The Ultra-Wideband (UWB) channel is a dense multipath channel. The system performance and design complexity issues of selective-Rake receiver (SRake) are studied. Rake receiver has difficulties achieving desired system performance in the dense multipath environment. The main ideas of SRake receiver are to obtain the SNR level on known multipath channel and determine the desired number of Rake fingers. In the implementation of the SRake, the CLEAN algorithm is used in selecting the paths with relatively high energy. We can improve the performance of SRake receiver by increasing the accuracy of path selection. By the property of local maximum peak within the smaller partition, Two-Stage CLEAN algorithm acquires the more accurate delay time of multipath. In order to mitigate the sidelobe effect and noise interference, the key assumption in the Deng¡¦s Modified CLEAN algorithm is that using average amplitude around the considered data change as the criterion to determine if the data value is a true path. In this thesis, we investigate CLEAN, Two-Stage CLEAN and Deng¡¦s Modified CLEAN algorithm in three different systems including UWB-Impulse Radio, Pulse Radar and DS-UWB. From the performance comparison, it can be seen that the Two-Stage CLEAN algorithm that has the highest accuracy of path selection in UWB system.

In this thesis study, joint frequency offset and channel estimation methods for single-input single-output (SISO) systems are examined. The performance of maximum likelihood estimate of the parameters are studied for different training sequences. Conventionally training sequences are designed solely for the channel estimation purpose. We present a numerical comparison of different training sequences for the joint estimation problem. The performance comparisons are made in terms of mean square estimation error (MSE) versus SNR and MSE versus the total training energy metrics. A novel estimation scheme using complementary sequences have been proposed and compared with existing schemes. The proposed scheme presents a lower estimation error than the others in almost all numerical simulations. The thesis also includes an extension for the joint channel-frequency offset estimation problem to the multi-input multi-output systems and a brief discussion for multiple frequency offset case is also given.

The main purpose of the study was to explore how learning cycle and traditional method as teaching methods contribute to the effect of contextual approach on 11th grade students&rsquo / achievement in &ldquo / impulse and momentum&rdquo / , and attitude towards physics. Therefore, a distinction between teaching approach (contextual vs. non-contextual) and teaching method (learning cycle vs. traditional method) was made and they were used as independent variables. Students&rsquo / gender was also used as an independent variable. Thus, the study was a 2x2x2 factorial design. The sample, drawn through the purposive sampling, included 226 students. Pretests and posttests were used for assessing students&rsquo / achievement in impulse and momentum, and attitude towards physics. Using Multivariate Analysis of Covariance (MANCOVA), the main effects of contextual approach, learning cycle, and student gender as well as the interaction effects among them were investigated. Consequently, (1) contextual approach was more effective in supporting students&rsquo / conceptual understanding of impulse and momentum, (2) learning cycle was as effective as the traditional method, (3) gender related difference in attitude towards physics in favor of males could not be removed through the treatments, (4) contextual approach worked better with the traditional method than the learning cycle for achievement and attitude, (5) males benefitted a little more from learning cycle while females benefitted a little more from traditional method in terms of conceptual and non-conceptual scores.

Traditional naval vessels with steel structures have the benefit of large safety factors and a distinct material endurance limit. However, as performance requirements and budget constraints rise, the demand for lighter weight vessels increases. Reducing the mass of vessels is commonly achieved by the use of aluminum or composite structures, which requires closer attention to be paid to crack initiation and propagation. It is rarely feasible to require a lengthy inspection process that removes the vessel from service for an extended amount of time. Structural health monitoring (SHM), involving continuous measurement of the structural response to an energy source, has been proposed as a step towards condition-based maintenance. Furthermore, using a passive monitoring system with an array of sensors has several advantages: monitoring can take place in real-time using only ambient noise vibrations and neither deployment of an active source nor visual access to the inspected areas are required. Passive SHM on a naval vessel is not without challenge. The structures of ships are typically geometrically complex, causing scattering, multiple reflections, and mode conversion of the propagating waves in the vessel. And rather than a distinct and predictable input produced by controlled active sources, the vibration sources are hull impacts, smaller waves, and even onboard machinery and activity. This research summarizes findings from data collected onboard a Navy vessel and presents recommendations data processing techniques. The intent is to present a robust method of passive structural health monitoring for such a vessel using only ambient vibrations recordings.

Vibration control requires high dynamic stiffness in mechanical structures for a reliable performance under extreme conditions. Dynamic stiffness composes the parameters of stiffness (K) and damping (η) that are usually in a trade-off relationship. This thesis study aims to break the trade-off relationship. After identifying the underlying mechanism of damping in composite materials and joint interfaces, this thesis studies the deposition technique and physical characteristics of nano-structured HDS (high dynamic stiffness) composite thick-layer coatings. The HDS composite were created by enlarging the internal grain boundary surface area through reduced grain size in nano scale (≤ 40 nm). The deposition process utilizes a PECVD (Plasma Enhanced Chemical Vapour Deposition) method combined with the HiPIMS (High Power Impulse Magnetron Sputtering) technology. The HDS composite exhibited significantly higher surface hardness and higher elastic modulus compared to Poly(methyl methacrylate) (PMMA), yet similar damping property. The HDS composites successfully realized vibration control of cutting tools while applied in their clamping interfaces. Compression preload at essential joint interfaces was found to play a major role in stability of cutting processes and a method was provided for characterizing joint interface properties directly on assembled structures. The detailed analysis of a build-up structure showed that the vibrational mode energy is shifted by varying the joint interface’s compression preload. In a build-up structure, the location shift of vibration mode’s strain energy affects the dynamic responses together with the stiffness and damping properties of joint interfaces. The thesis demonstrates that it is possible to achieve high stiffness and high damping simultaneously in materials and structures. Analysis of the vibrational strain energy distribution was found essential for the success of vibration control.

In der vorliegenden Studie wurde mittels der Bildgebung des funktionellen MRT die Dynamik der neuronalen Hirnmechanismen untersucht, die es dem Menschen erlauben, durch kurzfristigen Verzicht auf Belohnungen seinen Verhaltenserfolg langfristig zu optimieren. Durch den Vergleich zweier Extremgruppen gesunder Probanden (hoch- versus niedrig- impulsive Probanden) sollte ein möglicher Zusammenhang zwischen der Impulsivität und dem funktionellen Zusammenspiel frontostriataler Regelkreise während des aktiven Prozesses der Entscheidungsfindung dargestellt werden. Die vorliegende Studie hat gezeigt, dass gesunde, nicht- klinische Individuen, die sich selbst mittels der Barratt- Impulsivitätsskala als hoch- impulsiv charakterisiert haben, ihr Verlangen nach einer direkten Belohnung erfolgreich durch Aktivierung zweier komplementärer Hirnmechanismen kontrollieren können. Als erster Mechanismus ist festzuhalten, dass selbstkontrollierte Entscheidungen zu einer Abschwächung der belohnungsabhängigen Aktivierung im Nucleus accumbens führten, welche von einer ansteigenden inversen Verbindung mit dem anteroventralen präfrontalen Kortex begleitet wurde. Der zweite Mechanismus ist, dass HI- Probanden ihren Wunsch nach einer höherwertigen, aber suboptimalen Belohnung in Abhängigkeit von der Wertigkeit der unmittelbaren Belohnung durch Downregulation im ventromedialen präfrontalen Kortex kontrollierten. Diesem Mechanismus folgte eine ansteigende inverse Kopplung mit dem ventralen Striatum. Von entscheidender Bedeutung ist dabei, dass sich diese neuronalen Mechanismen qualitativ von denen der extrem- kontrollierten Probanden unterschieden. Insgesamt lässt sich sagen, dass diese Ergebnisse darauf hindeuten, dass es persönlichkeitsspezifische neuronale Mechanismen gibt, die es hoch-impulsiven Probanden ermöglichen, ihren Wunsch nach einer unmittelbaren Belohnung zu kontrollieren.

No description available.

Untersuchung zur Wirkung von intranasal verabreichtem Xylometazolin bei brachy- und normozephalen Hunden: Impuls-Oszillometrie und akustische Rhinometrie P. Franco, J. P. Hueber, G. U. Oechtering Klinik für Kleintiere, Arbeitsgruppe Brachyzephalie, Universität Leipzig Einleitung: Die zuchtbedingte Verkürzung des Gesichtsschädels brachy - zephaler Hunderassen hat zu einer Reihe klinisch relevanter morphologischer und physiologischer Veränderungen geführt. Hierzu zählen stenotische Naseneingänge, eine durch fehlgebildete Conchen obstruierte Nasenhöhle sowie ein verdicktes und verlängertes Gaumensegel. Diese Einengung der oberen Atemwege führt zu Atemnot und ausgeprägter Belastungsintoleranz, was als Brachyzephales Atemnotsyndrom (BAS) bezeichnet wird. Xylometazolin ist ein für den Menschen zugelassenes Alpha-Sympathomime - tikum. Topische und systemische Sympathomimetika werden beim Menschen zur Behandlung nasaler Kongestionen zum Abschwellen der Nasenschleimhaut eingesetzt. Zielstellung: Ausgehend von der Hypothese, dass Xylometazolin auch bei Hunden zu einem Abschwellen der Nasenschleimhaut führt und dass die Morphologie der Nasenmuscheln sich zwischen den zwei Zielgruppen unterscheidet, sollte der intranasale Strömungswiderstand bei brachy- und normozephalen Hunden vor und nach Xylometazolingabe mit Impuls- Oszillometrie untersucht werden. Zusätzlich wurden in der Beaglegruppe mit akustischer Rhinometrie das Nasenhöhlenvolumen und die minimale Querschnittsfläche bestimmt. Methodik: Die Messungen erfolgten nach dem Prinzip der Impuls-Oszillometrie (IOS) und akustischer Rhinometrie. In einer prospektiven klini - schen Studie wurden 10 brachyzephale Hunde (5 Möpse, 5 Französische Bulldoggen) und 6 Beagles untersucht. Bei den anästhesierten, spontan atmenden Tieren wurde der intranasale Strömungswiderstand mit Impuls- Oszillometrie unmittelbar vor und 30 Minuten nach intranasal verabreichtem Xylometazolin gemessen. Messungen mit akustischer Rhinometrie erfolgten zusätzlich vor und nach Xylometazolingabe. Bei allen Tieren wurden die oberen Atemwege endoskopisch und computertomographisch untersucht. Ergebnisse: Der aus drei Messungen gemittelte intranasale Strömungswiderstand bei Patienten mit BAS betrug vor Xylometazolingabe 0,87 ± 0,097 kPa/(L/s). Nach Xylometazolingabe reduzierte sich der intranasale Strömungswiderstand um etwa 48% auf 0,42 ± 0,55 kPa/(L/s). Vergleich - bare Ergebnisse ermittelten wir in der Beaglegruppe. Nach Xylometazolingabe ergab sich bei den Beagles eine Zunahme des Nasenvolumens und der minimalen Querschnittsfläche. Schlussfolgerungen: Wir konnten erstmals zeigen, dass Xylometazolin auch bei Hunden zum Abschwellen der Nasenschleimhaut führt und sich das Abschwellverhalten zwischen brachy- und normozephalen Hunden kaum voneinander unterscheidet. A13 Abstracts 18. Jahrestagung der DVG-FG InnLab © Schattauer 2010 Tierärztliche Praxis Kleintiere 1/2010

System identification finds nowadays application in various areas of biological research as a tool of empiric mathematical modeling and model individualization. A fundamental challenge of system identification in biology awaits in the form of response variability. Furthermore, biological systems tend to exhibit high degree of nonlinearity as well as significant time delays. This thesis covers system identification approaches developed for the applications within two particular biomedical fields: neuroscience and endocrinology. The first topic of the thesis is parameter estimation of the classical Elementary Motion Detector (EMD) model in insect vision. There are two important aspects to be taken care of in the identification approach, namely the nonlinear dynamics of the individual EMD and the spatially distributed structure of multiple detectors producing a measurable neural response. Hence, the suggested identification method is comprised of two consecutive stages addressing each of the above aspects. Furthermore, visual stimulus design for high spatial excitation order has been investigated. The second topic is parameter estimation of mathematical model for testosterone regulation in the human male. The main challenges of this application are in the unavailability of input signal measurements and the presence of an unknown pulsatile feedback in the system resulting in a highly nonlinear closed-loop dynamics. Semi-blind identification method has been developed based on a recently proposed pulse-modulated model of pulsatile endocrine regulation. The two system identification problems treated in the thesis bear some resemblance in the sense that both involve measured signals that can be seen as square-integrable functions of time. This property is handled by transforming the signals into the Laguerre domain, i.e. by equivalently representing the functions with their infinite Laguerre series.

Ultra-wideband (UWB) technology is the next viable solution for applications in wireless personal area network (WPAN), body area network (BAN) and wireless sensor network (WSN). However, as application evolves toward a more realistic situation, wideband channel characteristics such as pulse distortion must be accounted for in channel modeling. Furthermore, application-oriented services such as ranging and localization demand fast prototyping, real-time processing of measured data, and good low signal-to-noise ratio (SNR) performance. Despite the tremendous effort being vested in devising new receivers by the global research community, channel-estimating Rake receiver is still one of the most promising receivers that can offer superior performance to the suboptimal counterparts. However, acquiring Nyquist-rate samples costs substantial power and resource consumption and is a major obstacle to the feasible implementation of the asymptotic maximum likelihood (ML) channel estimator. In this thesis, we address all three aspects of the UWB impulse radio (UWB-IR), in three separate contributions. First, we study the {\it a priori} dependency of the CLEAN deconvolution with real-world measurements, and propose a high-resolution, multi-template deconvolution algorithm to enhance the channel estimation accuracy. This algorithm is shown to supersede its predecessors in terms of accuracy, energy capture and computational speed. Secondly, we propose a {\it regularized} least squares time-of-arrival (ToA) estimator with wavelet denoising to the problem of ranging and localization with UWB-IR. We devise a threshold selection framework based on the Neyman-Pearson (NP) criterion, and show the robustness of our algorithm by comparing with other ToA algorithms in both computer simulation and ranging measurements when advanced digital signal processing (DSP) is available. Finally, we propose a low-complexity ML (LC-ML) channel estimator to fully exploit the multipath diversity with Rake receiver with sub-Nyquist rate sampling. We derive the Cram\'er-Rao Lower Bound (CRLB) for the LC-ML, and perform simulation to compare our estimator with both the $\ell_1$-norm minimization technique and the conventional ML estimator.