Differential Mobility Spectrometry (DMS) using a non-radioactive ion source (NRIS) is investigated as a possible medical diagnostic instrument for near real-time detection of breast cancer biomarkers. In previous clinical studies, concentrations of Linoleic, Palmitic and Stearic fatty acids have been observed at different levels in women with carcinoma breast cancer versus women with benign tumors or healthy women showing no signs of breast cancer. Present diagnostic methods require a biopsy of the suspect tissue and a microscopic lab analysis performed to determine its disease state. This process can take hours or days before the patient and doctor are informed of the results. Controlled volumetric samples of each fatty acid listed above were introduced into a DMS instrument, using a NRIS, to determine detectability of each acid. The results provide proof-of-concept that Linoleic, Palmitic and Stearic fatty acids can be uniquely identified by varying the sample temperature and scanning the ionized fatty acid molecules in both the negative and positive ion mode of the DMS instrument. Detection response times range from 2 to 6 seconds for initial detection up to 35 seconds for peak detection. The Limit of Detection for the DMS instrument is estimated in the low parts per billion.

Proprietary.

This Ph.D. dissertation focuses on a comprehensive study of seismic waveform similarity aiming at two themes: (1) reliable identification of repeating earthquakes (repeaters) and (2) investigation of the detailed source process of induced seismicity through the three-dimensional spatiotemporal evolution of mainly neighbouring earthquakes. Theme 1: Reliable identification of repeaters. Repeaters, occurring repeatedly on the same fault patch with nearly identical waveforms, are usually identified with the match-filtering (MF) method which essentially measures the degree of waveform similarity between an earthquake pair through the corresponding cross-correlation coefficient (CC). However, the performance of the MF method can be severely affected by the length of the cross‐correlation window, the frequency band of the applied digital filter, and the presence of a large‐amplitude wave train. To optimize the performance of MF, I first examine the effects of different operational parameters and determine generic rules for selecting the window length and the optimal frequency passband. To minimize the impact of a large‐amplitude wave train, I then develop a new method, named the match-filtering with multisegment cross-correlation (MFMC) method. By equally incorporating the contributions from various segments of the waveforms, the new method is much more effective in capturing the minor waveform discrepancy between an event pair due to location difference and hence is more reliable in detecting potential repeaters and discriminating non-repeaters with large inter-event separation. With both synthetic and borehole array waveform data, I further reveal that waveform similarity is controlled by not only the inter-event separation but also many other factors, including station azimuth, epicentral distance, velocity structure, etc. Therefore, in contrast to the traditional view, the results indicate that waveform similarity alone is insufficient to unambiguously identify true repeaters. For reliable repeater identification, we should rely on a physics-based approach considering both the overlapped source area and magnitude difference. Specifically, I define an event pair to be true repeaters if their inter-event separation is smaller than the rupture radius of the larger event and their magnitude difference is no more than 1. For the precise estimation of inter-event distance in cases of limited data, I develop the differential traveltime double-difference (DTDD) method which relies on the relative S-P differential traveltime. The findings of this study imply that previously identified repeaters and their interpretations/hypotheses potentially can be biased and hence may need a systematic reexamination. Theme 2: Investigation of the detailed source process of induced seismicity. Earthquakes induced by hydraulic fracturing (HF), especially those with large magnitudes, are often observed to have occurred near/after well completion. The delayed triggering of induced seismicity with respect to injection commencement poses serious challenges for risk mitigation and hazard assessment. By performing waveform cross-correlation and hierarchical clustering analysis, I reveal a high-resolution three-dimensional source migration process with mainshock delayed triggering that is probably controlled by local hydrogeological conditions. The results suggest that poroelastic effects might contribute to induced seismicity but are likely insufficient to activate a non-critically stressed fault of sufficient size. My analysis shows that the rapid pore-pressure build-up from HF can be very localized and capable of producing large, felt earthquakes on non-critically stressed fault segments. I further infer that the number of critically stressed, large intraplate faults should be very limited, and that reactivation of such faults may require sufficient pore-pressure accumulation. The findings of this study may also explain why so few fluid injections are seismogenic. / Graduate

No description available.

No description available.

Drilled shafts are deep foundation elements created by excavating cylindrical shafts into the ground and filling them with concrete. Given the types of structures they support, failure to meet their performance criteria can jeopardize public safety and cause severe financial losses. Consequently, quality control measures are warranted to ensure these foundations meet design specifications, particularly with respect to their structural integrity and geotechnical capacity. Due to their inaccessibility, non-destructive testing (NDT) techniques have received much attention for drilled shaft quality control. However, there are limitations in the NDT tools currently used for structural integrity testing. Moreover, there is no current NDT tool to evaluate conditions underlying drilled shaft excavations and aid in verifying geotechnical capacity. The main objective of this research is to examine the development of new NDT methodologies to address some of the limitations in the inspection of drilled shaft structural integrity and geotechnical conditions underlying their excavations. The use of stress waves in large laboratory models is first examined to evaluate the performance of ray-based techniques for detecting anomalies. The study then continues to investigate the improvements offered by using a full waveform inversion (FWI) approach to analyze the stress wave data. A hybrid, multi-scale FWI workflow is recommended to increase the chance of the convergence of the inversion algorithms. Additionally, the benefits of a multi-parameter FWI are discussed. Since FWI is computationally expensive, a sequential optimal experimental design (SOED) analysis is proposed to determine the optimal hardware configurations for each application. The resulting benefit-cost curves from this analysis allow for designing an NDT survey that matches the available resources for the project. / Civil Engineering

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / Waveform Description Language (WDL) was invented to ease the process of porting legacy and/ or new radio waveforms to Programmable / Software Radios. WDL has two primary requirements; 1st it is to provide a rigorous executable behavioural description of waveform signal structures that is unambiguous and yet independent of any particular end item software radio architecture. The 2nd requirement is that the behavioural specification provides a path to automatic code generation for GP’s, DSP’s, and FPFG’s and that the Generated code be tested against the behavioural model.

Thesis (MScEng)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: In recent years Autonomous Underwater Vehicles (AUVs) have become interesting for harbor mapping and protection. AUVs require a SONAR sensor for observing their surroundings, thus enabling them to perform collision avoidance manoeuvres and scanning their operating environment for intruders or foreign objects, e.g. mines. To perform such actions the SONAR sensor is required to supply very fine range resolution for target imaging, as well as providing information about possible target velocity. Basic SONAR theory is discussed, as well as different approaches to signal design and processing techniques, for achieving the required resolution in range and target velocity. Two of the discussed approaches are selected for processing range and target velocity, respectively. Both approaches are simulated for their validity before being tested by using a custom-built platform. The platform is highly configurable and designed for capacity of testing a variety of SONAR signals and set ups. Furthermore, the platform is built by using off-the-shelf components to minimize development costs. The results of simulations and practical tests are presented. A high correlation between theory and practice is achieved. The knowledge and the platform presented form the stepping stone for further SONAR sensor developments. / AFRIKAANSE OPSOMMING: In die laaste jare het outonome onderwater voertuie (OOV) toenemend belangrik geword vir die kartografie en beskerming van hawens. OOV’s vereis SONAR sensore wat hulle in staat stel, om hulle omgewing waar te neem en sodoende botsing vermydings take te verrig en ook om hul werksomgewing noukeurig te skandeer om indringers of vreemde voorwerpe, bv. myne, op te spoor. Om sulke werk te verrig, word van die SONAR sensor vereis, om baie fyn afstand oplossings vir teiken te verskaf, insluitend die moontlike snelheid van die teiken. Basiese SONAR teorie word bespreek, en dan verskeie benaderings van sein ontwerp en verwerkings tegnieke. Twee van die bespreekte benaderings word gekies om afstand en teiken snelheid onderskeidelik te verwerk. Altwee benaderings word gesimuleer om hul geldigheid vas te stel, voor dat hulle getoets word op ’n pasmaat vervaardigde platform. Die platform is hoogs aanpasbaar en is ontwerp vir sy vermoë om ’n verskeidenheid SONAR seine en verwerkings te hanteer. Verder is die platform vervaardig met standard rakonderdele om ontwikkelingskoste so laag as moontlik te hou. Die uitslae van die simulerings en praktiese toetse word voorgestel. ’n Hoë mate aan korrelasie is bereik tussen teorie en praktyk. Die kennis en die platvorm, wat hier voorgestel word, vorm die eerste trappie vir toekomstige SONAR sensor ontwikkeling.

La Radio Logicielle (SDR : Software Defined Radio) et la Radio Cognitive (CR : Cognitive Radio) deviennent d'un usage courant car elles répondent à plusieurs enjeux technico-économiques majeurs dans le domaine des télécommunications. Ces systèmes radio permettent de combler l'écart de développement technologique qui existe entre la partie matérielle et la partie logicielle des systèmes de communication, en permettant la gestion optimale des bandes de fréquences sous-utilisées par la commutation en temps réel d'une configuration radio à une autre. Dans ce cadre, cette thèse présente la mise en œuvre d'une chaîne de traitements Radio Logicielle (appelée SDR waveform) dans un Système Multiprocesseurs sur Puce (MPSoC) à usage général (implémenté dans un FPGA de type Xilinx Virtex-4). Cette plateforme est basée autour d'un Réseau sur Puce (NoC) interconnectant 16 processeurs élémentaires (appelés PE) disposant de quatre blocs-mémoires externes DDR2. Nous avons proposé des implémentations temps réel et embarquées sur MPSoC de différentes briques de traitements d'une chaîne SDR, en concevant une stratégie efficace de parallélisation et de synchronisation pour chaque composante élémentaire de la « waveform ». Nous avons amélioré la fonctionnalité de la chaîne de traitement Radio Logicielle, en intégrant un Transceiver reconfigurable basé sur différents modèles de Réseaux de Neurones Artificiels (RNA) : les Cartes Auto-Organisatrices (SOM), les Réseaux de Neurones Compétitifs (LVQ) et enfin les Réseaux Multi-Couches de Perceptrons (MLP). Ces trois RNA permettent la reconnaissance de la norme spécifique basée sur les paramètres d'entrée extraits du signal et la reconfiguration du Transceiver de CR. La solution adaptative que nous avons proposée commute vers le RNA le plus approprié en fonction des caractéristiques du signal d'entrée détecté. Il est important de pouvoir prendre en compte des signaux complexes et multi-porteuses. Dans ce cadre, nous avons adressé le cas d'un signal complexe composé de plusieurs porteuses, ainsi en divisant les PEs en différents groupes indépendants, nous affectons chaque groupe de PEs au traitement d'une nouvelle porteuse. Nous avons conçu une stratégie efficace de synchronisation et de parallélisation de ces trois RNA pour CR Transceiver. Nous l'avons appliquée, par la suite pour l'implantation de nos algorithmes sur le MPSoC déjà cité. L'accélération que nous obtenons pour la SDR waveform et pour les algorithmes de Transceiver de CR démontre que les MPSoC à usage général sont une réponse pertinente, entre autres, aux contraintes de performances sur une telle plateforme. Le système que nous proposons apporte une réponse aux défis technico-économiques des grandes entreprises qui investissent ou prévoient d'investir dans des équipements basés sur des SDR ou des CR, puisqu'il permet d'éviter de recourir à des équipements d'accélération coûteux. Nous avons, par la suite, ajouté d'autres fonctionnalités à notre waveform avec un « CR Transceiver multinormes », en proposant une nouvelle approche pour la gestion du spectre radio. Ceci étant l'aspect le plus important de CR. Nous rendons ainsi notre waveform spectralement efficace en modélisant les caractéristiques radiofréquences (RF) du signal utilisateur primaire sous la forme d'une série temporelle multi-variée. Cette série temporelle est ensuite fournie comme entrée dans un Réseau de Neurones Récurrent d'Elman (ERNN) qui prédit l'évolution de la série temporelle de RF pour déterminer si l'utilisateur secondaire peut exploiter la bande de fréquences. Nous avons exploité la cyclo-stationnarité inhérente des signaux primaires pour la Modélisation Non-Linéaire Autorégressive Exogène (NARX : Non-linear AutoRegressive Exogenous) des séries temporelles des caractéristiques RF, car la prédiction d'une caractéristique RF demande d'abord de connaître les autres caractéristiques radios pertinentes. Nous avons observé une tendance similaire pour les valeurs prédites et observées. En résumé, nous avons proposé des algorithmes pour SDR waveform à efficacité spectrale avec un Transceiver Universel, ainsi que leurs implantations parallèles sur MPSoC. Notre conception de waveform répond aux exigences en performances et aux contraintes de ressources embarquées des applications dans le domaine / Software Defined Radio (SDR) and Cognitive Radio (CR) are entering mainstream. These high performance and high adaptability requiring devices with agile frequency operations hold promise to :1. address the inconsistency between hardware and software advancements, 2. real time mode switching from one radio configuration to another and3. efficient spectrum management in under-utilized spectrum bands. Framed within this statement, in this thesis we have implemented a SDR waveform on 16 Processing Element (PE) Network on chip (NoC) based general purpose Multiprocessors System on chip (MPSoC), with access to four external DDR2 memory banks, which is implemented on a single chip Xilinx Virtex-4 FPGA. We shifted short term development of a waveform into software domain by designing an efficient parallelization and synchronization strategy for each waveform component, individually. We enhance our designed waveform functionality by proposing and implementing three Artificial Neural Networks Schemes : Self Organizing Maps, Linear Vector Quantization and Multi-Layer Perceptrons as effective techniques for reconfiguring CR Transceiver after recognizing the specific standard based on input parameters, pertaining to different layers, extracted from the signal. Our proposed adaptive solution switches to appropriate Artificial Neural Network, based on the features of input signal sensed. We designed an efficient synchronization and parallelization strategy to implement the Artificial Neural Networks based CR Transceiver Algorithms on the aforementioned MPSoC chip. The speed up we obtained for our SDR waveform and CR Transceiver algorithms demonstrated that the general purpose MPSoC devices are the most efficient answer to the acquisition challenge for major organizations that invest or plan to invest in SDR and CR based devices, thereby allowing us to avoid expensive hardware accelerators. We address the case of a complex signal composed of many modulated carriers by dividing the PEs in individual groups, thus received signal with more than one Standard is processed efficiently. We add further functionality in our designed Multi-standard CR Transceiver possessing SDR Waveform by proposing a new approach for radio spectrum management, perhaps the most important aspect of CR. We make our designed waveform Spectrum efficient by modelling the primary user signal Radio Frequency features as a multivariate time series, which is then given as input to Elman Recurrent Neural Network that predicts the evolution of Radio Frequency Time Series to decide if the secondary user can exploit the Spectrum band. We exploit the inherent cyclostationary in primary signals for Non-linear Autoregressive Exogenous Time Series Modeling of Radio Frequency features, as predicting one RF feature needs the previous knowledge of other relevant RF features. We observe a similar trend between predicted and actual values. Ensemble, our designed Spectrum Efficient SDR waveform with a Universal Multi-standard Transceiver answers the SDR and CR performance requirements under resource constraints by efficient algorithm design and implementation using lateral thinking that seeks a greater cross-domain interaction

Les ions de terres rares en matrice cristalline, refroidis à très basse température, offrent des propriétés remarquables pour le traitement analogique du signal sur porteuse optique. L’élargissement inhomogène du spectre d’absorption peut en effet atteindre plusieurs centaines de gigahertz alors que la largeur homogène des raies d’absorption des ions individuels ne dépasse pas quelques kilohertz. Par pompage optique il est alors possible de modifier à volonté le profil du spectre d’absorption. On dispose ainsi d’un filtre programmable présentant à la fois une très grande bande passante, donnée par la largeur inhomogène, et une excellente résolution, fixée par la largeur homogène. Une raie d’absorption étroite correspond à un état de superposition quantique de longue durée de vie. C’est sous cet angle, celui des transitoires cohérents, et spécifiquement celui des échos de photons que nous abordons les propriétés du filtre programmable. Dans la première partie de la thèse, le filtre est programmé comme un élément dispersif. Il permet d’atteindre des taux de dispersion inaccessibles aux dispositifs optiques conventionnels, tels que les fibres optiques. Nous l’utilisons comme un composant de lentille temporelle, en vue de produire des signaux de forme arbitraire. Par rapport à des dispositifs d’optique conventionnels, on gagne plusieurs ordres de grandeurs en termes de produit temps x bande passante. Après avoir exploité l’écho de photon dans un contexte de filtrage linéaire, nous tirons parti de ses propriétés de très forte non-linéarité dans la seconde partie de la thèse. Cette fois nous cherchons à capturer un signal lumineux de très faible intensité, à le convertir en état de superposition atomique, puis à le restituer dans son état lumineux initial. Cela suppose en particulier d’empêcher les effets d’émission spontanée ou stimulé qui nuisent à la fidélité de la restitution. Pour ce faire, nous proposons un nouveau protocole que nous avons appelé « Revival Of Silenced Echo » (ROSE) / Rare earth ions doped crystals, when cooled at very low temperature, exhibit outstanding properties for optically-carried analogical signal processing. The absorption spectral broadening can reach several hundred of Gigahertz, while the homogeneous width of each individual ion does no exceed a few kilohertz. With the help of optical pumping, one may modify the absorption profile at will. The resulting programmable filter simultaneously offers a very large bandwidth, given by the inhomogeneous width, and a very good resolution, fixed by the homogeneous width. Narrow absorption line is related to long lifetime quantum superposition. We contemplate the programmable filter properties, keeping in mind this coherent transient picture, specifically related to photon echoes. In the first part of the dissertation, the programmable filter is programmed as a dispersive element. This gives access to dispersion rate values out of reach of conventional optical devices, such as optical fibers. We use the filter as a temporal lens component, with an eye to generating arbitrary waveforms. Thereby, we gain several orders of magnitude against conventional optical devices in terms of time x bandwidth product. After taking advantage of photon echoes in the linear filtering context, we capitalize on their strongly non-linear properties in the second part of the dissertation. This time we want to capture a very weak optical signal, to convert it into an atomic superposition state, and to restore it in its initial state of light. Faithful retrieval of the incoming signal relies on the elimination of spontaneous and stimulated emission. To this end, we propose a new protocol we have named « Revival Of Silenced Echo » (ROSE).