In recent years there has been growing interest in ad-hoc and wireless sensor networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the main sought after parameter. The cooperative localization performance of WSNs is ultimately constrained by the behavior of the utilized ranging technology in dense cluttered indoor environments. Recently, ultra-wideband (UWB) Time-of-Arrival (TOA) based ranging has exhibited potential due to its large bandwidth and high time resolution. However, the performance of its ranging and cooperative localization capabilities in dense indoor multipath environments needs to be further investigated. Of main concern is the high probability of non-line of sight (NLOS) and Direct Path (DP) blockage between sensor nodes, which biases the TOA estimation and degrades the localization performance. In this dissertation, we first present the results of measurement and modeling of UWB TOA-based ranging in different indoor multipath environments. We provide detailed characterization of the spatial behavior of ranging, where we focus on the statistics of the ranging error in the presence and absence of the DP and evaluate the pathloss behavior in the former case which is important for indoor geolocation coverage characterization. Parameters of the ranging error probability distributions and pathloss models are provided for different environments: traditional office, modern office, residential and manufacturing floor; and different ranging scenarios: indoor-to-indoor (ITI), outdoor-to-indoor (OTI) and roof-to-indoor (RTI). Based on the developed empirical models of UWB TOA-based OTI and ITI ranging, we derive and analyze cooperative localization bounds for WSNs in the different indoor multipath environments. First, we highlight the need for cooperative localization in indoor applications. Then we provide comprehensive analysis of the factors affecting localization accuracy such as network and ranging model parameters. Finally we introduce a novel distributed cooperative localization algorithm for indoor WSNs. The Cooperative LOcalization with Quality of estimation (CLOQ) algorithm integrates and disseminates the quality of the TOA ranging and position information in order to improve the localization performance for the entire WSN. The algorithm has the ability to reduce the effects of the cluttered indoor environments by identifying and mitigating the associated ranging errors. In addition the information regarding the integrity of the position estimate is further incorporated in the iterative distributed localization process which further reduces error escalation in the network. The simulation results of CLOQ algorithm are then compared against the derived G-CRLB, which shows substantial improvements in the localization performance.

No âmbito das mudanças climáticas globais, a quantificação do estoque de carbono em povoamentos florestais tem recebido mais atenção, principalmente pelo fato das florestas exercerem um papel fundamental no equilíbrio do estoque de carbono global. Com o objetivo de contribuir para esse processo, a parte investigativa deste trabalho foi desenvolvida em duas etapas. A primeira etapa objetivou o ajuste de modelos alométricos para a estimativa do estoque de carbono presente na biomassa total (Ctotal), no lenho comercial (Cleco) e parte residual (Crds) (casca, folhas e galhos) em plantações de Eucalyptus spp. em nível de árvores, através de uma amostragem destrutivas de árvores, análise elementar do carbono em laboratório e medidas convencionais de inventário. A medição do diâmetro à altura do peito (DAP) e altura total das árvores em parcelas amostradas instaladas nos talhões onde as árvores foram coletadas para determinação direta de carbono também foi realizada. A segunda parte, consistiu na avaliação do uso da tecnologia LiDAR (Light Detection and Ranging) aerotransportada (Airborne LASER scanning) como uma alternativa eficiente e versátil para a estimativa do estoque de carbono total (Ctotal), no lenho comercial de toras (Cleco) e no resíduo da árvore (Crds) em nível de parcelas em plantações de Eucalyptus spp usando como base o estoque de carbono estimado na primeira fase. Os resultados obtidos encontram-se resumidos em dois artigos científicos. O primeiro artigo mostra que os modelos baseados no logaritmo do diâmetro à altura do peito (DAP) e da altura total da árvore (Ht) oferecem boas precisão e exatidão para estimar o estoque de carbono em nível de árvore. O segundo artigo, permitiu a determinação das melhores métricas LiDAR para o cálculo do teor total de carbono, tanto no carbono total, lenho comercial e nas partes residuais da árvore em nível de plantação. Esses resultados, bem como os indicadores estatísticos utilizados para avaliar a qualidade dos ajustes, são o cerne desta dissertação. / In the context of global climate change, the quantification of the carbon content in forest plantations have received great attention. This is because vegetation play an important role in the global carbon budget. This master thesis was developed in two main parts. The first part was to adjust allometric equations for the estimation of the carbon content at a tree level. This was performed for the above ground section (Ctotal), in commercial logs (Cleco) and residuals ( Crds) (e.g. bark, leaves and branches/twigs). The experiment was based on the destructive model of individual trees harvested in commercial plantations of Eucaliptus spp. The experiment encompasses both forest inventory and laboratory analyses procedures. Additionally, in-situ measurements such as the diameter at the breast height (DBH) and the total tree height were also performed. These sample plots were located in homogeneous forest units and close to the areas were the trees have been harvested. The second part of this master thesis was the evaluation of the airborne LiDAR technology as a tool for the retrieval of the above ground biomass (Ctotal), the carbon present in the commercial logs (Cleco) and residuals. This procedure was performed at the sample plots level. This procedure was based on the information provided in the first part. The results are presented as two scientific manuscripts. The first manuscript shows that allometric equations based on the log of the variables diameter at the breast height (DBH) and total tree height (Ht) were good predictors for the retrieval of the total carbon content at a tree level. The second manuscript allow the selection of the best LiDAR derived metrics for the retrieval of the total carbon content, either at above ground level, commercial logs and residual parts of the tree at a sample plots level. These results, as well as the statistical indicators for the adjustment of several statistical models is the core of this master thesis.

Multi-spectral Satellite imagery, among remotely sensed data from airborne and spaceborne platforms, contained the NIR band information is the major source for the land- cover classification. The main purpose of aerial imagery is for thematic land-use/land-cover mapping which is rarely used for land cover classification. Recently, the newly developed digital aerial cameras containing NIR band with up to 10cm ultra high resolution makes the land-cover classification using aerial imagery possible. However, because the urban ground objects are so complex, multi-spectral imagery is still not sufficient for urban classification. Problems include the difficulty in discriminating between trees and grass, the misclassification of buildings due to diverse roof compositions and shadow effects, and the misclassification of cars on roads. Recently, aerial LiDAR (ULiUght UDUetection UAUnd URUanging) data have been integrated with remotely sensed data to obtain better classification results. The LiDAR-derived normalized digital surface models (nDSMs) calculated by subtracting digital elevation models (DEMs) from digital surface models (DSMs) becomes an important factor for urban classification. This study proposed an adaptive raw-data-based, surface-based LiDAR data-filtering algorithm to generate DEMs as the foundation of generating the nDSMs. According to the experiment results, the proposed adaptive LiDAR data-filtering algorithm not only successfully filters out ground objects in urban, forest, and mixed land cover areas but also derives DEMs within the LiDAR data measuring accuracy based on the absolute and relative accuracy evaluation experiments results. For the aerial imagery urban classification, this study first conducted maximum likelihood classification (MLC) experiments to identify features suitable for urban classification using LiDAR data and aerial imagery. The addition of LiDAR height data improved the overall accuracy by up to 28 and 18%, respectively, compared to cases with only red¡Vgreen¡Vblue (RGB) and multi-spectral imagery. It concludes that the urban classification is highly dependent on LiDAR height rather than on NIR imagery. To further improve classification, this study proposes a knowledge-based classification system (KBCS) that includes a three-level height, ¡§asphalt road, vegetation, and non-vegetation¡¨ (A¡VV¡VN) classification model, rule-based scheme and knowledge-based correction (KBC). The proposed KBCS improved overall accuracy by 12 and 7% compared to maximum likelihood and object-based classification, respectively. The classification results have superior visual interpretability compared to the MLC classified image. Moreover, the visual details in the KBCS are superior to those of the OBC without involving a selection procedure for optimal segmentation parameters.

With the increasing advancements in the digital technology, future wireless systems are promising to support higher data rates, higher mobile speeds, and wider coverage areas, among other features. While further technological developments allow systems to support higher computational complexity, lower power consumption, and employ larger memory units, other resources remain limited. One such resource, which is of great importance to wireless systems, is the available spectrum for radio communications. To be able to support high data rate wireless applications, there is a need for larger bandwidths in the spectrum. Since the spectrum cannot be expanded, studies have been concerned with fully utilizing the available spectrum. One approach to achieve this goal is to reuse the available spectrum through space, time, frequency, and code multiplexing techniques. Another approach is to optimize the transceiver design as to achieve the highest throughput over the used spectrum. From the physical layer perspective, there is a need for a highly flexible and efficient modulation technique to carry the communication signal. A multicarrier modulation technique known as orthogonal frequency division multiplexing (OFDM) is one example of such a technique. OFDM has been used in a number of current wireless standards such as wireless fidelity (WiFi) and worldwide interoperability for microwave access (WiMAX) standards by the Institute of Electrical and Electronics Engineers (IEEE), and has been proposed for future 4G technologies such as the long term evolution (LTE) and LTE-advanced standards by the 3rd Generation Partnership Project (3GPP), and the wireless world initiative new radio (WINNER) standard by the Information society technologies (IST). This is due to OFDM’s high spectral efficiency, resistance to narrow band interference, support for high data rates, adaptivity, and scalability. In this dissertation, OFDM and multiuser OFDM , also known as orthogonal frequency division multiple access (OFDMA), techniques are investigated as a candidate for advanced wireless systems. Features and requirements of future applications are discussed in detail, and OFDM’s ability to satisfy these requirements is investigated. We identify a number of challenges that when addressed can improve the performance and throughput of OFDM-based systems. The challenges are investigated over three stages. In the first stage, minimizing, or avoiding, the interference between multiple OFDMA users as well as adjacent systems is addressed. An efficient algorithm for OFDMA uplink synchronization that maintains the orthogonality between multiple users is proposed. For adjacent channel interference, a new spectrum shaping method is proposed that can reduce the out-of-band radiation of OFDM signals. Both methods increase the utilization of available spectrum and reduce interference between different users. In the second stage, the goal is to maximize the system throughput for a given available bandwidth. The OFDM system performance is considered under practical channel conditions, and the corresponding bit error rate (BER) expressions are derived. Based on these results, the optimum pilot insertion rate is investigated. In addition, a new pilot pattern that improves the system ability to estimate and equalize various radio frequency (RF) impairments is proposed. In the last stage, acquiring reliable measurements regarding the received signal is addressed. Error vector magnitude (EVM) is a common performance metric that is being used in many of today’s standards and measurement devices. Inferring the signal-to-noise ratio (SNR) from EVM measurements has been investigated for either high SNR values or data-aided systems. We show that using current methods does not yield reliable estimates of the SNR under other conditions. Thus, we consider the relation between EVM and SNR for nondata-aided systems. We provide expressions that allow for accurate SNR estimation under various practical channel conditions.

Ultrawideband (UWB) is one of the promising technologies for future short-range high data rate communications (e.g. for wireless personal area networks) and longer range low data rate communications (e.g. wireless sensor networks).Despite its various advantages and potentials (e.g. low-cost circuitry, unlicensed reuse of licensed spectrum, precision ranging capability etc.), UWB also has its own challenges. The goal of this dissertation is to identify and address some of those challenges, and provide a framework for practical UWB transceiver design.In this dissertation, various modulation options for UWB systems are reviewed in terms of their bit error rate (BER) performances, spectral characteristics, modem and hardware complexities, and data rates. Time hopping (TH) code designs for both synchronous (introduced an adaptive code assignment technique) and asynchronous UWB impulse radio (IR) systems are studied. An adaptive assignment of two different multiple access parame ters (number of pulses per symbol and number of pulse positions per frame)is investigated again considering both synchronous and asynchronous scenarios, and a mathematical framework is developed using Gaussian approximations of interference statistics for different scenarios. Channel estimation algorithms for multiuser UWB communication systems using symbol-spaced (proposed a technique that decreases the training size), frame-spaced (proposed a pulse-discarding algorithm for enhanced estimationperformance), and chip-spaced (using least squares (LS) estimation) sampling are analyzed.A comprehensive review on multiple accessing andinterference avoidance/cancellation for IR-UWB systems is presented.BER performances of different UWB modulation schemes in the presence of timing jitter are evaluated and compared in static and multipath fading channels, and finger estimation error, effects of jitter distribution, and effects of pulse shape are investigated. A unified performance analysis app roach for different IR-UWB transceiver types (stored-reference, transmitted-reference, and energy detector) employing various modulation options and operating at sub-Nyquist sampling rates is presented. The time-of-arrival (TOA) estimation performance of different searchback schemesunder optimal and suboptimal threshold settings are analyzed both for additive white Gaussian noise (AWGN) and multipath channels.

Die letzten zwanzig Jahre haben gezeigt, dass die Integration luftgestützter Lasertechnologien (Light Detection and Ranging; LiDAR) in die Erfassung von Waldressourcen dazu beitragen kann, die Genauigkeit von Schätzungen zu erhöhen. Um diese zu ermöglichen, müssen Feldaten mit LiDAR-Daten kombiniert werden. Diverse Techniken der Modellierung bieten die Möglichkeit, diese Verbindung statistisch zu beschreiben. Während die Wahl der Methode in der Regel nur geringen Einfluss auf Punktschätzer hat, liefert sie unterschiedliche Schätzungen der Genauigkeit. In der vorliegenden Studie wurde der Einfluss verschiedener Modellierungstechniken und Variablenauswahl auf die Genauigkeit von Schätzungen untersucht. Der Schwerpunkt der Arbeit liegt hierbei auf LiDAR Anwendungen im Rahmen von Waldinventuren. Die Methoden der Variablenauswahl, welche in dieser Studie berücksichtigt wurden, waren das Akaike Informationskriterium (AIC), das korrigierte Akaike Informationskriterium (AICc), und das bayesianische (oder Schwarz) Informationskriterium. Zudem wurden Variablen anhand der Konditionsnummer und des Varianzinflationsfaktors ausgewählt. Weitere Methoden, die in dieser Studie Berücksichtigung fanden, umfassen Ridge Regression, der least absolute shrinkage and selection operator (Lasso), und der Random Forest Algorithmus. Die Methoden der schrittweisen Variablenauswahl wurden sowohl im Rahmen der Modell-assistierten als auch der Modell-basierten Inferenz untersucht. Die übrigen Methoden wurden nur im Rahmen der Modell-assistierten Inferenz untersucht. In einer umfangreichen Simulationsstudie wurden die Einflüsse der Art der Modellierungsmethode und Art der Variablenauswahl auf die Genauigkeit der Schätzung von Populationsparametern (oberirdische Biomasse in Megagramm pro Hektar) ermittelt. Hierzu wurden fünf unterschiedliche Populationen genutzt. Drei künstliche Populationen wurden simuliert, zwei weitere basierten auf in Kanada und Norwegen erhobenen Waldinveturdaten. Canonical vine copulas wurden genutzt um synthetische Populationen aus diesen Waldinventurdaten zu generieren. Aus den Populationen wurden wiederholt einfache Zufallsstichproben gezogen und für jede Stichprobe wurden der Mittelwert und die Genauigkeit der Mittelwertschätzung geschäzt. Während für das Modell-basierte Verfahren nur ein Varianzschätzer untersucht wurde, wurden für den Modell-assistierten Ansatz drei unterschiedliche Schätzer untersucht. Die Ergebnisse der Simulationsstudie zeigten, dass das einfache Anwenden von schrittweisen Methoden zur Variablenauswahl generell zur Überschätzung der Genauigkeiten in LiDAR unterstützten Waldinventuren führt. Die verzerrte Schätzung der Genauigkeiten war vor allem für kleine Stichproben (n = 40 und n = 50) von Bedeutung. Für Stichproben von größerem Umfang (n = 400), war die Überschätzung der Genauigkeit vernachlässigbar. Gute Ergebnisse, im Hinblick auf Deckungsraten und empirischem Standardfehler, zeigten Ridge Regression, Lasso und der Random Forest Algorithmus. Aus den Ergebnissen dieser Studie kann abgeleitet werden, dass die zuletzt genannten Methoden in zukünftige LiDAR unterstützten Waldinventuren Berücksichtigung finden sollten.

[Truncated abstract] This thesis describes the development, clinical validation and initial application of a technique for taking measurements of the shape and dimensions of the human upper airway, called anatomical optical coherence tomography (aOCT). The technique uses a transparent catheter containing a rotating optical probe which is introduced transnasally and positioned in the airway and oesophagus. Optical coherence tomography is used to take calibrated cross-sectional images of the airway lumen as the probe rotates. The probe can also be advanced or withdrawn within the catheter during scanning to build up three-dimensional information. The catheter remains stationary so that the subject is not aware of the probe motion. The initial application of the system is research into obstructive sleep apnoea (OSA), a serious condition characterized by repetitive collapse of the upper airway during sleep and an independent risk factor for deaths by heart disease, strokes or car accidents. Measurement of upper airway size and shape is important for the investigation of the pathophysiology of OSA, and for the development and assesment of new treatments. . . We have used aOCT to capture three-dimensional data sets of the airway shape from upper oesophagus to the nasal cavity, undertaken measurements of compliance and other airway characteristics, and recorded dynamic airway shape during confirmed sleep apnoea events in a hospital sleep laboratory. We have shown that aOCT generates quantitative, real-time measurements of upper airway size and shape, allowing study over lengthy periods during both sleep and wakefulness. These features should make it useful for study of upper airway behavior to investigate OSA pathophysiology, and aid clinical management and treatment development.

Light Detection and Ranging (LIDAR) är en teknik för att samla in data om terräng. Genom att använda dessa data kan man skapa olika terrängmodeller. Denna studie syftar till att undersöka hur olika procentuella reduceringar av ursprungsdata påverkar kvalitén hos genererade höjdmodeller i form av Triangular Irregular Network (TIN). Detta görs genom att med hjälp av statistiska metoder göra jämförelser mellan punkter i den genererade TIN modellen och motsvarande punkter i det ursprungliga LIDAR punktmolnet. Studien visar att, beroende på noggrannhetskrav och topografi, en så liten andel som 5 % av punkterna kan vara tillräckligt, samt att noggrannhetsförbättring vid användning av mer än 50 % av ursprungsdata inte kan motivera den ökade arbetsbelastningen för datahantering.

This thesis is concerned with the task of autonomous selection of objects to remove (unload) them from a pile in robotic manipulation systems. Applications such as the automation of logistics processes and service robots require an ability to autonomously manipulate objects in the environment. A collapse of a pile of objects due to an inappropriate choice of the object to be removed from the pile cannot be afforded for an autonomous robotic manipulation system. This dissertation presents an indepth analysis of the problem and proposes methods and algorithms to empower robotic manipulation systems to select a safe object from a pile elaborately and autonomously. The contributions presented in this thesis are three-fold. First, a set of algorithms is proposed for extracting a minimal set of high level symbolic relations, namely, gravitational act and support relations, of physical interactions between objects composing a pile. The symbolic relations, extracted by a geometrical reasoning method and a static equilibrium analysis can be readily used by AI paradigms to analyze the stability of a pile and reason about the safest set of objects to be removed. Considering the problem of undetected objects and the uncertainty in the estimated poses as they exist in realistic perception systems, a probabilistic approach is proposed to extract the support relations and to make a probabilistic decision about the set of safest objects using notions from machine learning and decision theory. Second, an efficient search based algorithm is proposed in an internal representation to automatically resolve the inter-penetrations between the shapes of objects due to errors in the poses estimated by an existing object detection module. Refining the poses by resolving the inter-penetrations results in a geometrically consistent model of the environment, and was found to reduce the overall pose error of the objects. This dissertation presents the concept of minimum translation search for object pose refinement and discusses a discrete search paradigm based on the concept of depth of penetration between two polyhedrons. Third, an application centric evaluation of ranging sensors for selecting a set of appropriate sensors for the task of object detection in the design process of a real-world robotics manipulation system is presented. The performance of the proposed algorithms are tested on data sets generated in simulation and from real-world scenarios.

Bovine tuberculosis is a global cause for concern in livestock, free-ranging wildlife, zoological collections and the human population. Large amount of time, effort and resources are spent on its diagnosis and control methods. This study was aimed at determining the sensitivity and specificity of the IS6110 specific PCR test on formalin fixed, paraffin embedded (FFPE) tissue blocks, compared to that of the gold standard method culture and to differentiate M. bovis from other members of the M. tuberculosis complex using the RD4 region of difference specific PCR test. A total of 141 FFPE tissue blocks of wild animals from game reserves, the National Zoological Gardens and routine tuberculosis (TB) surveys in Kruger National Park were tested. Among the 50 known TB positive samples (35 M. bovis culture positive, twelve M. tuberculosis culture positive and three diagnosed tuberculosis positive on histopathology examination) the IS6110 PCR had an overall sensitivity of 22%. The positive predictive value of the IS6110 test (91.67%) was quite high implying that although sensitivity was low, one can be highly confident that a positive test result is a true reflection of the positive disease status. The overall sensitivity of the RD4 PCR was 20%. The positive predictive value of the RD4 test (41.67%) was low, implying that a positive test result may be unreliable. The sensitivities of the M. tuberculosis and M. bovis culture positive samples were compared and a significant difference was noted. Sensitivities of the IS6110 and RD4 assays in M. tuberculosis culture positive samples were 66.67% and 33.33%, respectively; sensitivities of the IS6110 and RD4 assays in M. bovis culture positive samples were 8.57% and 17.14%, respectively. Difference in bacterial load in tissues infected with the two mycobacterial species may account for this finding (i.e. M. bovis infections have a lower bacteria load). Of the 91 known TB negative samples, the specificity of the IS6110 (98.90%) and RD4 (84.62%) PCR tests were high, but the negative predictive values of 69.67% and 65.81%, respectively, suggest that the probability of negative test results being incorrect still exists. The resultant sensitivity was increased when parallel interpretation was applied to histopathology examination and the IS6110 or RD4 PCR tests and when applied to the IS6110 and RD4 PCR tests. Both histopathology examination and PCR tests produce rapid results and their combination can be used in routine diagnostics. The RD4 PCR assay was unable to distinguish M. bovis from other members of the MTB complex and based on the findings of this study the RD4 PCR cannot add value to the diagnosis of suspect tuberculosis samples at this stage, but successful troubleshooting relating to 1) extraction method, 2) DNA inhibitors, 3) contamination and 4) multisampling protocol, may enable its use in future. / Dissertation (MSc)--University of Pretoria, 2013. / gm2014 / Veterinary Tropical Diseases / Unrestricted