Search results for " Error."

showing 10 items of 1034 documents

Familial Trichostrongylus Infection Misdiagnosed as Acute Fascioliasis

2015

To the Editor: Human fascioliasis, infection with Fasciola spp. flukes, is highly pathogenic in both acute and chronic phases and can result in death (1). This disease has been recently emerging, in part linked to climate and global changes (2). Human Fasciola infection has been reported in 5 continents and is related to the disease’s wide spread in livestock. Guilan Province in northern Iran is a fascioliasis-endemic area where the largest human epidemics have occurred, together affecting ≈15,000 persons (3). In 2014, 3 sisters (ages 35, 33, and 38) and their 41-year-old brother (patients 1–4, respectively) sought medical care at the same time, all with a 3-week history of symptoms. The pa…

Microbiology (medical)medicine.medical_specialtyAbdominal painFascioliasisLetterTrichostrongylusEpidemiologylcsh:MedicineparasitesIranGastroenterologyAsymptomaticlcsh:Infectious and parasitic diseasesInternal medicinemedicineEosinophiliaAnimalsHumanslcsh:RC109-216TrichostrongylusmisdiagnosisDiagnostic ErrorsLetters to the EditorEggs per gramFecesbiologybusiness.industrylcsh:RTrichostrongylosisbiology.organism_classificationSurgeryzoonosesDiarrheaInfectious Diseasesmedicine.symptombusinessFlatulenceFamilial Trichostrongylus Infection Misdiagnosed as Acute FascioliasisEmerging Infectious Diseases
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Explaining failures in innovative thought processes in engineering design

2012

Abstract The aim of this study is to explore factors causing failures in innovative thought processes in engineering design. An innovation process is here understood as a complex and multi-phased thinking and problem solving process generating new and mostly unforeseeable solutions. The phases are partly overlapping and simultaneous. This complicated nature of innovation process demands a lot from innovation management, and thus it is not unusual that innovation processes fail. Identifying problems and shortcomings is important because it helps organizations to eliminate them in the future. This study focus on thought processes of individual participants in an innovation process, which is r…

Microinnovation processesEngineeringKnowledge managementProcess (engineering)business.industryPerspective (graphical)engineering designthought failuresInnovation managementIdentifying problemsInnovation processthought errorsRisk analysis (engineering)General Materials ScienceEngineering design processbusinessProcedia - Social and Behavioral Sciences
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Joint LMMSE equalizer for HSDPA in full-rate space time transmit diversity schemes

2005

This contribution presents a joint linear minimum mean square error (LMMSE) equalizer for full-rate space-time transmit diversity multi-code schemes based on W-CDMA, featuring two and four transmit antennas. Specifically, high-rate, high load systems are targeted, in order to analyze the high speed downlink packet access (HSDPA) of 3GPP Release 6. We derive an equivalent transmission scheme to equalize the received sufficient statistic in a single stage. To reduce the effects of multipath and multiuser interference, and to provide spatial and frequency diversity at the receiver, an LMMSE equalizer is employed. Computer simulations confirm that the proposed schemes achieve robust performance…

Minimum mean square errorComputer scienceSettore ING-INF/03 - Telecomunicazionileast mean squares methodsComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSEqualizerAdaptive equalizerData_CODINGANDINFORMATIONTHEORYFull RateTransmit diversityTransmission (telecommunications)3G mobile communicationantenna arrayfading channelTelecommunications linkdiversity receptionComputer Science::Networking and Internet ArchitectureElectronic engineeringequaliserFadingMultipath propagationComputer Science::Information TheoryCommunication channelDiversity scheme
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Graph Topology Learning and Signal Recovery Via Bayesian Inference

2019

The estimation of a meaningful affinity graph has become a crucial task for representation of data, since the underlying structure is not readily available in many applications. In this paper, a topology inference framework, called Bayesian Topology Learning, is proposed to estimate the underlying graph topology from a given set of noisy measurements of signals. It is assumed that the graph signals are generated from Gaussian Markov Random Field processes. First, using a factor analysis model, the noisy measured data is represented in a latent space and its posterior probability density function is found. Thereafter, by utilizing the minimum mean square error estimator and the Expectation M…

Minimum mean square errorOptimization problemComputer scienceBayesian probabilityExpectation–maximization algorithmEstimatorGraph (abstract data type)Topological graph theoryBayesian inferenceAlgorithm2019 IEEE Data Science Workshop (DSW)
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Accommodation-related changes in monochromatic aberrations of the human eye as a function of age.

2008

PURPOSE. To investigate the relationship between accommodation and the optical aberrations of the whole human eye, as a function of age. METHODS. Sixty healthy subjects with spherical ametropia in the range 3 D, astigmatism less than 1 D, corrected visual acuity of 20/18 or better, and normal findings in an ophthalmic examination were enrolled. Subjects were divided into four groups, with age ranges of 19 to 29, 30 to 39, 40 to 49, and 50 to 60 years. Monochromatic optical aberrations and pupil size were measured with a Hartmann-Shack wavefront sensor under monocular viewing conditions, without pharmacological dilation or cycloplegia. Stimulus vergences were in the range of 0 to 5 D, with a…

MiosisAdultMaleAgingVisual acuitygenetic structuresPupilRetinaContrast SensitivityMedicineHumansMonocularbusiness.industryAccommodation OcularCycloplegiaPupilMiddle AgedRefractive Errorseye diseasesSpherical aberrationmedicine.anatomical_structureOptometryHuman eyeFemalesense organsmedicine.symptombusinessAccommodationInvestigative ophthalmologyvisual science
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State Estimation of a Mobile Manipulator via Non-uniformly Sampled Position Measurements

2011

Abstract We derive an exact deterministic nonlinear estimator to compute the continuous state of a nonlinear time-varying system based on discrete, non uniformly time spaced, state measurements. The system consists of a robot arm mounted on a mobile non holonomic vehicle. The paper also discusses the effect on the estimation error of a bounded input additive noise.

Mobile manipulatorHolonomicContinuous stateBounded inputState (functional analysis)Noise (electronics)Nonholonomic vehicleComputer Science::RoboticsNonlinear systemNonlinear estimatorSettore ING-INF/04 - AutomaticaControl theoryPosition (vector)Estimation errorBounded functionState measurementsNonlinear time varying systemRobotic armRobot armMobile manipulatorMathematics
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On the Provisioning of Mobile Digital Terrestrial TV Services to Vehicles With DVB-T

2012

[EN] Most of the DVB-T (Digital Video Broadcasting -Terrestrial) networks deployments worldwide have been designed for fixed rooftop antennas and high transmission capacity, not providing good coverage level for vehicular mobile reception. This letter analyzes how to combine different technical solutions, so far studied individually, in order to increase the robustness of the transmission for vehicular reception to provide in-band mobile services. In particular, we consider: receive antenna diversity, hierarchical modulation, and Application Layer Forward Error Correction (AL-FEC). Performance evaluation results have been obtained by means of simulations, laboratory tests, and field measure…

Mobile radiobusiness.industryComputer scienceIMT AdvancedComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSMobile televisionData_CODINGANDINFORMATIONTHEORYAntenna diversityMobile DVB-TTerrestrial televisionHierarchical modulationMobile stationTEORIA DE LA SEÑAL Y COMUNICACIONESDigital Video BroadcastingMedia TechnologyDVB-TApplication layer forward error correctionElectrical and Electronic EngineeringbusinessAntenna diversityComputer networkIEEE Transactions on Broadcasting
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MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech

2022

Abstract Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep Recurrent Neural Network-based framework is presented to detect depression and to predict its severity level from speech. Low-level and high-level audio features are extracted from audio recordings to predict the 24 scores of the Patient Health Questionnaire and the binary class of depression diagnosis. To overcome the problem of the small size of Speech Depression Recognition (SDR) datasets, expanding training labels and transferred features are considered. The proposed approach outperforms the state-of-art approaches on the DAIC-WOZ database with an overall accura…

Modality (human–computer interaction)Mean squared errorComputer scienceSpeech recognitionBiomedical EngineeringHealth Informaticsmedicine.diseaseClass (biology)Patient Health QuestionnaireComputingMethodologies_PATTERNRECOGNITIONRecurrent neural networkSignal ProcessingmedicineMajor depressive disorderMel-frequency cepstrumDepression (differential diagnoses)Biomedical Signal Processing and Control
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Conformational response to ligand binding in phosphomannomutase2: insights into inborn glycosylation disorder.

2014

Background: Mutations in phosphomannomutase2 cause glycosylation disorder, a disease without a cure that will largely benefit from accurate ligand-bound models. Results: We obtained two models of phospomannomutase2 bound to glucose 1,6-bisphosphate and validated them with limited proteolysis. Conclusion: Ligand binding induces a large conformational transition in PMM2. Significance: We produce and validate closed-form models of PMM2 that represent a starting point for rational drug discovery.

Models MolecularPELEGlycosylationProtein Conformation1Molecular Sequence DataGlucose-6-PhosphateGlycosylation Inhibitor6-bisphosphate; PELE; computer modeling; drug discovery; glycosylation; glycosylation inhibitor; ligand-binding protein; phosphomannomutaseLigandsDrug DiscoveryAnimalsHumansAmino Acid Sequence16-BisphosphateProtein UnfoldingTemperatureLigand-binding Proteinphosphomannomutase 2 and mass spectrometryPhosphotransferases (Phosphomutases)PhosphomannomutaseMutationProteolysisMetabolism Inborn ErrorsMolecular BiophysicsPeptide HydrolasesProtein BindingComputer ModelingThe Journal of biological chemistry
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Correlation of Pharmacological Properties of a Group of Hypolipaemic Drugs by Molecular Topology

1996

Abstract This investigation was undertaken to test the ability of the molecular connectivity model to predict the percentage of plasma protein binding, the percentage of total cholesterol reduction and oral LD50 in rats of a group of hypolipaemic drugs using multi-variable regression equations with multiple correlation coefficients, standard error of estimate, degrees of freedom, F-Snedecor function values, Mallow's CP and Student's t-test as criteria of fit. Regression analyses showed that the molecular connectivity model predicts these properties. Corresponding stability (cross validation) studies were made on the selected prediction models which confirmed their goodness of fit. The resul…

Molecular modelStereochemistryDegrees of freedom (statistics)Pharmaceutical ScienceModels BiologicalCross-validationLethal Dose 50CorrelationStructure-Activity RelationshipFenofibrateGoodness of fitAnimalsMultiple correlationFuransHypolipidemic AgentsPharmacologyChemistryBlood ProteinsRegressionRatsCholesterolProbucolStandard errorRegression AnalysisBiological systemProtein BindingJournal of Pharmacy and Pharmacology
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