For this study an attempt was made to bridge the disciplines of linguistics and composition in order to examine factors contributing to textual coherence. Pairs of descriptive texts written by fifty college students were examined in order to identify the factors which differentiate quality and topic. Students were asked to compose a descriptive paragraph on the topic of fall. They were then encouraged to use their five senses, given leaves, and asked to compose a paragraph describing the leaves. The pairs of texts thus elicited were evaluated for preference by readers. The ANOVA revealed a significant difference (p=.001) between the two topics with fall texts preferred over the more specific leaves texts. Results suggest that encouraging students to use their five senses does not improve their writing. It may be more important to move through various levels of abstraction than to merely focus on sensory detail. The texts were also scored holistically by two trained evaluators. Results of this grading were used to choose five high- and five low-coherence texts on each of the two topics. These 20 texts were then analyzed in terms of the tagmemic referential hierarchy. A MANOVA was done to examine the dependent variables of Slot (location in time or space), Role (purpose or reason), and Cohesion (sociocultural context) in relation to quality and topic for these texts. Slot was found to be significant for both quality (p=.025) and topic (p=.004). Role was significant only for quality (p=.001). Cohesion was nonsignificant for either quality or topic. These results suggest that students should: (a) be encouraged to locate their texts in time and space in order to develop an adequate context for readers; (b) be encouraged to include purposes and reasons for the statements they make; and (c) be encouraged, where appropriate, to include a focus on humans and their activities (either literal or figurative) since such reference is a distinguishing feature of high-coherence texts.

Wastewater Treatment Plants (WWTPs) are sophisticated systems that have to sustain long-term qualified performance, regardless of temporally volatile volumes or compositions of the incoming wastewater. Membrane filtration in the Membrane Bioreactors (MBRs) reduces the WWTPs footprint and produces effluents of proper quality. The energy or electric power consumption of the WWTPs, mainly from aeration equipment and pumping, is directly linked to greenhouse gas emission and economic input. Biological treatment requires oxygen from aeration to perform aerobic decomposition of aquatic pollutants, while pumping consumes energy to overcome friction in the channels, piping systems, and membrane filtration. In this thesis, we researched full-scale WWTPs Influent Conditions (ICs) monitoring and forecasting models to facilitate the energy consumption budgeting and raise early alarms when facing latent abnormal events. Accurate and efficient forecasts of ICs could avoid unexpected system disruption, maintain steady product quality, support efficient downstream processes, improve reliability and save energy. We carried out a numerical study of bioreactor microbial ecology for MBRs microbial communities to identify indicator species and typical working conditions that would assist in reactor status confirmation and support energy consumption budgeting. To quantify membrane fouling and cleaning effects at various scales, we proposed quantitative methods based on Matern covariances to analyze biofouling layer thickness and roughness obtained from Optical Coherence Tomography (OCT) images taken from gravitydriven MBRs under various working conditions. Such methods would support practitioners to design suitable data-driven process operation or replacement cycles and lead to quantified WWTPs monitoring and energy saving. For future research, we would investigate data from other full-scale water or wastewater treatment process with higher sampling frequency and apply kernel machine learning techniques for process global monitoring. The forecasting models would be incorporated into optimization scenarios to support data-driven decision-making. Samples from more MBRs would be considered to gather information of microbial community structures and corresponding oxygen-energy consumption in various working conditions. We would investigate the relationship between pressure drop and spatial roughness measures. Anisotropic Matern covariance related metrics would be adopted to quantify the directional effects under various operation and cleaning working conditions.

Flera modeller och skalor har gjorts genom psykologins historia för att bättreförstå och reflektera kring individens hälsa och dennes perception av den.Studiens syfte var att undersöka samband mellan femfaktorsmodellen,KASAM samt generell mental hälsa med bakgrundsvariablerna kön, ålderoch civilstatus. Totalt 86 högskolestudenter från mellersta Sverige deltog istudien genom att fylla i en enkät innehållande GHQ-12 skala, Shafer’sfemfaktorsskala och Antonovskys KASAM skala. Resultaten visade inget samband mellan generell mental hälsa och de valda bakgrundsvariablerna;negativt samband mellan psykisk ohälsa och KASAM; negativt sambandmellan mental ohälsa och extraversion, positivt samband mellan generellmental ohälsa och neuroticism, inget samband mellan mental hälsa och andrapersonlighetsegenskaper. Totalt kunde 47 % av variationen i generell mentalhälsa förklaras av samtliga prediktorvariablerna. Svagheten med studien varbl.a. urval och andel deltagare samt förståelse av modellerna. Vidarediskuteras resultaten i jämförelse med andra relevanta studier.

This thesis deals mainly with perfusion modeling in optical coherence tomography (OCT). The introductory part deals with basic theory of the OCT, including a description of its basic applications. Part of the work was the testing of selected contrasting materials suitable for the OCT and the design and implementation of phantoms, which were subsequently used in the main part of the thesis. In the practical part, attention is paid to the perfusion analysis in the OCT, first the application of the dilution theory in the OCT for flow estimation, then a study testing the basic theory of perfusion on OCT by means of tissue phantom. Another part of the thesis is devoted to the method of speckle variance analysis for flow visualization.

The aim of this diploma thesis was to get familiar with methods to generate surrogates and how to apply them on cardiovascular signals. The first part of this diploma thesis describes the basic theory of baroreflex function and methods to generate surrogate data. Surrogate data were generated from data, acquired from the database, by using three different methods. In the next part of this diploma thesis, coherence significance between blood pressure and heart intervals was calculated by using surrogates. In the end two hypotheses were defined and tested by which it was detected whether the orthostatic change of the measurement position has effect on the causal coherence change and baroreflex function.

This master’s thesis deals with signal evaluation using Fourier transform. In the theoretical section, different methods of signal analysis with an emphasis on a Fast Fourier Transform are described. Theoretical section also contains description of common machinery faults and their diagnosis using frequency spectrum analysis. In the practical section, an algorithm for signal evaluation with an emphasis on coherence condition was designed in the Matlab environment. This algorithm was later used to evaluate submitted signals.

This work describes optical coherence tomography, it's principle and methods for automatic segmentation intra-retinal layers in OCT images . There is proposed algorithm for boundary detection of two intra retinal layers, RFNL and RPE layer based on thresholding and second algorithm for detection of seven layers, which is based on graph search algorithm. In summary is compared accuracy against manualy segmented layers and there is also proposed solution for problematic parts.

This diploma thesis deals with uncertainties of interferometric measurements and methods for their evaluation. In the theoretical part of the thesis, are described interferometers and interferometric measurement techniques. Furthermore, there is presented process of determining the measurement uncertainty using methods GUM and Monte Carlo. In the practical part of the thesis, there are these two methods are used for qualification of measurement uncertainty calculated for the specific interferometer.

The diploma thesis deals with the construction design of reflective type of holographic microscope together with the proposal for the mechanical imposition of optical elements. Thesis contains parts where the illumination beam tracing through the optical system is calculated and discussed, followed up with the accuracy requirements for rectification mechanisms and their design. The three-dimensional model of modularly solved microscope is presented in conclusion of this thesis together with selected microscope sub-assemblies.

Reflected-light digital holographic microscope developed at IPE FME BUT uses off-axis holography principle and low spatial and temporal coherence illumination. Microscope allows reconstruction of the image amplitude and the image phase, which can be handled in real time. The only limiting factors are imaging speed of the detector and computer performance when processing holograms. Reconstruction of image phase and amplitude allows high-resolution profilometric measurements in the vertical axis direction. This thesis deals with the automatization of profilometric measurement method proposed in [2]. Proposed method uses the combination of the image phase and the image amplitude for the measurement of specimens with surface structure the vertical size of which cause the uncertainty of the image phase by a factor of 2pí. Futher the thesis deals with the construction design of the illumination system of the microscope and its realization together with experimental verification of functionality of proposed method automatization.