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The objective of the thesis is to compare planned and realized fertility of a small sample of Czech women with finished fertility. A questionnaire was used to determine both planned and actual number of children, their gender, birth order and spacing and the age of woman at her first birth and her marital status. The realization of these events was compared and the reasons for failure were identified. A sample of 47 respondents anonymously completed the two-page questionnaire comprising of four parts -- plan, reality, personal characteristics and additional questions. Additional questions were related to contraception, abortions, religion, etc. The survey showed average number of 2.34 child per woman, whereas planned average number was 2.28. Further, on average 53 % of women fulfilled their plans regarding number of children, gender and order, spacing, age at the first birth and age at the first marriage. Finally, the correlation between observed number of children and planned number of children was analysed based on gathered data. The resulting model showed that the planned number of children one corresponds with realized number of children 1.47.

The purpose of this dissertation is to contribute to the closure of these aforementioned research gaps. Answering these calls, the following research objectives are proposed: 1. Understanding the main factors that have an influence on the capital structure decision of firms. 2. Understanding how the capital structure of firms differs among various industries and to fathom cross-sectional differences in the importance of debt determinants among industries. 3. Investigating the influence of time on the capital structure decision of firms. In specific, it must be found out whether certain debt determinants alter their effect on the capital structure decision of firms over time. 4. Studying the market-timing effect of debt financing. It must be researched how managers time the debt market when engaging in bond or loan issues. 5. Empirically proving how stylized factors and market-timing behaviour influences the transaction of equity, bond and loan issues as well as of share repurchases. 6. Finally, discussing how far the stylized facts can be explained by existing capital structure theory in order to crown the theory, whose notion can best account the observed financing patterns across the world.

Die vorliegende Doktorarbeit beschäftigt sich mit der experimentellen Studie zweier miteinander verbundener Phänomene: Dem intrinsischen Timing-Jitter in einem supraleitendenden Nanodraht-Einzelphotonen-Detektor (SNSPD) und der Relaxation der Elektronenenergie in supraleitenden Filmen. Supraleitende Nanodrähte auf einem dielektrischen Substrat als mikroskopische Grundbausteine jeglicher SNSPDs stellen sowohl für theoretische als auch für experimentelle Studien komplexe Objekte dar. Die Komplexität ergibt sich aus der Tatsache, dass SNSPDs in der Praxis stark ungeordnete und ultradünne supraleitende Filme verwenden, die eine akustische Fehlanpassung zu dem zugrundeliegenden Substrat aufweisen und einen Nichtgleichgewichts-Zustand implizieren. Die Arbeit untersucht die Komplexität des am weitesten in der SNSPD Technologie verbreiteten Materials, Niobnitrid (NbN), indem verschiedene experimentelle Methoden angewandt werden. Als eine mögliche Anwendung der SNSPD-Technologie wird ein Prototyp eines dispersiven Raman-Spektrometers mit Einzelphotonen-Sensitivität demonstriert. / This Ph.D. thesis is based on the experimental study of two mutually interconnected phenomena: intrinsic timing jitter in superconducting nanowire single-photon detectors (SNSPDs) and relaxation of the electron energy in superconducting films. Microscopically, a building element of any SNSPD device, a superconducting nanowire on top of a dielectric substrate, represents a complex object for both experimental and theoretical studies. The complexity arises because, in practice, the SNSPD utilizes strongly disordered and ultrathin superconducting films, which acoustically mismatch with the underlying substrate, and implies a non-equilibrium state. This thesis addresses the complexity of the most conventional superconducting material used in SNSPD technology, niobium nitride (NbN), by applying several distinct experimental techniques. As an emerging application of the SNSPD technology, we demonstrate a prototype of the dispersive Raman spectrometer with single-photon sensitivity.

No description available.

Spiking neural networks using Leaky-Integrate-and-Fire (LIF) neurons and Spike-timing-depend Plasticity (STDP) learning, are commonly used as more biological possible networks. Compare to DNNs and RNNs, the LIF-STDP networks are models which are closer to the biological cortex. LIF-STDP neurons use spikes to communicate with each other, and they learn through the correlation among these pre- and post-synaptic spikes. Simulation of such networks usually requires high-performance supercomputers which are almost all based on von Neumann architecture that separates storage and computation. In von Neumann architecture solutions, memory access is the bottleneck even for highly optimized Application-Specific Integrated Circuits (ASICs). In this thesis, we propose an optimization method that can reduce the memory access cost by avoiding a dual-access pattern. In LIF-STDP networks, the weights usually are stored in the form of a two-dimensional matrix. Pre- and post-synaptic spikes trigger row and column access correspondingly. But this dual-access pattern is very costly for DRAM. We eliminate the column access by introducing a post-synaptic buffer and an approximation function. The post-synaptic spikes are recorded in the buffer and are processed at pre-synaptic spikes together with the row updates. This column update elimination method will introduce errors due to the limited buffer size. In our error analysis, the experiments show that the probability of introducing intolerable errors can be bounded to a very small number with proper buffer size and approximation function. We also present a performance analysis of the Column Update Elimination (CUE) optimization. The error analysis of the column updates elimination method is the main contribution of our work. / Spikande neurala nätverk som använder LIF-neuroner och STDP-inlärning, används vanligtvis som ett mer biologiskt möjligt nätverk. Jämfört med DNN och RNN är LIF-STDP-nätverken modeller närmare den biologiska cortex. LIFSTDP-neuroner använder spikar för att kommunicera med varandra, och de lär sig genom korrelationen mellan dessa pre- och postsynaptiska spikar. Simulering av sådana nätverk kräver vanligtvis högpresterande superdatorer som nästan alla är baserade på von Neumann-arkitektur som separerar lagring och beräkning. I von Neumanns arkitekturlösningar är minnesåtkomst flaskhalsen även för högt optimerade Application-Specific Integrated Circuits (ASIC). I denna avhandling föreslår vi en optimeringsmetod som kan minska kostnaden för minnesåtkomst genom att undvika ett dubbelåtkomstmönster. I LIF-STDPnätverk lagras vikterna vanligtvis i form av en tvådimensionell matris. Preoch postsynaptiska toppar kommer att utlösa rad- och kolumnåtkomst på motsvarande sätt. Men detta mönster med dubbel åtkomst är mycket dyrt i DRAM. Vi eliminerar kolumnåtkomsten genom att införa en postsynaptisk buffert och en approximationsfunktion. De postsynaptiska topparna registreras i bufferten och bearbetas vid presynaptiska toppar tillsammans med raduppdateringarna. Denna metod för eliminering av kolumnuppdatering kommer att introducera fel på grund av den begränsade buffertstorleken. I vår felanalys visar experimenten att sannolikheten för att införa oacceptabla fel kan begränsas till ett mycket litet antal med korrekt buffertstorlek och approximationsfunktion. Vi presenterar också en prestandaanalys av CUE-optimeringen. Felanalysen av elimineringsmetoden för kolumnuppdateringar är det huvudsakliga bidraget från vårt arbete

Hebbian learning based neural network learning rules when implemented on hardware, store their synaptic weights in the form of a two-dimensional matrix. The storage of synaptic weights demands large memory bandwidth and storage. While memory units are optimized for only row-wise memory access, Hebbian learning rules, like the spike-timing dependent plasticity, demand both row and column-wise access of memory. This dual pattern of memory access accounts for the dominant cost in terms of latency as well as energy for realization of large scale spiking neural networks in hardware. In order to reduce the memory access cost in Hebbian learning rules, a Column Update Elimination optimization has been previously implemented, with great efficacy, on the Bayesian Confidence Propagation neural network, that faces a similar challenge of dual pattern memory access. This thesis explores the possibility of extending the column update elimination optimization to spike-timing dependent plasticity, by simulating the learning rule on a two layer network of leaky integrate-and-fire neurons on an image classification task. The spike times are recorded for each neuron in the network, to derive a suitable probability distribution function for spike rates per neuron. This is then used to derive an ideal postsynaptic spike history buffer size for the given algorithm. The associated memory access reductions are analysed based on data to assess feasibility of the optimization to the learning rule. / Hebbiansk inlärning baserat på neural nätverks inlärnings regler används vid implementering på hårdvara, de lagrar deras synaptiska vikter i form av en tvådimensionell matris. Lagringen av synaptiska vikter kräver stor bandbredds minne och lagring. Medan minnesenheter endast är optimerade för radvis minnesåtkomst. Hebbianska inlärnings regler kräver som spike-timing-beroende plasticitet, både rad- och kolumnvis åtkomst av minnet. Det dubbla mönstret av minnes åtkomsten står för den dominerande kostnaden i form av fördröjning såväl som energi för realiseringen av storskaliga spikande neurala nätverk i hårdvara. För att minska kostnaden för minnesåtkomst i hebbianska inlärnings regler har en Column Update Elimination-optimering tidigare implementerats, med god effektivitet på Bayesian Confidence Propagation neurala nätverket, som står inför en liknande utmaning med dubbel mönster minnesåtkomst. Denna avhandling undersöker möjligheten att utöka ColumnUpdate Elimination-optimeringen till spike-timing-beroende plasticitet. Detta genom att simulera inlärnings regeln på ett tvålagers nätverk av läckande integrera-och-avfyra neuroner på en bild klassificerings uppgift. Spike tiderna registreras för varje neuron i nätverket för att erhålla en lämplig sannolikhetsfördelning funktion för frekvensen av toppar per neuron. Detta används sedan för att erhålla en idealisk postsynaptisk spike historisk buffertstorlek för den angivna algoritmen. De associerade minnesåtkomst minskningarna analyseras baserat på data för att bedöma genomförbarheten av optimeringen av inlärnings regeln.

The aim of this dissertation is to shed light on how life can turn out for individuals with long term social assistance and afterwards when it has ceased. The primary objective of the dissertation is to study the changes that have occurred during the life course and the impact of those changes on the life course at large. A key question of this dissertation is the development of selfsufficiency and work-life patterns in a longitudinal perspective. The dissertation consists of a longitudinal study based on qualitative interviews with an interval of 20 years. The empirical data is composed of interviews with 11 recipients of social assistance – seven of which have been interviewed again in 2008/2009. A life course perspective is employed in the data analysis as a comprehensive approach and analytical tool. Other analytical approaches are related to the impact of the welfare state on the life course and to the term marginality. The situation of the interviewed group regarding self-sufficiency, employment and social conditions is viewed from a one-year perspective, a 20- year perspective and a life course perspective. The different time perspectives generated widely diverse pictures and nowledge. Not everyone worked at the point of the last interview but all were in a better social and economical position. No one remained on social assistance. One conclusion is that the notion of social problems being reinforced and exacerbated over time is simplistic. Another conclusion is that it appears that social assistance and social services have little importance from a life course perspective. A concluding result is that cross-sectional studies of individuals in a vulnerable situation are of limited value. A brief look at a person’s life does not say much of what the rest of his or her life will look like. Keywords: Life course, long term social assistance, social welfare services, human agency, timing, social integration, notions of social problems, welfare state, marginality.

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Sandia National Laboratories (SNL) currently achieves a bandwidth efficiency (h ) of 0.5 to 1.0 bps/Hz by using traditional modulation schemes, such as, BPSK and QFSK. SNL has an interest in increasing the present bandwidth efficiency by a factor of 4 or higher with the same allocated bandwidth (about 10 MHz). Simulations have shown that 32- QAM trellis-coded modulation (TCM) gives a good bit error rate (BER) performance, and meets the requirements as far as the bandwidth efficiency is concerned. Critical to achieving this is that the receiver be able to achieve timing synchronization. This paper examines a particular timing recovery algorithm for all-digital receivers. Timing synchronization in a digital receiver can be achieved in different ways. One way of achieving this is by interpolating the original sampled sequence to produce another sampled sequence synchronized to the symbol rate or a multiple of the symbol rate. An adaptive sampling conversion algorithm which performs this function was developed by Floyd Gardner in 1993. In the present work, his algorithm was applied to two different modulation schemes, BPSK and 4-ary PAM. The two schemes were simulated in the presence of AWGN and ISI along with Gardner’s algorithm for timing recovery, and a fractionally spaced equalizer (T/2 FSE) for equalization. Simulations show that the algorithm gives good BER performance for BPSK in all the situations, and at different sampling frequencies, but unfortunately poor performance for the 4-ary PAM scheme. This indicates that Gardner’s algorithm for sampling conversion is not suitable for multi-level signaling schemes.

Thesis (PhD (Electrical and Electronic Engineering))--University of Stellenbosch, 2009. / Although the Class D topology offers several advantages, its use in audio amplification has previously been limited by the lack of competitiveness in fidelity compared to its linear counterparts. During the past decade, technological advances in semiconductor technology have awakened new interest since competitive levels of distortion could now be achieved. The output stage of such an amplifier is the primary limiting factor in its performance. In this dissertation, four non-ideal effects existing in this stage are identified and mathematically analysed. The analytical analysis makes use of a well-established mathematical model, based on the double Fourier series method, to model the imperfections introduced into a naturally sampled pulsewidth modulated waveform. The analysis is complemented by simulation using a strategy based on Newton’s numerical method. The theory is verified by a comparison between the analytical-, simulated- and experimental results.