Aktuelle Affektforschung betont die Bedeutung mikrolängsschnittlicher Daten für das Verstehen täglichen affektiven Funktionierens, da sie es erlauben affektive Dynamiken und potentiell zugrunde liegende Prozesse zu beschreiben. Dynamische Längsschnittmodelle werden entsprechend attraktiver. In dieser Dissertation komme ich Forderungen nach einer Integration kontextueller Informationen in die Untersuchung täglichen affektiven Funktionierens nach. Speziell modifiziere ich populäre dynamische Modelle so, dass sie kontextuelle Variationen einbeziehen. In einem ersten Beitrag werden Personen als in Kontexte eingebettet begriffen. Der vorgeschlagene Ansatz der festen moderierten Zeitreihenanalyse berücksichtigt systemische Reaktionen auf kontextuelle Veränderungen, indem Veränderungen in allen Parametern eines dynamischen Zeitreihenmodells auf kontextuelle Veränderungen bedingt schätzt werden. Kontextuelle Veränderungen werden als bekannt und assoziierte Parameterveränderungen als deterministisch behandelt. Folglich sind Modellspezifikation und -schätzung erleichtert und in kleineren Stichproben praktikabel. Es sind allerdings Informationen über den Einfluss kontextueller Faktoren erforderlich. Anwendbar auf einzelne Personen erlaubt der Ansatz die uneingeschränkte Exploration interindividueller Unterschiede in kontextualisierten affektiven Dynamiken. In einem zweiten Beitrag werden Personen als mit Kontexten interagierend begriffen. Ich implementiere eine Prozessperspektive auf kontextuelle Schwankungen, die die Dynamiken täglicher Ereignisse über autoregressive Modelle mit Poisson Messfehler abbildet. Die Kombination von Poisson und Gaußscher autoregressiver Modellierung erlaubt eine Formalisierung des dynamischen Zusammenspiels kontextueller und affektiver Prozesse. Die Modelle sind hierarchisch aufgesetzt und erfassen so interindividuelle Unterschiede in intraindividuellen Dynamiken. Die Schätzung erfolgt über simulationsbasierte Verfahren der Bayesschen Statistik. / Recent affect research stresses the importance of micro-longitudinal data for understanding daily affective functioning, as they allow describing affective dynamics and potentially underlying processes. Accordingly, dynamic longitudinal models get increasingly promoted. In this dissertation, I address calls for an integration of contextual information into the study of daily affective functioning. Specifically, I modify popular dynamic models so that they incorporate contextual changes. In a first contribution, individuals are characterized as embedded in contexts. The proposed approach of fixed moderated time series analysis accounts for systemic reactions to contextual changes by estimating change in all parameters of a dynamic time series model conditional on contextual changes. It thus treats contextual changes as known and related parameter changes as deterministic. Consequently, model specification and estimation are facilitated and feasible in smaller samples, but information on which and how contextual factors matter is required. Applicable to single individuals, the approach permits an unconstrained exploration of inter-individual differences in contextualized affective dynamics. In a second contribution, individuals are characterized as interacting reciprocally with contexts. Implementing a process perspective on contextual changes, I model the dynamics of daily events using autoregressive models with Poisson measurement error. Combining Poisson and Gaussian autoregressive models can formalize the dynamic interplay between contextual and affective processes. It thereby distinguishes not only unique from joint dynamics, but also affective reactivity from situation selection, evocation, or anticipation. The models are set up as hierarchical to capture inter-individual differences in intra-individual dynamics. Estimation is carried out via simulation-based techniques in the Bayesian framework.

Diese Dissertation umfasst sowohl einen theoretisches als auch einen empirischen Beitrag zur Analyse der Messung der gesamten Faktorproduktivität (TFP). Das erste Kapitel inspiziert die bestehende Literatur über die häufigsten Techniken der TFP Messung und gibt einen Überblick über deren Limitierung. Das zweite Kapitel betrachtet Daten, die durch ein Real Business Cycle Modell generiert wurden und untersucht das quantifizierbare Ausmaß von Messfehlern des Solow Residuums als ein Maß für TFP Wachstum, wenn der Kapitalstock fehlerhaft gemessen wird und wenn Kapazitätsauslastung und Abschreibungen endogen sind. Das dritte Kapitel schlägt eine neue Methodologie in einem bayesianischen Zusammenhang vor, die auf Zustands- Raum-Modellen basiert. Das vierte Kapitel führt einen neuen Ansatz zur Bestimmung möglicher Spill-over Effekte auf Grund neuer Technologien auf die Produktivität ein und kombiniert eine kontrafaktische Zerlegung, die von den Hauptannahmen des Malquist Indexes abgeleitet wird mit ökonometrischen Methoden, die auf Machado and Mata (2005) zurückgehen. / This dissertation consists of theoretical and empirical contributions to the study on Total Factor Productivity (TFP) measurement. The first chapter surveys the literature on the most used techniques in measuring TFP and surveys the limits of these frameworks. The second chapter considers data generated from a Real Business Cycle model and studies the quantitative extent of measurement error for the Solow residual as a measure of TFP growth when the capital stock is measured with error and when capacity utilization and depreciation are endogenous. Furthermore, it proposes two alternative measurements of TFP growth which do not require capital stocks. The third chapter proposes a new methodology based on State-space models in a Bayesian framework. Applying the Kalman Filter to artificial data, it proposes a computation of the initial condition for productivity growth based on the properties of the Malmquist index. The fourth chapter introduces a new approach for identifying possible spillovers emanating from new technologies on productivity combining a counterfactual decomposition derived from the main properties of the Malmquist index and the econometric technique introduced by Machado and Mata (2005).

The diplomma thesis is dealing with possibilities of Signal to noise ratio measurement by method, which is based on direct measurement. It is chosen the most suitable method – signal and noise separation to two different parallel signal branches, where is measured signal strength in one branch and root mean square value in the other. The thesis is consisted of a concept of detail block scheme of Signal to noise ratio meter, which was designed in terms of theoretical knowledge. Particular functional blocks were circuit-designed, the active and passive parts were chosen and their function were described. There were made simulation and displayed input and output time flows. There is designed the whole connection of engineered Signal to noise ratio meter in the last part of my thesis. The double-sided board of printed circuit is contained too. It was created simple programme for supervisor micro-processor. Thereby were constructed complete bases for realization.

Ultraprecision single point diamond turning is required to produce parts with sub-nanometer surface roughness and sub-micrometer surface profiles tolerances. These parts have applications in the optics industry, where tight form accuracy is required while achieving high surface finish quality. Generally, parts can be polished to achieve the desired finish, but then the form accuracy can easily be lost in the process rendering the part unusable. Currently, most mid to low spatial frequency surface finish errors are inspected offline. This is done by physically removing the workpiece from the machining fixture and mounting the part in a laser interferometer. This action introduces errors in itself through minute differences in the support conditions of the over constrained part on a machine as compared to the mounting conditions used for part measurement. Once removed, the fixture induced stresses and the part’s internal residual stresses relax and change the shape of the generally thin parts machined in these applications. Thereby, the offline inspection provides an erroneous description of the performance of the machine. This research explores the use of a single, high resolution, capacitance sensor to quickly and qualitatively measure the low to mid spatial frequencies on the workpiece surface, while it is mounted in a fixture on a standard ultraprecision single point diamond turning machine after a standard facing operation. Following initial testing, a strong qualitative correlation exists between the surface profiling on a standard offline system and this online measuring system. Despite environmental effects and the effects of the machine on the measurement system, the capacitive system with some modifications and awareness of its measurement method is a viable option for measuring mid to low spatial frequencies on a workpiece surface mounted on an ultraprecision machine with a resolution of 1nm with an error band of ±5nm with a 20kHz bandwidth. / Thesis / Master of Applied Science (MASc)