Supernova-Detektion mit dem IceCube-Neutrinoteleskop

IceCube, ein Neutrinoteleskop, welches zur Zeit am Südpol aufgebaut und voraussichtlich 2011 fertiggestellt sein wird, kann galaktische Kernkollaps-Supernovae mit hoher Signifikanz und unübertroffener statistischer Genauigkeit der Neutrinolichtkurve detektieren. Derartige Supernovae werden begleitet von einem massiven Ausbruch niederenergetischer Neutrinos aller Flavour. Beim Durchfliegen des Detektormediums Eis entstehen Positronen und Elektronen, welche wiederum lokale Tscherenkowlichtschauer produzieren, die in ihrer Summe das gesamte Eis erleuchten. Ein Nachweis ist somit, trotz der Optimierung IceCubes auf hochenergetische Teilchenspuren, über eine kollektive Rauschratenerhöhung aller optischen Module möglich. Die vorwiegende Reaktion ist der inverse Betazerfall der Antielektronneutrinos, welcher über 90,% des gesamten Signals ausmacht.rnrnDiese Arbeit beschreibt die Implementierung und Funktionsweise der Supernova-Datennahme-Software sowie der Echtzeitanalyse, mit welcher die oben genannte Nachweismethode seit August 2007 realisiert ist. Die Messdaten der ersten zwei Jahre wurden ausgewertet und belegen ein extrem stabiles Verhalten des Detektors insgesamt sowie fast aller Lichtsensoren, die eine gemittelte Ausfallquote von lediglich 0,3,% aufweisen. Eine Simulation der Detektorantwort nach zwei unterschiedlichen Supernova-Modellen ergibt eine Sichtweite IceCubes, die im besten Falle bis zur 51,kpc entfernten Großen Magellanschen Wolke reicht. Leider ist der Detektor nicht in der Lage, die Deleptonisierungsspitze aufzulösen, denn Oszillationen der Neutrinoflavour innerhalb des Sterns modifizieren die Neutrinospektren ungünstig. Jedoch können modellunabhängig anhand des frühesten Signalanstiegs die inverse Massenhierarchie sowie $sin^2 2theta_{13} > 10^{-3}$ etabliert werden, falls die Entfernung zur Supernova $leq$,6,kpc beträgt. Gleiches kann durch Auswertung eines möglichen Einflusses der Erdmaterie auf die Neutrinooszillation mit Hilfe der Messung eines zweiten Neutrinodetektors erreicht werden.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Thin films of polythiophene: Linear and nonlinear optical characterization

Wir haben die linearen und nichtlinearen optischen Eigenschaften von dünnen Schichten und planaren Wellenleitern aus mehreren konjugierten Polymeren (MEH-PPV und P3AT) und Polymeren mit -Elektronen Systemen in der Seitenkette (PVK und PS) untersucht und verglichen. PVK und PS haben relativ kleine Werte des nichtlinearen Brechungsindex n2 bei 532 nm, nämlich (1,2 ± 0,5)10-14 cm2/W und (2,6 ± 0,5) 10-14 cm2/W.rnWir haben die linearen optischen Konstanten von mehreren P3ATs untersucht, insbesondere den Einfluss der Regioregularität und Kettenlänge der Alkylsubstituenten. Wir haben das am besten geeignete Polymere für Wellenleiter Anwendungen identifiziert, welches P3BT-ra genannt ist. Wir haben die linearen optischen Eigenschaften dünner Schichten des P3BT-ra untersucht, die mit Spincoating aus verschiedenen Lösungsmitteln mit unterschiedlichen Siedetemperaturen präparieret wurden. Wir haben festgestellt, dass P3BT-ra Filme aus Toluol-Lösungen die am besten geeigneten Wellenleiter für die intensitätsabhängigen Prismen-Kopplungs Experimente sind, weil diese geringe Wellenleiterdämpfungsverluste bei = 1064 nm haben. rnWir haben die Dispersionen des Wellenleiterdämfungsverlustes gw, des nichtlinearen Brechungsindex n2 und des nichtlinearen Absorptionskoeffizienten 2 von Wellenleitern aus P3BT-ra im Bereich von 700 - 1500 nm gemessen. Wir haben große Werte des nichtlinearen Brechungsindex bis 1,5x10-13 cm2/W bei 1150 nm beobachtet. Wir haben gefunden, dass die Gütenkriterien (“figures of merit“) für rein optische Schalter im Wellenlängebereich 1050 - 1200 nm erfüllt sind. Dieser Bereich entspricht dem niederenergetischen Ausläufer der Zwei-Photonen-Absorption. Die Gütekriterien von P3BT-ra gehören zu den besten der bisher bekannten Werte von konjugierten Polymeren.rnWir haben gefunden, dass P3BT-ra ein vielversprechender Kandidat für integriert-optische Schalter ist, weil es eine gute Kombination aus großer Nichtlinearität dritter Ordnung, geringen Wellenleiterdämpfungverlusten und ausreichender Photostabilität zeigt. rnWir haben einen Vergleich der gemessenen Dispersion von gw, n2 und 2 mit der Theorie durchgeführt. Durch Kurvenanpassung der Dispersion von gw haben wir gefunden, dass Rayleigh-Streuung der dominierende Dämpfungsmechanismus in MEH-PPV und P3BT-ra Wellenleitern ist. Ein quantenmechanischer Ansatz wurde zur Berechnung der nichtlinearen Suszeptibilität dritter Ordnung (3) verwendet, um die gemessenen Spektren von n2 und 2 von P3BT-ra und MEH-PPV zu simulieren. Dies kann erklären, dass sättigbare Absorption und Zwei-Photonen Absorption die hauptsächlichen Effekte sind, welche die Dispersion von n2 und 2 verursachen. rn

Ultra low power analog-to-information conversion by short-time compressed sensing

Il compressed sensing è un’innovativa tecnica per l’acquisizione dei dati, che mira all'estrazione del solo contenuto informativo intrinseco di un segnale. Ciò si traduce nella possibilità di acquisire informazione direttamente in forma compressa, riducendo la quantità di risorse richieste per tale operazione. In questa tesi è sviluppata un'architettura hardware per l'acquisizione di segnali analogici basata sul compressed sensing, specializzata al campionamento con consumo di potenza ridotto di segnali biomedicali a basse frequenze. Lo studio è svolto a livello di sistema mediante l'integrazione della modulazione richiesta dal compressed sensing in un convertitore analogico-digitale ad approssimazioni successive, modificandone la logica di controllo. Le prestazioni risultanti sono misurate tramite simulazioni numeriche e circuitali. Queste confermano la possibilità di ridurre la complessità hardware del sistema di acquisizione rispetto allo stato dell'arte, senza alterarne le prestazioni.

Efficient computation of discrete polynomial transforms

This letter presents a new recursive method for computing discrete polynomial transforms. The method is shown for forward and inverse transforms of the Hermite, binomial, and Laguerre transforms. The recursive flow diagrams require only 2 additions, 2( +1) memory units, and +1multipliers for the +1-point Hermite and binomial transforms. The recursive flow diagram for the +1-point Laguerre transform requires 2 additions, 2( +1) memory units, and 2( +1) multipliers. The transform computation time for all of these transforms is ( )

Ear acupuncture points in neonates

OBJECTIVE: The aim of this study was to determine the presence and absence of acupuncture ear points in healthy neonates. DESIGN: This was a prospective observational study performed at a university teaching hospital. Subjects: The subjects were healthy neonates. We compared male and female neonates, right and left lobe, term and preterm deliveries, and cesarean sections versus vaginal deliveries. Examinations took place on the fifth day after delivery and were performed by a neuronal pen (SVESA 1070, SVESA GmbH, Munich, Germany). An integrated optical signal detected the ear points that were assigned to the Chinese ear map. MAIN OUTCOME MEASURES: This study looked at the presence and absence of acupuncture ear points in neonates. RESULTS: There were 27 male neonates and 23 female neonates. In 66% of neonates, no points at all were found. We detected 0-4 points on the right lobe and 0-2 points on the left lobe. The psychovegetative rim was the most common point in 26% of all children. No psychic points were detected. No significant differences were found between right and left ear lobes, male and female neonates, or term and preterm deliveries with respect to numbers of points or access of points. Moreover, there were no differences among modes of delivery. CONCLUSIONS: Some ear points in healthy neonates are detectable and not dependent on side of the ear lobe. Females had significantly more acupuncture points. There was an extremely significant difference in the group with 2 active earpoints between cesarean and vaginally delivered neonates. The most important point was the psychovegetative rim and the absence of psychic points in favor of the organ points. Possibly, ear points in neonates could be used for diagnostic and therapeutic options in neonates in the future.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

Application of MFBD Algorithms to Image Reconstruction Under Anisoplanatic Conditions

All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. Both military and civilian surveillance, gun-sighting, and target identification systems are interested in terrestrial imaging over very long horizontal paths, but atmospheric turbulence can blur the resulting images beyond usefulness. My dissertation explores the performance of a multi-frame-blind-deconvolution technique applied under anisoplanatic conditions for both Gaussian and Poisson noise model assumptions. The technique is evaluated for use in reconstructing images of scenes corrupted by turbulence in long horizontal-path imaging scenarios and compared to other speckle imaging techniques. Performance is evaluated via the reconstruction of a common object from three sets of simulated turbulence degraded imagery representing low, moderate and severe turbulence conditions. Each set consisted of 1000 simulated, turbulence degraded images. The MSE performance of the estimator is evaluated as a function of the number of images, and the number of Zernike polynomial terms used to characterize the point spread function. I will compare the mean-square-error (MSE) performance of speckle imaging methods and a maximum-likelihood, multi-frame blind deconvolution (MFBD) method applied to long-path horizontal imaging scenarios. Both methods are used to reconstruct a scene from simulated imagery featuring anisoplanatic turbulence induced aberrations. This comparison is performed over three sets of 1000 simulated images each for low, moderate and severe turbulence-induced image degradation. The comparison shows that speckle-imaging techniques reduce the MSE 46 percent, 42 percent and 47 percent on average for low, moderate, and severe cases, respectively using 15 input frames under daytime conditions and moderate frame rates. Similarly, the MFBD method provides, 40 percent, 29 percent, and 36 percent improvements in MSE on average under the same conditions. The comparison is repeated under low light conditions (less than 100 photons per pixel) where improvements of 39 percent, 29 percent and 27 percent are available using speckle imaging methods and 25 input frames and 38 percent, 34 percent and 33 percent respectively for the MFBD method and 150 input frames. The MFBD estimator is applied to three sets of field data and the results presented. Finally, a combined Bispectrum-MFBD Hybrid estimator is proposed and investigated. This technique consistently provides a lower MSE and smaller variance in the estimate under all three simulated turbulence conditions.

Application of Signal Advance Technology to Electrophysiology

Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.

TDOA for Narrow-band Signal with Low Sampling Rate and Imperfect Synchronization

Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

Optimization of Schwinger pair production in colliding laser pulses

Recent studies of Schwinger pair production have demonstrated that the asymptotic particle spectrum is extremely sensitive to the applied field profile. We extend the idea of the dynamically assisted Schwinger effect from single pulse profiles to more realistic field configurations to be generated in an all-optical experiment searching for pair creation. We use the quantum kinetic approach to study the particle production and employ a multi-start method, combined with optimal control theory, to determine a set of parameters for which the particle yield in the forward direction in momentum space is maximized. We argue that this strategy can be used to enhance the signal of pair production on a given detector in an experimental setup.

Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques

This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

Improving Speech Interaction in Vehicles Using Context-Aware Information through A SCXML Framework

Speech Technologies can provide important benefits for the development of more usable and safe in-vehicle human-machine interactive systems (HMIs). However mainly due robustness issues, the use of spoken interaction can entail important distractions to the driver. In this challenging scenario, while speech technologies are evolving, further research is necessary to explore how they can be complemented with both other modalities (multimodality) and information from the increasing number of available sensors (context-awareness). The perceived quality of speech technologies can significantly be increased by implementing such policies, which simply try to make the best use of all the available resources; and the in vehicle scenario is an excellent test-bed for this kind of initiatives. In this contribution we propose an event-based HMI design framework which combines context modelling and multimodal interaction using a W3C XML language known as SCXML. SCXML provides a general process control mechanism that is being considered by W3C to improve both voice interaction (VoiceXML) and multimodal interaction (MMI). In our approach we try to anticipate and extend these initiatives presenting a flexible SCXML-based approach for the design of a wide range of multimodal context-aware HMI in-vehicle interfaces. The proposed framework for HMI design and specification has been implemented in an automotive OSGi service platform, and it is being used and tested in the Spanish research project MARTA for the development of several in-vehicle interactive applications.

Banco de medidas automático para linealización de amplificadores

This work is focused on building and configuring a measurement test bench for non linear High Power Amplifiers, more precisely those ones based on the Envelope Elimination and Restoration. At first sight the test bench is composed of several arbitrary waveform generators, an oscilloscope, a vector signal generator and a spectrum analyzer all of them controlled remotely. The test bench works automatically, that is why several software control programs have been developed in order to control all this equipment. The control programs have been developed in Matlab/Octave Scripting language and at last chance in a more low level language as C. The signal processing algorithms, taking into account that the time alignment one is the most important, have been developed in Matlab/Octave Scripting too. An improvement of 10dB in the ACPR(Adjacent Channel Power Ratio) has been obtained just by applying the time alignment algorithm developed in this work

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations