Dichteschätzung mit Wavelets

Es soll eine Dichtefunktion geschätzt werden unter der Modellannahme, dass diese in einer geeigneten Besovklasse liegt und kompakten Träger hat. Hierzu wird ein Waveletschätzer TW näher untersucht, der Thresholding-Methoden verwendet. Es wird die asymptotische Konvergenzgeschwindigkeit von TW für eine große Zahl von Beobachtungen angegeben und bewiesen. Schließlich werden in einem Überblick weitere Waveletschätzer diskutiert und mit TW verglichen. Es zeigt sich, dass TW in vielen Modellannahmen die optimale Konvergenzrate erreicht.

Gait analysis using a single wearable inertial measurement unit

Procedures for quantitative walking analysis include the assessment of body segment movements within defined gait cycles. Recently, methods to track human body motion using inertial measurement units have been suggested. It is not known if these techniques can be readily transferred to clinical measurement situations. This work investigates the aspects necessary for one inertial measurement unit mounted on the lower back to track orientation, and determine spatio-temporal features of gait outside the confines of a conventional gait laboratory. Apparent limitations of different inertial sensors can be overcome by fusing data using methods such as a Kalman filter. The benefits of optimizing such a filter for the type of motion are unknown. 3D accelerations and 3D angular velocities were collected for 18 healthy subjects while treadmill walking. Optimization of Kalman filter parameters improved pitch and roll angle estimates when compared to angles derived using stereophotogrammetry. A Weighted Fourier Linear Combiner method for estimating 3D orientation angles by constructing an analytical representation of angular velocities and allowing drift free integration is also presented. When tested this method provided accurate estimates of 3D orientation when compared to stereophotogrammetry. Methods to determine spatio-temporal features from lower trunk accelerations generally require knowledge of sensor alignment. A method was developed to estimate the instants of initial and final ground contact from accelerations measured by a waist mounted inertial device without rigorous alignment. A continuous wavelet transform method was used to filter and differentiate the signal and derive estimates of initial and final contact times. The technique was tested with data recorded for both healthy and pathologic (hemiplegia and Parkinson’s disease) subjects and validated using an instrumented mat. The results show that a single inertial measurement unit can assist whole body gait assessment however further investigation is required to understand altered gait timing in some pathological subjects.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Chemische Zusammensetzung der Aerosole : Design und Datenauswertung eines Einzelpartikel-Laserablationsmassenspektrometers

Atmosphärische Aerosolpartikel wirken in vielerlei Hinsicht auf die Menschen und die Umwelt ein. Eine genaue Charakterisierung der Partikel hilft deren Wirken zu verstehen und dessen Folgen einzuschätzen. Partikel können hinsichtlich ihrer Größe, ihrer Form und ihrer chemischen Zusammensetzung charakterisiert werden. Mit der Laserablationsmassenspektrometrie ist es möglich die Größe und die chemische Zusammensetzung einzelner Aerosolpartikel zu bestimmen. Im Rahmen dieser Arbeit wurde das SPLAT (Single Particle Laser Ablation Time-of-flight mass spectrometer) zur besseren Analyse insbesondere von atmosphärischen Aerosolpartikeln weiterentwickelt. Der Aerosoleinlass wurde dahingehend optimiert, einen möglichst weiten Partikelgrößenbereich (80 nm - 3 µm) in das SPLAT zu transferieren und zu einem feinen Strahl zu bündeln. Eine neue Beschreibung für die Beziehung der Partikelgröße zu ihrer Geschwindigkeit im Vakuum wurde gefunden. Die Justage des Einlasses wurde mithilfe von Schrittmotoren automatisiert. Die optische Detektion der Partikel wurde so verbessert, dass Partikel mit einer Größe < 100 nm erfasst werden können. Aufbauend auf der optischen Detektion und der automatischen Verkippung des Einlasses wurde eine neue Methode zur Charakterisierung des Partikelstrahls entwickelt. Die Steuerelektronik des SPLAT wurde verbessert, so dass die maximale Analysefrequenz nur durch den Ablationslaser begrenzt wird, der höchsten mit etwa 10 Hz ablatieren kann. Durch eine Optimierung des Vakuumsystems wurde der Ionenverlust im Massenspektrometer um den Faktor 4 verringert.rnrnNeben den hardwareseitigen Weiterentwicklungen des SPLAT bestand ein Großteil dieser Arbeit in der Konzipierung und Implementierung einer Softwarelösung zur Analyse der mit dem SPLAT gewonnenen Rohdaten. CRISP (Concise Retrieval of Information from Single Particles) ist ein auf IGOR PRO (Wavemetrics, USA) aufbauendes Softwarepaket, das die effiziente Auswertung der Einzelpartikel Rohdaten erlaubt. CRISP enthält einen neu entwickelten Algorithmus zur automatischen Massenkalibration jedes einzelnen Massenspektrums, inklusive der Unterdrückung von Rauschen und von Problemen mit Signalen die ein intensives Tailing aufweisen. CRISP stellt Methoden zur automatischen Klassifizierung der Partikel zur Verfügung. Implementiert sind k-means, fuzzy-c-means und eine Form der hierarchischen Einteilung auf Basis eines minimal aufspannenden Baumes. CRISP bietet die Möglichkeit die Daten vorzubehandeln, damit die automatische Einteilung der Partikel schneller abläuft und die Ergebnisse eine höhere Qualität aufweisen. Daneben kann CRISP auf einfache Art und Weise Partikel anhand vorgebener Kriterien sortieren. Die CRISP zugrundeliegende Daten- und Infrastruktur wurde in Hinblick auf Wartung und Erweiterbarkeit erstellt. rnrnIm Rahmen der Arbeit wurde das SPLAT in mehreren Kampagnen erfolgreich eingesetzt und die Fähigkeiten von CRISP konnten anhand der gewonnen Datensätze gezeigt werden.rnrnDas SPLAT ist nun in der Lage effizient im Feldeinsatz zur Charakterisierung des atmosphärischen Aerosols betrieben zu werden, während CRISP eine schnelle und gezielte Auswertung der Daten ermöglicht.

Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.

Tecniche di elaborazione di immagini radiografiche in odontoiatria

Il presente progetto di tesi è stato svolto in collaborazione con l’ufficio tecnico di Ricerca & Sviluppo dell’azienda Cefla Dentale, divisione MyRay (Imola - BO Italia). A seguito dell’esperienza maturata nel settore dei radiografici dentali, scelte aziendali hanno richiesto l’aggiornamento delle tecniche di elaborazione dell’immagine acquisita. Ogni prodotto commercializzato è fornito di un software predisposto alla gestione dei pazienti e alle operazioni di post-procesing tipiche: riduzione del rumore, aumento dei contrasti, della luminosità, misurazioni e tutti quelli presenti nei più comuni software di elaborazione grafica. Questi filtri digitali sono raccolti in una libreria sviluppata a seguito di una collaborazione esterna. Col presente elaborato viene effettuata una panoramica sulle tecniche di filtraggio utilizzate e vengono introdotte diverse proposte finalizzate alla riduzione del rumore. Test di valutazione qualitativa e quantitativa, su fantocci target, fantocci antropomorfi e set di immagini in-vivo, guideranno la scelta verso la proposta migliore, la quale verrà successivamente inserita all’interno della libreria e andrà ad aggiungersi ai filtri a disposizione dell’utente finale.

Geospatial analysis of western juniper (Juniperus occidentalis) encroachment utilizing remotely sensed data

Utilizing remote sensing methods to assess landscape-scale ecological change are rapidly becoming a dominant force in the natural sciences. Powerful and robust non-parametric statistical methods are also actively being developed to compliment the unique characteristics of remotely sensed data. The focus of this research is to utilize these powerful, robust remote sensing and statistical approaches to shed light on woody plant encroachment into native grasslands--a troubling ecological phenomenon occurring throughout the world. Specifically, this research investigates western juniper encroachment within the sage-steppe ecosystem of the western USA. Western juniper trees are native to the intermountain west and are ecologically important by means of providing structural diversity and habitat for many species. However, after nearly 150 years of post-European settlement changes to this threatened ecosystem, natural ecological processes such as fire regimes no longer limit the range of western juniper to rocky refugia and other areas protected from short fire return intervals that are historically common to the region. Consequently, sage-steppe communities with high juniper densities exhibit negative impacts, such as reduced structural diversity, degraded wildlife habitat and ultimately the loss of biodiversity. Much of today's sage-steppe ecosystem is transitioning to juniper woodlands. Additionally, the majority of western juniper woodlands have not reached their full potential in both range and density. The first section of this research investigates the biophysical drivers responsible for juniper expansion patterns observed in the sage-steppe ecosystem. The second section is a comprehensive accuracy assessment of classification methods used to identify juniper tree cover from multispectral 1 m spatial resolution aerial imagery.

Laser Doppler imaging for intraoperative human brain mapping

The identification and accurate location of centers of brain activity are vital both in neuro-surgery and brain research. This study aimed to provide a non-invasive, non-contact, accurate, rapid and user-friendly means of producing functional images intraoperatively. To this end a full field Laser Doppler imager was developed and integrated within the surgical microscope and perfusion images of the cortical surface were acquired during awake surgery whilst the patient performed a predetermined task. The regions of brain activity showed a clear signal (10-20% with respect to the baseline) related to the stimulation protocol which lead to intraoperative functional brain maps of strong statistical significance and which correlate well with the preoperative fMRI and intraoperative cortical electro-stimulation. These initial results achieved with a prototype device and wavelet based regressor analysis (the hemodynamic response function being derived from MRI applications) demonstrate the feasibility of LDI as an appropriate technique for intraoperative functional brain imaging.

Content Classification of Multimedia Documents using Partitions of Low-Level Features

Audio-visual documents obtained from German TV news are classified according to the IPTC topic categorization scheme. To this end usual text classification techniques are adapted to speech, video, and non-speech audio. For each of the three modalities word analogues are generated: sequences of syllables for speech, “video words” based on low level color features (color moments, color correlogram and color wavelet), and “audio words” based on low-level spectral features (spectral envelope and spectral flatness) for non-speech audio. Such audio and video words provide a means to represent the different modalities in a uniform way. The frequencies of the word analogues represent audio-visual documents: the standard bag-of-words approach. Support vector machines are used for supervised classification in a 1 vs. n setting. Classification based on speech outperforms all other single modalities. Combining speech with non-speech audio improves classification. Classification is further improved by supplementing speech and non-speech audio with video words. Optimal F-scores range between 62% and 94% corresponding to 50% - 84% above chance. The optimal combination of modalities depends on the category to be recognized. The construction of audio and video words from low-level features provide a good basis for the integration of speech, non-speech audio and video.

Tropical cyclone-related socio-economic losses in the western North Pacific region

The western North Pacific (WNP) is the area of the world most frequently affected by tropical cyclones (TCs). However, little is known about the socio-economic impacts of TCs in this region, probably because of the limited relevant loss data. Here, loss data from Munich RE's NatCatSERVICE database is used, a high-quality and widely consulted database of natural disasters. In the country-level loss normalisation technique we apply, the original loss data are normalised to present-day exposure levels by using the respective country's nominal gross domestic product at purchasing power parity as a proxy for wealth. The main focus of our study is on the question of whether the decadal-scale TC variability observed in the Northwest Pacific region in recent decades can be shown to manifest itself economically in an associated variability in losses. It is shown that since 1980 the frequency of TC-related loss events in the WNP exhibited, apart from seasonal and interannual variations, interdecadal variability with a period of about 22 yr – driven primarily by corresponding variations of Northwest Pacific TCs. Compared to the long-term mean, the number of loss events was found to be higher (lower) by 14% (9%) in the positive (negative) phase of the decadal-scale WNP TC frequency variability. This was identified for the period 1980–2008 by applying a wavelet analysis technique. It was also possible to demonstrate the same low-frequency variability in normalised direct economic losses from TCs in the WNP region. The identification of possible physical mechanisms responsible for the observed decadal-scale Northwest Pacific TC variability will be the subject of future research, even if suggestions have already been made in earlier studies.

Phytoplankton Scales of Variability in the California Current System: 1. Interannual and Cross-Shelf Variability

In the California Current System, strong mesoscale variability associated with eddies and meanders of the coastal jet play an important role in the biological productivity of the area. To assess the dominant timescales of variability, a wavelet analysis is applied to almost nine years (October 1997 to July 2006) of 1-km-resolution, 5-day-averaged, Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll a (chl a) concentration data. The dominant periods of chlorophyll variance, and how these change in time, are quantified as a function of distance offshore. The maximum variance in chlorophyll occurs with a period of similar to 100-200 days. A seasonal cycle in the timing of peak variance is revealed, with maxima in spring/summer close to shore (20 km) and in autumn/winter 200 km offshore. Interannual variability in the magnitude of chlorophyll variance shows maxima in 1999, 2001, 2002, and 2005. There is a very strong out-of-phase correspondence between the time series of chlorophyll variance and the Pacific Decadal Oscillation (PDO) index. We hypothesize that positive PDO conditions, which reflect weak winds and poor upwelling conditions, result in reduced mesoscale variability in the coastal region, and a subsequent decrease in chlorophyll variance. Although the chlorophyll variance responds to basin-scale forcing, chlorophyll biomass does not necessarily correspond to the phase of the PDO, suggesting that it is influenced more by local-scale processes. The mesoscale variability in the system may be as important as the chl a biomass in determining the potential productivity of higher trophic levels.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Variability of mesospheric water vapor above Bern in relation to the 27-day solar rotation cycle

Many studies investigated solar–terrestrial responses (thermal state, O₃ , OH, H₂O) with emphasis on the tropical upper atmosphere. In this paper the Focus is switched to water vapor in the mesosphere at a mid-latitudinal location. Eight years of water vapor profile measurements above Bern (46.88°N/7.46°E) are investigated to study oscillations with the Focus on periods between 10 and 50 days. Different spectral analyses revealed prominent features in the 27-day oscillation band, which are enhanced in the upper mesosphere (above 0.1 hPa, ∼64 km) during the rising sun spot activity of solar cycle 24. Local as well as zonal mean Aura MLS observations Support these results by showing a similar behavior. The relationship between mesospheric water and the solar Lyman-α flux is studied by comparing thesi-milarity of their temporal oscillations. The H₂O oscillation is negatively correlated to solar Lyman-α oscillation with a correlation coefficient of up to −0.3 to −0.4, and the Phase lag is 6–10 days at 0.04 hPa. The confidence level of the correlation is ≥99%. This finding supports the assumption that the 27-day oscillation in Lyman-α causes a periodical photo dissociation loss in mesospheric water. Wavelet power spectra, cross-wavelet transform and wavelet coherence analysis (WTC)complete our study. More periods of high common wavelet power of H₂O and solar Lyman-α are present when amplitudes of the Lyman-α flux increase. Since this is not a measure of physical correlation a more detailed view on WTC is necessary, where significant (two sigma level)correlations occur intermittently in the 27 and 13-day band with variable Phase lock behavior. Large Lyman-α oscillations appeared after the solar super storm in July 2012 and the H₂O oscillations show a well pronounced anticorrelation. The competition between advective transport and photo dissociation loss of mesospheric water vapor may explain the sometimes variable Phase relationship of mesospheric H₂O and solar Lyman-α oscillations. Generally, the WTC analysis indicates that solar variability causes observable photochemical and dynamical processes in the mid-latitude mesosphere.

Phytoplankton Scales of Variability in the California Current System: 2. Latitudinal Variability

The California Current System encompasses a southward flowing current which is perturbed by ubiquitous mesoscale variability. The extent to which latitudinal patterns of physical variability are reflected in the distribution of biological parameters is poorly known. To investigate the latitudinal distribution of chlorophyll variance, a wavelet analysis is applied to nearly 9 years (October 1997 to July 2006) of 1-km-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll concentration data at 5-day resolution. Peaks in the latitudinal distribution of chlorophyll variance coincide with features of the coastal topography. Maxima in variance are located offshore of Vancouver Island and downstream of Heceta Bank, Cape Blanco, Point Arena, and possibly Point Conception. An analysis of dominant wavelengths in the chlorophyll data reveals a transfer of energy into smaller scales is generated in the vicinity of the coastal capes. The latitudinal distribution of variance in sea level anomaly corresponds closely to the chlorophyll variance in the nearshore region (<100 km offshore), suggesting that the same processes determine the distribution of both. Farther offshore, there is no correspondence between latitudinal patterns of sea level anomaly and chlorophyll variance. This likely represents a transition from physical to biological control of the phytoplankton distribution.

An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^