stacked Hierarchical Dirichlet Processes with Reduced Sampling Complexity

2018

Nonparametric topic models based on hierarchical Dirichlet processes (HDPs) allow for the number of topics to be automatically discovered from the data. The computational complexity of standard Gibbs sampling techniques for model training is linear in the number of topics. Recently, it was reduced to be linear in the number of topics per word using a technique called alias sampling combined with Metropolis Hastings (MH) sampling. We propose a different proposal distribution for the MH step based on the observation that distributions on the upper hierarchy level change slower than the document-specific distributions at the lower level. This reduces the sampling complexity, making it linear i…

Topic modelComputational complexity theoryComputer science02 engineering and technologyLatent Dirichlet allocationDirichlet distributionsymbols.namesakeArtificial Intelligence020204 information systems0202 electrical engineering electronic engineering information engineeringMathematicsMulti-label classificationbusiness.industrySampling (statistics)Pattern recognitionHuman-Computer InteractionDirichlet processMetropolis–Hastings algorithmHardware and ArchitectureTest setsymbols020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithmSoftwareInformation SystemsGibbs sampling2017 IEEE International Conference on Big Knowledge (ICBK)
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A Survey of Multi-Label Topic Models

2019

Every day, an enormous amount of text data is produced. Sources of text data include news, social media, emails, text messages, medical reports, scientific publications and fiction. To keep track of this data, there are categories, key words, tags or labels that are assigned to each text. Automatically predicting such labels is the task of multi-label text classification. Often however, we are interested in more than just the pure classification: rather, we would like to understand which parts of a text belong to the label, which words are important for the label or which labels occur together. Because of this, topic models may be used for multi-label classification as an interpretable mode…

Topic modelInformation retrievalComputer scienceGeography Planning and DevelopmentFlexibility (personality)02 engineering and technologyTask (project management)ComputingMethodologies_PATTERNRECOGNITION020204 information systems0202 electrical engineering electronic engineering information engineeringKey (cryptography)General Earth and Planetary Sciences020201 artificial intelligence & image processingSocial mediaWater Science and TechnologyACM SIGKDD Explorations Newsletter
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Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

2020

With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…

Topic modelshort textInformation retrievalSocial networkbusiness.industryLatent semantic analysisComputer scienceRandom projectiontopic modelingUser-generated contentSubject (documents)Context (language use)Latent Dirichlet allocationlcsh:QA75.5-76.95symbols.namesakeArtificial Intelligenceonline social networkssymbolsMethodslcsh:Electronic computers. Computer sciencenatural language processingbusinessuser-generated contentFrontiers in Artificial Intelligence
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Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates

2022

Abstract Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This study aimed to provide a new approach with better performance for landslide mapping and adopting readily available variables. In addition, it investigates the capability of a state-of-the-art model developed using the group method of data handling (GMDH) to spatially model LS. Furthermore, hybridized models of GMDH were developed using different metaheuristic algorithms. The study area was the Bonghwa region of South Korea, for which an accurate landslide inventory dataset is available. We considered a total of 13 spatial covariates (altitude, slope, aspect, topographic wetness index, val…

Topographic Wetness IndexVariablesReceiver operating characteristicMean squared errorGroup method of data handlingmedia_common.quotation_subjectLandslideArtificial intelligence Data-scarcity Factor selection GIS Natural disasterscomputer.software_genreRegressionCovariateData miningcomputerEarth-Surface Processesmedia_commonMathematicsCATENA
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Topographic maps for clustering and fast identification of bacteria using 16s housekeeping gene

2012

In microbial identification the standard method to attribute a specific name to a bacterial isolate relays on the comparison of morphologic and phenotypic characters to those described for type or typical strains. In the last years a new standard for identifying bacteria using genotypic information began to be developed. In this new approach phylogenetic relationships of bacteria could be determined by comparing a stable part of the bacteria genetic code, the so called "housekeeping genes". The most commonly used gene for taxonomic purposes for bacteria is the 16S rRNA. The goal of this chapter is to show that genotypic features can be used to build a topographic map for clustering of a lar…

Topographic map clusteringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial Intelligence
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On inductive dimensions for fuzzy topological spaces

1995

An approach to the dimension theory for fuzzy topological spaces is being developed. The appropriate context for this theory is not the category CFT of Chang fuzzy topological spaces or some of its modifications, but the category Hut introduced in the paper (this category is a slight extension of the category H of Hutton fuzzy topological spaces Hutton (1980). The frames of this category allow us to make exposition simple and uniform, and on the other hand to make it applicable in quite a general setting.

Topological algebraLogicTopological tensor productTopological spaceTopologyTopological vector spaceHomeomorphismAlgebraArtificial IntelligenceMathematics::Category TheoryDimension theoryCategory of topological spacesMathematicsZero-dimensional spaceFuzzy Sets and Systems
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Mixed Harmonic Elimination Control for a Single-Phase 9 Level Grid-Connected Inverter

2018

The power quality requirements are increasingly stringent, due to the continuous growth of devices connected to the grid that introduce harmonics. These devices include DC to AC energy conversion systems, i.e. grid connected inverters. The design, control and operation of these systems must take into account the rules of interconnection to the electricity grid. To improve the quality of the output waveform of the grid-connected inverter, Multilevel Converters (MC) with selective harmonic elimination modulation technique can be used. This paper presents a single-phase nine level grid-connected inverter with DC/DC input stages. The obtained switching angles for THD minimization are independen…

Total harmonic distortionselective Harmonic elimination (SHE)business.industryComputer scienceTotal Harmonic Distortion (THD)Electrical engineeringModulation indexEnergy Engineering and Power TechnologyConvertersAC powerGridDC-AC conversionHarmonic MitigationSettore ING-IND/31 - ElettrotecnicaComputer Networks and CommunicationArtificial IntelligenceHarmonicsMultilevel InverterWaveformInverterSafety Risk Reliability and Qualitybusiness2018 International Conference on Smart Grid (icSmartGrid)
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Expressing digression linguistically: Do digressive markers exist?

2009

Abstract This paper analyzes the relationship between digressions and topic shifts in the light of the Spanish marker por cierto . Against the standard explanation, which takes digression as a well-established linguistic operation, digression is regarded as a rhetorical operation, underspecified at the linguistic level. The most conspicuous trace of digression, the so-called digressive markers , cannot be distinguished from topic shifters on the basis of the instruction provided by the marker alone. Thus, both types of markers should be grouped together as a single class, that of “new relevant information markers” (NRIMs). The perceived differences between topic shifters and digressive mark…

Trace (semiology)Linguistics and LanguageArtificial IntelligenceRhetorical questionSingle classPragmaticsPsychologyRelevant informationLanguage and LinguisticsDiscourse markerDigressionLinguisticsJournal of Pragmatics
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