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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
241

Cloud adoption : a goal-oriented requirements engineering approach

Zardari, Shehnila January 2016 (has links)
The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers’ ability to meet service level agreements. These risks hinder the adoption of cloud computing. We motivate the need for a new requirements engineering methodology for systematically helping businesses and users to adopt cloud services and for mitigating risks in such transition. The methodology is grounded in goal-oriented approaches for requirements engineering. We argue that Goal-Oriented Requirements Engineering (GORE) is a promising paradigm to adopt for goals that are generic and flexible statements of users’ requirements, which could be refined, elaborated, negotiated, mitigated for risks and analysed for economics considerations. The methodology can be used by small to large scale organisations to inform crucial decisions related to cloud adoption. We propose a risk management framework based on the principle of GORE. In this approach, we liken risks to obstacles encountered while realising cloud user goals, therefore proposing cloud-specific obstacle resolution tactics for mitigating identified risks. The proposed framework shows benefits by providing a principled engineering approach to cloud adoption and empowering stakeholders with tactics for resolving risks when adopting the cloud. We extend the work on GORE and obstacles for informing the adoption process. We argue that obstacles’ prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis.
242

3D facial expression classification using a statistical model of surface normals and a modular approach

Ujir, Hamimah January 2013 (has links)
Following the success in 3D face recognition, the face processing community is now trying to establish good 3D facial expression recognition. Facial expressions provide the cues of communication in which we can interpret the mood, meaning and emotions at the same time. With current advanced 3D scanners technology, direct anthropometric measurements (i.e. the comparative study of sizes and proportions of the human body) are easily obtainable and it offers 3D geometrical data suitable for 3D face processing studies. Instead of using the raw 3D facial points, we extracted its derivative which gives us 3D facial surface normals. We constructed a statistical model for variations in facial shape due to changes in six basic expressions using 3D facial surface normals as the feature vectors. In particular, we are interested in how such facial expression variations manifest themselves in terms of changes in the field of 3D facial surface normals. We employed a modular approach where a module contains the facial features of a distinct facial region. The decomposition of a face into several modules promotes the learning of a facial local structure and therefore the most discriminative variation of the facial features in each module is emphasized. We decomposed a face into six modules and the expression classification for each module is carried out independently. We constructed a Weighted Voting Scheme (WVS) to infer the emotion underlying a collection of modules using a weight that is determined using the AdaBoost learning algorithm. Using our approach, using 3D facial surface normal as the feature vector of WVS yields a better performance than 3D facial points and 3D distance measurements in facial expression classification using both WVS and Majority Voting Scheme (MVS). The attained results suggest surface normals do indeed produce a comparable result particularly for six basic facial expressions with no intensity information.
243

Dynamic data-driven framework for reputation management

Onolaja, Olufunmilola Oladunni January 2012 (has links)
The landscape of security has been changed by the increase in online market places, and the rapid growth of mobile and wireless networks. Users are now exposed to greater risks as they interact anonymously in these domains. Despite the existing security paradigms, trust among users remains a problem. Reputation systems have now gained popularity because of their effectiveness in providing trusted interactions. We argue that managing reputation by relying on history alone and/or biased opinions is inadequate for security, because such an approach exposes the domain to vulnerabilities. Alternatively, the use of historical, recent and anticipated events supports effective reputation management. We investigate how the dynamic data-driven application systems paradigm can aid reputation management. We suggest the use of the paradigm's primitives, which includes the use of controller and simulation components for performing computations and predictions. We demonstrate how a dynamic framework can provide effective reputation management that is not influenced by biased observations. This is an online decision support system that can enable stakeholders make informed judgments. To highlight the framework's usefulness, we report on its predictive performance through an evaluation stage. Our results indicate that a dynamic data-driven approach can lead to effective reputation management in trust-reliant domains.
244

Sensor-enhanced imaging

Assam, Aieat January 2013 (has links)
Most approaches to spatial image management involve GPS or image processing. In this thesis, a sensor-focused alternative is explored. It requires user and camera tracking, particularly challenging in indoor environments. Possible indoor tracking methods are evaluated and pedestrian dead reckoning is selected. A study is conducted to evaluate sensors and choose a combination for pedestrian and camera tracking. Gyroscope and accelerometer offer comparable step detection performance, with gyroscope and tilt compensated compass providing heading data. Images taken from the same viewpoint are successfully arranged using panorama stitching without any image processing. The results compare favourably to conventional methods. While lacking visual definition of image processing methods, they can complement them if used in tandem. Sensor compositing and pedestrian tracking are implemented in a unified system. Several methods for fusing compass and gyroscope data are compared, but do not produce statistically significant improvement over using just the compass. The system achieves loop closure accuracy of 91% of path length and performs consistently across multiple participants. The final system can be used in GPS-denied locations and presents an image content independent way of managing photographs. It contributes to pedestrian tracking and image composting fields and has potential commercial uses (illustrated by an example Android app).
245

Characterising fitness landscapes with fitness-probability cloud and its applications to algorithm configuration

Lu, Guanzhou January 2014 (has links)
Metaheuristics are approximation optimisation techniques widely applied to solve complex optimisation problems. Despite a large number of developed metaheuristic algorithms, a limited amount of work has been done to understand on which kinds of problems the proposed algorithm will perform well or poorly and why. A useful solution to this dilemma is to use fitness landscape analysis to gain an in-depth understanding of which algorithms, or algorithm variants are best suited for solving which kinds of problem instances, even to dynamically determine the best algorithm configuration during different stages of a search algorithm. This thesis for the first time bridges the gap between fitness landscape analysis and algorithm configuration, i.e., finding the best suited configuration of a given algorithm for solving a particular problem instance. Studies in this thesis contribute to the following: a. Developing a novel and effective approach to characterise fitness landscapes and measure problem difficulty with respect to algorithms. b. Incorporating fitness landscape analysis in building a generic (problem-independent) approach, which can perform automatic algorithm configuration on a per-instance base, and in designing novel and effective algorithm configurations. c. Incorporating fitness landscape analysis in establishing a generic framework for designing adaptive heuristic algorithms.
246

On a purely categorical framework for coalgebraic modal logic

Chen, Liang-Ting January 2014 (has links)
A category CoLog of distributive laws is introduced to unify different approaches to modal logic for coalgebras, based merely on the presence of a contravariant functor P that maps a state space to its collection of predicates. We show that categorical constructions, including colimits, limits, and compositions of distributive laws as a tensor product, in CoLog generalise and extend existing constructions given for Set coalgebraic logics and that the framework does not depend on any particular propositional logic or state space. In the case that P establishes a dual adjunction with its dual functor S, we show that a canonically defined coalgebraic logic exists for any type of coalgebras. We further restrict our discussion to finitary algebraic logics and study equational coalgebraic logics. Objects of predicate liftings are used to characterise equational coalgebraic logics. The expressiveness problem is studied via the mate correspondence, which gives an isomorphism between CoLog and the comma category from the pre-composition to the post-composition with S. Then, the modularity of the expressiveness is studied in the comma category via the notion of factorisation system.
247

Task scheduling and merging in space and time

Mudrova, Lenka January 2017 (has links)
Every day, robots are being deployed in more challenging environments, where they are required to perform complex tasks. In order to achieve these tasks, robots rely on intelligent deliberation algorithms. In this thesis, we study two deliberation approaches – task scheduling and task planning. We extend these approaches in order to not only deal with temporal and spatial constraints imposed by the environment, but also exploit them to be more efficient than the state-of-the-art approaches. Our first main contribution is a scheduler that exploits a heuristic based on Allen’s interval algebra to prune the search space to be traversed by a mixed integer program. We empirically show that the proposed scheduler outperforms the state of the art by at least one order of magnitude. Furthermore, the scheduler has been deployed on several mobile robots in long-term autonomy scenarios. Our second main contribution is the POPMERX algorithm, which is based on merging of partially ordered temporal plans. POPMERX first reasons with the spatial and temporal structure of separately generated plans. Then, it merges these plans into a single final plan, while optimising the makespan of the merged plan. We empirically show that POPMERX produces better plans that the-state-ofthe- art planners on temporal domains with time windows.
248

Population based spatio-temporal probabilistic modelling of fMRI data

Alowadi, Nahed January 2018 (has links)
High-dimensional functional magnetic resonance imaging (fMRI) data is characterized by complex spatial and temporal patterns related to neural activation. Mixture based Bayesian spatio-temporal modelling is able to extract spatiotemporal components representing distinct haemodyamic response and activation patterns. A recent development of such approach to fMRI data analysis is so-called spatially regularized mixture model of hidden process models (SMM-HPM). SMM-HPM can be used to reduce the four-dimensional fMRI data of a pre-determined region of interest (ROI) to a small number of spatio-temporal prototypes, sufficiently representing the spatio-temporal features of the underlying neural activation. Summary statistics derived from these features can be interpreted as quantification of (1) the spatial extent of sub-ROI activation patterns, (2) how fast the brain respond to external stimuli; and (3) the heterogeneity in single ROIs. This thesis aims to extend the single-subject SMM-HPM to a multi-subject SMM-HPM so that such features can be extracted at group-level, which would enable more robust conclusion to be drawn.
249

On some multivariate control charts

Alfarag, Fadhil January 2016 (has links)
To maintain the quality of a product or to improve the reliability of a process, all industries need to monitor several parameters about their production process. Control charts are some visualization tools for monitoring processes statistically. In this work, we propose a few control charting schemes to monitor several characteristics of a process at the same time and to detect when it goes out of control. Our objective is to reduce the false alarms (the scheme detects a problem when actually there is none) as well as to quickly detect the correct out-of-control situation. The novelty of the proposed schemes are that they do not depend on commonly assumed Normal distribution of the process variables and is applicable for a much wider range of data distributions. At first, we make a detailed literature review of some univariate and multivariate control charts. We perform a comparison study of the commonly used multivariate control charts when the underlying distribution is not normal and show that they perform poorly giving a very high false alarm rate. Next we propose some nonparametric multivariate control charts based on the lengths of the multivariate rank vectors. The ideas are similar to the ones proposed by Liu (1995), however, we show that our proposed methods are computationally simpler in any dimension. We propose some more multivariate versions of Shewhert type, CUSUM and EWMA control charts based on spatial sign vectors and signed rank vectors. We also discuss several design parameters in the construction of these charts. None of the proposed charts depend on the assumption of underlying distribution or estimation of distributional parameters.
250

Nanomaterial sensing : integrating MEMS technology and self-assembled monolayers

Rushdi, Abduljabbar Ibrahim Rasheed January 2018 (has links)
The integration of self-assembled monolayer (SAM) into microelectromechanical system (MEMS) devices is introduced in Chapter 1. Chapter 2 is concerned with the specific immobilization of NeutrAvidin on pure and mixed SAMs of biotinylated tri(ethylene glycol) undecanethiol (BUT, biotin containing sensor element for Neutravidin) and tetra(ethylene glycol) (TEG, spacer) which were deposited on Au surfaces. Contact angle, ellipsometry and XPS were used to characterize the composition of these SAMs. SPR and QCM were used to study the adsorption behavior of NeutrAvidin to the pure and mixed SAMs. Chapter 3 describes the optimum conditions in details of how to obtain the monolayer of 11-amino-1-undecanethiol hydrochloride (Alk-amine) and 4-aminothiophenol (Ar-amine) SAM, which were deposited on an Au surface by using an ethanolic solution of Triethylamine (TEA) and how to reduce the contamination which are combined with the deposition of the two amines. Finally, ellipsometry, contact angle and XPS were used to characterise the monolayer of two amine SAMs. Chapter 4 describes the optimum conditions of gold nanoparticles (G-NPs) deposition on a monolayer of Alk and Ar-amine terminated SAMs, which were described in chapter 3, at different pHs. AFM and QCM confirm that the optimum deposition of G-NPs was at pH 5 for the two amine SAMs and the deposition on Alk-amine SAM is much higher than on Ar-amine SAM. Thus, Alk-amine SAM was chosen for chemically modifying the surface of a micro paddle. After the modification the paddle was used to detect the deposited mass of G-NPs and SEM was used to confirm dispersity of the monolayer of G-NPs.

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