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Connectivity analysis with structural equation modelling: an example of the effects of voxel selection
Structural equation modelling (SEM) of neuroimaging data is commonly applied to a network of distributed brain regions. We applied SEM to an fMRI dataset to identify condition-specific effects in a simple experiment composed of visual stimulation and baseline conditions. The visual network was composed of three well-defined anatomical regions (V1, V2, and V5) and three path connections (V1 â V2, V1 â V5, and V2 â V5). This network was used to test four hypotheses: (1) whether the condition-specific effects for all three connections vary according to the data selected for modelling; (2) whether the âsummaryâ measures that are often used are indeed appropriate; (3) whether measures taken from the voxel timecourse can reliably predict the condition-specific effects for each one of the three path connections, and (4) whether all voxels within an anatomical region yield equivalent SEM outcomes. There was some variability in the significance of the condition-specific effects across randomly selected voxels within regions. However, the SEM outcome from the âsummaryâ measures was comparable to the most frequent pattern of condition-specific effects. Magnitude, delay, spread, and goodness-of-fit measures taken from a gamma fit to the voxel time courses predicted reliably the significance of the SEM condition-specific effects for each connection. This result enabled us to identify spatially coherent regions at the boundaries of V2 that displayed different condition-specific effects from those seen in the majority of the voxels. Although the generality of these results awaits further investigation, this example highlights a number of important issues for SEM
Development Of A High Performance Mosaicing And Super-Resolution Algorithm
In this dissertation, a high-performance mosaicing and super-resolution algorithm is described. The scale invariant feature transform (SIFT)-based mosaicing algorithm builds an initial mosaic which is iteratively updated by the robust super resolution algorithm to achieve the final high-resolution mosaic. Two different types of datasets are used for testing: high altitude balloon data and unmanned aerial vehicle data. To evaluate our algorithm, five performance metrics are employed: mean square error, peak signal to noise ratio, singular value decomposition, slope of reciprocal singular value curve, and cumulative probability of blur detection. Extensive testing shows that the proposed algorithm is effective in improving the captured aerial data and the performance metrics are accurate in quantifying the evaluation of the algorithm
Quantitative non-destructive testing
The work undertaken during this period included two primary efforts. The first is a continuation of theoretical development from the previous year of models and data analyses for NDE using the Optical Thermal Infra-Red Measurement System (OPTITHIRMS) system, which involves heat injection with a laser and observation of the resulting thermal pattern with an infrared imaging system. The second is an investigation into the use of the thermoelastic effect as an effective tool for NDE. As in the past, the effort is aimed towards NDE techniques applicable to composite materials in structural applications. The theoretical development described produced several models of temperature patterns over several geometries and material types. Agreement between model data and temperature observations was obtained. A model study with one of these models investigated some fundamental difficulties with the proposed method (the primitive equation method) for obtaining diffusivity values in plates of thickness and supplied guidelines for avoiding these difficulties. A wide range of computing speeds was found among the various models, with a one-dimensional model based on Laplace's integral solution being both very fast and very accurate
Blur Classification Using Segmentation Based Fractal Texture Analysis
The objective of vision based gesture recognition is to design a system, which can understand the human actions and convey the acquired information with the help of captured images. An image restoration approach is extremely required whenever image gets blur during acquisition process since blurred images can severely degrade the performance of such systems. Image restoration recovers a true image from a degraded version. It is referred as blind restoration if blur information is unidentified. Blur identification is essential before application of any blind restoration algorithm. This paper presents a blur identification approach which categories a hand gesture image into one of the sharp, motion, defocus and combined blurred categories. Segmentation based fractal texture analysis extraction algorithm is utilized for featuring the neural network based classification system. The simulation results demonstrate the preciseness of proposed method
Clarity of View: An Analytic Hierarchy Process (AHP)-Based Multi-Factor Evaluation Framework for Driver Awareness Systems in Heavy Vehicles
Several emerging technologies hold great promise to improve the situational awareness of the heavy vehicle driver. However, current industry-standard evaluation methods do not measure all the comprehensive factors contributing to the overall effectiveness of such systems. The average commercial vehicle driver in the USA is 54 years old with many drivers continuing past retirement age. Current methods for evaluating visibility systems only consider field of view and do not incorporate measures of the cognitive elements critical to drivers, especially the older demographic. As a result, industry is challenged to evaluate new technologies in a way that provides enough information to make informed selection and purchase decisions. To address this problem, we introduce a new multi-factor evaluation framework, âClarity of View,â that incorporates several important factors for visibility systems including: field of view, image detection time, distortion, glare discomfort, cost, reliability, and gap acceptance accuracy. It employs a unique application of the Analytic Hierarchy Process (AHP) that involves both expert participants acting in a Supra-Decision Maker role alongside driver-level participants giving both actual performance data as well as subjective preference feedback. Both subjective and objective measures have been incorporated into this multi-factor decision-making model that will help industry make better technology selections involving complex variables. A series of experiments have been performed to illustrate the usefulness of this framework that can be expanded to many types of automotive user-interface technology selection challenges. A unique commercial-vehicle driving simulator apparatus was developed that provides a dynamic, 360-degree, naturalistic driving environment for the evaluation of rearview visibility systems. Evaluations were performed both in the simulator and on the track. Test participants included trucking industry leadership and commercially licensed drivers with experience ranging from 1 to 40 years. Conclusions indicated that aspheric style mirrors have significant viability in the commercial vehicle market. Prior research on aspheric mirrors left questions regarding potential user adaptation, and the Clarity of View framework provides the necessary tools to reconcile that gap. Results obtained using the new Clarity of View framework were significantly different than that which would have previously been available using current industry status-quo published test methods. Additional conclusions indicated that middle-aged drivers performed better in terms of image detection time than young and elderly age categories. Experienced drivers performed better than inexperienced drivers, regardless of age. This is an important conclusion given the demographic challenges faced by the commercial vehicle industry today that is suffering a shortage of new drivers and may be seeking ways to retain its aging driver workforce. The Clarity of View evaluation framework aggregates multiple factors critical to driver visibility system effectiveness into a single selection framework that is useful for industry. It is unique both in its multi-factor approach and custom-developed apparatus, but also in its novel approach to the application of the AHP methodology. It has shown significance in ability to discern more well-informed technology selections and is flexible to expand its application toward many different types of driver interface evaluations
Clustering Inverse Beamforming and multi-domain acoustic imaging approaches for vehicles NVH
Il rumore percepito allâinterno della cabina di un veicolo Ăš un aspetto molto rilevante nella valutazione della sua qualitĂ complessiva. Metodi sperimentali di acoustic imaging, quali beamforming e olografia acustica, sono usati per identificare le principali sorgenti che contribuiscono alla rumorositĂ percepita allâinterno del veicolo. Lâobiettivo della tesi proposta Ăš di fornire strumenti per effettuare dettagliate analisi quantitative tramite tali tecniche, ad oggi relegate alle fasi di studio preliminare, proponendo un approccio modulare che si avvale di analisi dei fenomeni vibro-acustici nel dominio della frequenza, del tempo e dellâangolo di rotazione degli elementi rotanti tipicamente presenti in un veicolo. CiĂČ permette di ridurre tempi e costi della progettazione, garantendo, al contempo, una maggiore qualitĂ del pacchetto vibro-acustico. Lâinnovativo paradigma proposto prevede lâuso combinato di algoritmi di pre- e post- processing con tecniche inverse di acoustic imaging per lo studio di rilevanti problematiche quali lâidentificazione di sorgenti sonore esterne o interne allâabitacolo e del rumore prodotto da dispositivi rotanti. Principale elemento innovativo della tesi Ăš la tecnica denominata Clustering Inverse Beamforming. Essa si basa su un approccio statistico che permette di incrementare lâaccuratezza (range dinamico, localizzazione e quantificazione) di una immagine acustica tramite la combinazione di soluzioni, del medesimo problema inverso, ottenute considerando diversi sotto-campioni dellâinformazione sperimentale disponibile, variando, in questo modo, in maniera casuale la sua formulazione matematica. Tale procedimento garantisce la ricostruzione nel dominio della frequenza e del tempo delle sorgenti sonore identificate. Un metodo innovativo Ăš stato inoltre proposto per la ricostruzione, ove necessario, di sorgenti sonore nel dominio dellâangolo. I metodi proposti sono stati supportati da argomentazioni teoriche e validazioni sperimentali su scala accademica e industriale.The interior sound perceived in vehicle cabins is a very important attribute for the user. Experimental acoustic imaging methods such as beamforming and Near-field Acoustic Holography are used in vehicles noise and vibration studies because they are capable of identifying the noise sources contributing to the overall noise perceived inside the cabin. However these techniques are often relegated to the troubleshooting phase, thus requiring additional experiments for more detailed NVH analyses. It is therefore desirable that such methods evolve towards more refined solutions capable of providing a larger and more detailed information. This thesis proposes a modular and multi-domain approach involving direct and inverse acoustic imaging techniques for providing quantitative and accurate results in frequency, time and angle domain, thus targeting three relevant types of problems in vehicles NVH: identification of exterior sources affecting interior noise, interior noise source identification, analysis of noise sources produced by rotating machines. The core finding of this thesis is represented by a novel inverse acoustic imaging method named Clustering Inverse Beamforming (CIB). The method grounds on a statistical processing based on an Equivalent Source Method formulation. In this way, an accurate localization, a reliable ranking of the identified sources in frequency domain and their separation into uncorrelated phenomena is obtained. CIB is also exploited in this work for allowing the reconstruction of the time evolution of the sources sought. Finally a methodology for decomposing the acoustic image of the sound field generated by a rotating machine as a function of the angular evolution of the machine shaft is proposed. This set of findings aims at contributing to the advent of a new paradigm of acoustic imaging applications in vehicles NVH, supporting all the stages of the vehicle design with time-saving and cost-efficient experimental techniques. The proposed innovative approaches are validated on several simulated and real experiments
The Canadian Cluster Comparison Project: detailed study of systematics and updated weak lensing masses
Masses of clusters of galaxies from weak gravitational lensing analyses of
ever larger samples are increasingly used as the reference to which baryonic
scaling relations are compared. In this paper we revisit the analysis of a
sample of 50 clusters studied as part of the Canadian Cluster Comparison
Project. We examine the key sources of systematic error in cluster masses. We
quantify the robustness of our shape measurements and calibrate our algorithm
empirically using extensive image simulations. The source redshift distribution
is revised using the latest state-of-the-art photometric redshift catalogs that
include new deep near-infrared observations. Nonetheless we find that the
uncertainty in the determination of photometric redshifts is the largest source
of systematic error for our mass estimates. We use our updated masses to
determine b, the bias in the hydrostatic mass, for the clusters detected by
Planck. Our results suggest 1-b=0.76+-0.05(stat)}+-0.06(syst)}, which does not
resolve the tension with the measurements from the primary cosmic microwave
background.Comment: resubmitted to MNRAS after review by refere
Enhancing the information content of geophysical data for nuclear site characterisation
Our knowledge and understanding to the heterogeneous structure and processes occurring in the Earthâs subsurface is limited and uncertain. The above is true even for the upper 100m of the subsurface, yet many processes occur within it (e.g. migration of solutes, landslides, crop water uptake, etc.) are important to human activities. Geophysical methods such as electrical resistivity tomography (ERT) greatly improve our ability to observe the subsurface due to their higher sampling frequency (especially with autonomous time-lapse systems), larger spatial coverage and less invasive operation, in addition to being more cost-effective than traditional point-based sampling. However, the process of using geophysical data for inference is prone to uncertainty. There is a need to better understand the uncertainties embedded in geophysical data and how they translate themselves when they are subsequently used, for example, for hydrological or site management interpretations and decisions. This understanding is critical to maximize the extraction of information in geophysical data. To this end, in this thesis, I examine various aspects of uncertainty in ERT and develop new methods to better use geophysical data quantitatively. The core of the thesis is based on two literature reviews and three papers. In the first review, I provide a comprehensive overview of the use of geophysical data for nuclear site characterization, especially in the context of site clean-up and leak detection. In the second review, I survey the various sources of uncertainties in ERT studies and the existing work to better quantify or reduce them. I propose that the various steps in the general workflow of an ERT study can be viewed as a pipeline for information and uncertainty propagation and suggested some areas have been understudied. One of these areas is measurement errors. In paper 1, I compare various methods to estimate and model ERT measurement errors using two long-term ERT monitoring datasets. I also develop a new error model that considers the fact that each electrode is used to make multiple measurements. In paper 2, I discuss the development and implementation of a new method for geoelectrical leak detection. While existing methods rely on obtaining resistivity images through inversion of ERT data first, the approach described here estimates leak parameters directly from raw ERT data. This is achieved by constructing hydrological models from prior site information and couple it with an ERT forward model, and then update the leak (and other hydrological) parameters through data assimilation. The approach shows promising results and is applied to data from a controlled injection experiment in Yorkshire, UK. The approach complements ERT imaging and provides a new way to utilize ERT data to inform site characterisation. In addition to leak detection, ERT is also commonly used for monitoring soil moisture in the vadose zone, and increasingly so in a quantitative manner. Though both the petrophysical relationships (i.e., choices of appropriate model and parameterization) and the derived moisture content are known to be subject to uncertainty, they are commonly treated as exact and errorâfree. In paper 3, I examine the impact of uncertain petrophysical relationships on the moisture content estimates derived from electrical geophysics. Data from a collection of core samples show that the variability in such relationships can be large, and they in turn can lead to high uncertainty in moisture content estimates, and they appear to be the dominating source of uncertainty in many cases. In the closing chapters, I discuss and synthesize the findings in the thesis within the larger context of enhancing the information content of geophysical data, and provide an outlook on further research in this topic
Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems
Nach einer Einleitung behandelt Teil 2 Mehrbenutzer-Scheduling fĂŒr die
AbwÀrtsstrecke von drahtlosen MIMO Systemen mit einer Sendestation und
kanaladaptivem precoding: In jeder Zeit- oder Frequenzressource kann eine
andere Nutzergruppe gleichzeitig bedient werden, rÀumlich getrennt durch
unterschiedliche Antennengewichte. Nutzer mit korrelierten KanÀlen sollten
nicht gleichzeitig bedient werden, da dies die rÀumliche Trennbarkeit
erschwert. Die Summenrate einer Nutzermenge hÀngt von den Antennengewichten
ab, die wiederum von der Nutzerauswahl abhÀngen. Zur Entkopplung des
Problems schlÀgt diese Arbeit Metriken vor basierend auf einer geschÀtzten
Rate mit ZF precoding. Diese lÀsst sich mit Hilfe von wiederholten
orthogonalen Projektionen abschÀtzen, wodurch die Berechnung von
Antennengewichten beim Scheduling entfÀllt. Die RatenschÀtzung kann
basierend auf momentanen Kanalmessungen oder auf gemittelter Kanalkenntnis
berechnet werden und es können Datenraten- und Fairness-Kriterien
berĂŒcksichtig werden. Effiziente Suchalgorithmen werden vorgestellt, die
die gesamte Systembandbreite auf einmal bearbeiten können und zur
KomplexitĂ€tsreduktion die Lösung in Zeit- und Frequenz nachfĂŒhren können.
Teil 3 zeigt wie mehrere Sendestationen koordiniertes Scheduling und
kooperative Signalverarbeitung einsetzen können. Mittels orthogonalen
Projektionen ist es möglich, Inter-Site Interferenz zu schÀtzen, ohne
Antennengewichte berechnen zu mĂŒssen. Durch ein Konzept virtueller Nutzer
kann der obige Scheduling-Ansatz auf mehrere Sendestationen und sogar
Relays mit SDMA erweitert werden. Auf den benötigten Signalisierungsaufwand
wird kurz eingegangen und eine Methode zur SchÀtzung der Summenrate eines
Systems ohne Koordination besprochen. Teil4 entwickelt Optimierungen fĂŒr
Turbo Entzerrer. Diese Nutzen Signalkorrelation als Quelle von Redundanz.
Trotzdem kann eine Kombination mit MIMO precoding sinnvoll sein, da bei
Annahme realistischer Fehler in der Kanalkenntnis am Sender keine optimale
InterferenzunterdrĂŒckung möglich ist. Mit Hilfe von EXIT Charts wird eine
neuartige Methode zur adaptiven Nutzung von a-priori-Information zwischen
Iterationen entwickelt, die die Konvergenz verbessert. Dabei wird gezeigt,
wie man semi-blinde KanalschĂ€tzung im EXIT chart berĂŒcksichtigen kann.
In Computersimulationen werden alle Verfahren basierend auf
4G-Systemparametern ĂŒberprĂŒft.After an introduction, part 2 of this thesis deals with downlink multi-user
scheduling for wireless MIMO systems with one transmitting station
performing channel adaptive precoding:Different user subsets can be served
in each time or frequency resource by separating them in space with
different antenna weight vectors. Users with correlated channel matrices
should not be served jointly since correlation impairs the spatial
separability.The resulting sum rate for each user subset depends on the
precoding weights, which in turn depend on the user subset. This thesis
manages to decouple this problem by proposing a scheduling metric based on
the rate with ZF precoding such as BD, written with the help of orthogonal
projection matrices. It allows estimating rates without computing any
antenna weights by using a repeated projection approximation.This rate
estimate allows considering user rate requirements and fairness criteria
and can work with either instantaneous or long term averaged channel
knowledge.Search algorithms are presented to efficiently solve user
grouping or selection problems jointly for the entire system bandwidth
while being able to track the solution in time and frequency for complexity
reduction.
Part 3 shows how multiple transmitting stations can benefit from
cooperative scheduling or joint signal processing. An orthogonal projection
based estimate of the inter-site interference power, again without
computing any antenna weights, and a virtual user concept extends the
scheduling approach to cooperative base stations and finally included SDMA
half-duplex relays in the scheduling.Signalling overhead is discussed and a
method to estimate the sum rate without coordination.
Part 4 presents optimizations for Turbo Equalizers. There, correlation
between user signals can be exploited as a source of redundancy.
Nevertheless a combination with transmit precoding which aims at reducing
correlation can be beneficial when the channel knowledge at the transmitter
contains a realistic error, leading to increased correlation. A novel
method for adaptive re-use of a-priori information between is developed to
increase convergence by tracking the iterations online with EXIT charts.A
method is proposed to model semi-blind channel estimation updates in an
EXIT chart.
Computer simulations with 4G system parameters illustrate the methods using realistic channel models.Im Buchhandel erhÀltlich:
Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems / Fuchs-Lautensack,Martin
Ilmenau: ISLE, 2009,116 S.
ISBN 978-3-938843-43-
Sensitivity analysis in a scoping review on police accountability : assessing the feasibility of reporting criteria in mixed studies reviews
In this paper, we report on the findings of a sensitivity analysis that was carried out within a previously conducted scoping review, hoping to contribute to the ongoing debate about how to assess the quality of research in mixed methods reviews. Previous sensitivity analyses mainly concluded that the exclusion of inadequately reported or lower quality studies did not have a significant effect on the results of the synthesis. In this study, we conducted a sensitivity analysis on the basis of reporting criteria with the aims of analysing its impact on the synthesis results and assessing its feasibility. Contrary to some previous studies, our analysis showed that the exclusion of inadequately reported studies had an impact on the results of the thematic synthesis. Initially, we also sought to propose a refinement of reporting criteria based on the literature and our own experiences. In this way, we aimed to facilitate the assessment of reporting criteria and enhance its consistency. However, based on the results of our sensitivity analysis, we opted not to make such a refinement since many publications included in this analysis did not sufficiently report on the methodology. As such, a refinement would not be useful considering that researchers would be unable to assess these (sub-)criteria
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