Search results for "Detection"

showing 10 items of 2543 documents

Instrumentation for time-of-flight elastic recoil detection analysis

2016

Time-of-flight elastic recoil detection is an ion beam based method to analyze the elemental composition of thin film samples at different depths. In order to improve the mass resolution and to enable kinematic correction a position sensitive gas ionization chamber energy detector was constructed. This detector along with pre-existing timing detectors were connected to a modern fully digitizing data acquisition setup. This thesis describes the design of these instruments, including all aspects from the mechanical design of the gas ionization detector to the algorithm and software development of the digitizing acquisition setup. The performance of the system has been studied with measurements …

digital pulse processingmateriaalitutkimusanalyysilaitteetelastic recoil detection analysisanalyysimenetelmätsirontaohutkalvottime-of-flightgas ionization chamberdigitizerdigitaalitekniikka
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Human Activity Signatures Captured under Different Directions Using SISO and MIMO Radar Systems

2022

In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2×2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Anc…

direction-independent human activity recognition; fall detection; distributed MIMO; FMCW radar; micro-Doppler signatures; aspect angle; multistatic radar systems; passive step counter; DTW; velocity estimationFluid Flow and Transfer ProcessesProcess Chemistry and TechnologyGeneral EngineeringVDP::Medisinske Fag: 700General Materials ScienceVDP::Matematikk og Naturvitenskap: 400InstrumentationComputer Science::Information TheoryComputer Science ApplicationsApplied Sciences
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Quantitative Rotor Broken Bar Evaluation in Double Squirrel Cage Induction Machines under Dynamic Operating Conditions

2013

Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the …

discrete wavelet transformEngineeringbusiness.industryRotor (electric)Squirrel-cage rotorBar (music)squirrel cage motorSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciFault (power engineering)FAULT DIAGNOSISFault detection and isolationPower (physics)law.inventionVibrationTime-Frequency AnalysisControl theorylawAC Machine Condition monitoring Double cage rotor fault diagnostics induction motor wavelet TransformbusinessInduction motor
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Anomaly-based online intrusion detection system as a sensor for cyber security situational awareness system

2016

Almost all the organisations and even individuals rely on complex structures of data networks and networked computer systems. That complex data ensemble, the cyber domain, provides great opportunities, but at the same time it offers many possible attack vectors that can be abused for cyber vandalism, cyber crime, cyber espionage or cyber terrorism. Those threats produce requirements for cyber security situational awareness and intrusion detection capability. This dissertation concentrates on research and development of anomaly-based network intrusion detection system as a sensor for a situational awareness system. In this dissertation, several models of intrusion detection systems are devel…

early warningpääsynvalvontatunkeilijan havaitsemisjärjestelmätcyber securityvalvontajärjestelmättilannekuvaanomaly detectionsituational awarenessinformation sharingnetwork securityintrusion detection systemklusterianalyysitiedonlouhintakyberturvallisuustietoverkotclustering
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Regularization Preserving Localization of Close Edges

2007

International audience; In this letter, we address the problem of the influence of neighbor edges and their effect on the edge delocalization while extracting a neighbor contour by a derivative approach. The properties to be fulfilled by the regularization operators to minimize or suppress this side effect are deduced, and the best detectors are pointed out. The study is carried out in 1-D for discrete signal. We show that among the derivative filters, one of them can correctly detect our model edges without being influenced by a neighboring transition, whatever their separation distance is and their respective amplitude is. A model of contour and close transitions is presented and used through…

edge localization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingneighbor edge[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyEdge detectionDiscrete-time signal[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringRegularization operatorCanny edge detectorEdge detectionElectrical and Electronic EngineeringMathematicsedge modelbusiness.industryApplied MathematicsDetector020207 software engineeringPattern recognitionregularization filterDeriche edge detectorAmplitude[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Regularization (physics)Signal Processing020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmIEEE Signal Processing Letters
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Scratch detection and removal from static images using simple statistics and genetic algorithms

2002

This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conven…

education.field_of_studySettore INF/01 - InformaticaComputer sciencePopulationImage processingLinear interpolationObject detectionHardware and ArchitectureScratchStatisticsLine (geometry)Genetic algorithmElectrical and Electronic Engineeringeducationcomputer1707Interpolationcomputer.programming_language
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A Method Based on Multi-source Feature Detection for Counting People in Crowded Areas

2019

We propose a crowd counting method for multisource feature fusion. Image features are extracted from multiple sources, and the population is estimated by image feature extraction and texture feature analysis, along with for crowd image edge detection. We count people in high-density still images. For instance, in the city’s squares, sports fields, subway stations, etc. Our approach uses a still image taken by a camera on a drone to appraise the count in the population density image, using a kind of sources of information: HOG, LBP, CANNY. We furnish separate estimates of counts and other statistical measurements through several types of sources. Support vector machine SVM, classification an…

education.field_of_studyWarning systembusiness.industryFeature extractionPopulationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRegression analysisPattern recognitionImage (mathematics)Support vector machineArtificial intelligencebusinesseducationMulti-sourceFeature detection (computer vision)2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP)
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Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data

2014

Incorporating prior knowledge (e.g., the spatial distribution of zip codes and background population effects) into a model using Bayesian methods could potentially improve outbreak detection. We adapted a previously described Bayesian model-based spatiotemporal surveillance technique to daily respiratory syndrome counts in NYC Emergency Department data in 2009, the year of the H1N1 influenza pandemic. Citywide, 56 alarms were produced across 15 zip codes, all during days of elevated respiratory visits. Future work includes evaluating our choice of baseline length, considering other alarm thresholds, and conducting a formal evaluation of the method across five syndromes in NYC.

education.field_of_studybusiness.industryBayesian probabilityH1N1 influenzaPopulationEmergency departmentISDS 2013 Conference Abstractscomputer.software_genreBayesian inferenceZip codeFormal evaluationspatiotemporal dataPandemicoutbreak detectionGeneral Earth and Planetary SciencesMedicinesyndromic surveillanceData miningbusinesseducationcomputerCartographyBayesian modelsGeneral Environmental ScienceOnline Journal of Public Health Informatics
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Anomaly Detection in Dynamic Social Systems Using Weak Estimators

2009

Anomaly detection involves identifying observationsthat deviate from the normal behavior of a system. One ofthe ways to achieve this is by identifying the phenomena thatcharacterize “normal” observations. Subsequently, based on thecharacteristics of data learned from the “normal” observations,new observations are classified as being either “normal” or not.Most state-of-the-art approaches, especially those which belongto the family parameterized statistical schemes, work under theassumption that the underlying distributions of the observationsare stationary. That is, they assume that the distributions thatare learned during the training (or learning) phase, thoughunknown, are not time-varyin…

education.field_of_studybusiness.industryComputer sciencePopulationEstimatorMachine learningcomputer.software_genreOutlierAnomaly detectionArtificial intelligenceData miningAnomaly (physics)businesseducationcomputer2009 International Conference on Computational Science and Engineering
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Detection ofEPOgene doping in blood

2012

Gene doping--or the abuse of gene therapy--will continue to threaten the sports world. History has shown that progress in medical research is likely to be abused in order to enhance human performance. In this review, we critically discuss the progress and the risks associated with the field of erythropoietin (EPO) gene therapy and its applicability to EPO gene doping. We present typical vector systems that are employed in ex vivo and in vivo gene therapy trials. Due to associated risks, gene doping is not a feasible alternative to conventional EPO or blood doping at this time. Nevertheless, it is well described that about half of the elite athlete population is in principle willing to risk …

education.field_of_studybusiness.industryTransgeneGenetic enhancementPopulationPharmaceutical SciencePharmacologyBioinformaticsAnalytical ChemistryBlood dopingSubstance Abuse DetectionGene dopingErythropoietinEnvironmental ChemistryMedicineeducationbusinessGeneSpectroscopymedicine.drugDrug Testing and Analysis
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