Search results for "Data analysi"

showing 10 items of 391 documents

A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics

2015

Real data from manufacturing processes are essential to create useful insights for decision-making. However, acquiring real manufacturing data can be expensive and time consuming. To address this issue, we implement a virtual milling machine model to generate machine monitoring data from process plans. MTConnect is used to report the monitoring data. This paper presents (1) the characteristics and specification of milling machine tools, (2) the architecture for implementing the virtual milling machine model, and (3) the integration with a simulation environment for extending to a virtual shop floor model. This paper also includes a case study to explain how to use the virtual milling machin…

Engineeringbusiness.product_categoryMTConnect[ INFO ] Computer Science [cs]Process (engineering)business.industryComputerApplications_COMPUTERSINOTHERSYSTEMSData generatorPredictive analyticsSTEPIndustrial engineeringMachine toolManufacturing dataMTConnectMonitoring dataData analyticsData generatorData analysis[INFO]Computer Science [cs]businessSimulationMilling
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THE “ZISA” IN PALERMO: BIOCLIMATIC ASPECTS OF ITS ARCHITECTURE

2010

In the present work is examined, as an ante-litteram example of summer residence and bioclimatic archi-tecture, the ancient castle of the Zisa (from the Arabic 'al-aziz = noble, shining, glorious), meaningful work of Arab-Islamic character built up at the beginnings of the XII century (fig. 1). The building holds a notable importance as it is one of the few examples of Norman civil architecture with elements of Arab-Islamic character and Byzantian culture, but also because it had been conceived according to the most re-fined Islamic techniques of free cooling. The building (fig. 1) presents itself like a massive rectangular construction developed on three levels. On the architectural plan t…

Environmental contitionSettore ING-IND/11 - Fisica Tecnica AmbientaleClimatic data analysisBioclimatic ArchitectureHistorical heiritage
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Two Half-Truths Make a Whole? On Bias in Self-Reports and Tracking Data

2019

The pervasive use of mobile information technologies brings new patterns of media usage, but also challenges to the measurement of media exposure. Researchers wishing to, for example, understand the nature of selective exposure on algorithmically driven platforms need to precisely attribute individuals’ exposure to specific content. Prior research has used tracking data to show that survey-based self-reports of media exposure are critically unreliable. So far, however, little effort has been invested into assessing the specific biases of tracking methods themselves. Using data from a multimethod study, we show that tracking data from mobile devices is linked to systematic distortions in sel…

Erhebungstechniken und Analysetechniken der SozialwissenschaftenSozialwissenschaften SoziologieNutzungComputer sciencebusiness.industrydigital traces; media exposure; nonreactive measurement; quantitative methods; self-reports; survey; tracking datautilizationGeneral Social SciencesInformation technologyDigitale MedienLibrary and Information SciencesData scienceComputer Science Applicationsdata captureMethods and Techniques of Data Collection and Data Analysis Statistical Methods Computer Methodsddc:300MessungTracking datameasurementDatengewinnungbusinessSocial sciences sociology anthropologyLawdigital mediaSocial Science Computer Review
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Empirical model evaluation and hypothesis testing

2016

Chapter 5 deals with the empirical model evaluation and the testing of hypotheses. It starts out with the evaluation of the measurement and the structural models, using the PLS algorithm. After the evaluation of the complete model, moderating effects are examined by conducting group comparisons (section 5.4.1) and by investigating interaction effects (5.4.2). After that, selected constructs are further examined by exploratory data analysis (section 5.5).

Exploratory data analysisBrand relationshipSection (archaeology)EconometricsGroup comparisonStatistical hypothesis testingMathematicsBrand loyalty
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Basic Statistical Techniques

2012

Exploratory data analysisData collectionComputer scienceInterval estimationStatisticsData analysisStatistical inferenceSampling (statistics)Statistical and Managerial Techniques for Six Sigma Methodology
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Exploratory data analysis of environmental governance at local level in the south-west region of Poland

2018

Exploratory data analysisGeographyEnvironmental governanceRegional scienceGeneral MedicineBiblioteka Regionalisty
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Intra-urban spatial distributions of population and employment : the case of the agglomeration of Dijon, 1999

2003

The aim of this paper is to analyze the intra-urban spatial distributions of population and employment in the agglomeration of Dijon (regional capital of Burgundy, France). We study whether this agglomeration has followed the general tendency of job decentralization observed in most urban areas or whether it is still characterized by a monocentric pattern. In that purpose, we use a sample of 136 observations at the communal and at the IRIS (infra-urban statistical area) levels with 1999 census data and the employment database SIRENE (INSEE). First; we study the spatial pattern of total employment and employment density using exploratory spatial data analysis. Apart from the CBD, few IRIS ar…

Exploratory spatial data analysis[SHS.SOCIO]Humanities and Social Sciences/Sociology[SHS.SOCIO] Humanities and Social Sciences/Sociologyspatial heterogeneity[ SHS.SOCIO ] Humanities and Social Sciences/Sociologyemployment subcenterspopulation densitymonocentric and polycentric configurationsspatial autocorrelation
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Core of communities in bipartite networks

2017

We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Ran…

FOS: Computer and information sciencesAccuracy and precisionPhysics - Physics and SocietyBipartite systemRand indexFOS: Physical sciencesPhysics and Society (physics.soc-ph)computer.software_genre01 natural sciences010104 statistics & probabilityRobustness (computer science)0103 physical sciences01.02. Számítás- és információtudomány0101 mathematics010306 general physicsMathematicsSocial and Information Networks (cs.SI)Probability and statisticsComputer Science - Social and Information NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)network theory community detectionPhysics - Data Analysis Statistics and ProbabilityBipartite graphData miningcomputerData Analysis Statistics and Probability (physics.data-an)
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Selectivity in Probabilistic Causality: Drawing Arrows from Inputs to Stochastic Outputs

2011

Given a set of several inputs into a system (e.g., independent variables characterizing stimuli) and a set of several stochastically non-independent outputs (e.g., random variables describing different aspects of responses), how can one determine, for each of the outputs, which of the inputs it is influenced by? The problem has applications ranging from modeling pairwise comparisons to reconstructing mental processing architectures to conjoint testing. A necessary and sufficient condition for a given pattern of selective influences is provided by the Joint Distribution Criterion, according to which the problem of "what influences what" is equivalent to that of the existence of a joint distr…

FOS: Computer and information sciencesArtificial Intelligence (cs.AI)91E45 (Primary) 60A05 (Secondary)Computer Science - Artificial IntelligencePhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesProbability (math.PR)FOS: MathematicsFOS: Physical sciencesQuantitative Biology - Quantitative MethodsMathematics - ProbabilityData Analysis Statistics and Probability (physics.data-an)Quantitative Methods (q-bio.QM)
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Retrieval of Case 2 Water Quality Parameters with Machine Learning

2018

Water quality parameters are derived applying several machine learning regression methods on the Case2eXtreme dataset (C2X). The used data are based on Hydrolight in-water radiative transfer simulations at Sentinel-3 OLCI wavebands, and the application is done exclusively for absorbing waters with high concentrations of coloured dissolved organic matter (CDOM). The regression approaches are: regularized linear, random forest, Kernel ridge, Gaussian process and support vector regressors. The validation is made with and an independent simulation dataset. A comparison with the OLCI Neural Network Swarm (ONSS) is made as well. The best approached is applied to a sample scene and compared with t…

FOS: Computer and information sciencesComputer Science - Machine Learning010504 meteorology & atmospheric sciences0211 other engineering and technologiesFOS: Physical sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesData modelingMachine Learning (cs.LG)Physics - Geophysicssymbols.namesakeRadiative transferGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsArtificial neural networkbusiness.industry6. Clean waterRandom forestGeophysics (physics.geo-ph)Support vector machineColored dissolved organic matterKernel (statistics)Physics - Data Analysis Statistics and ProbabilitysymbolsArtificial intelligencebusinesscomputerData Analysis Statistics and Probability (physics.data-an)
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