In the textile industry it is important to know features of different fabrics. A number of experiments, which analyze the features of fabrics, are performed in Kaunas University of Technology. First of them is investigation of textile fabric buckling parameters using buckling wave test method. Three different plain weave fabrics treated with different concentrations of PVA (polyvinyl acetate) stiffener were chosen as a research objects. There were two factors, which outlined the behavior of the textile buckling. These were buckling wave’s height and the area under it. The buckling wave can be outlined as projections of the fabric in the vertical direction. During experiment, the samples of textile were cut out in three directions: longitudinal, transverse and 45º bias direction. Function of wave area changes increasing the in-plain deformation has the same expression in all three cutting directions. It is determined that the wave’s area function depends on two variables. The bending behavior of fabrics is an important topic in scientific textile research as well as in industrial applications. The TH 7 bending meter provides a measure of force required to bend the fabric sample in different angles. The obtained force-angle relationship shows nonlinear behavior. The TH 7 tester was developed in Czech Republic as an alternative method to KES (Kawabata Evaluation System) bending meter that is the most frequently encountered and cited test used to determine the bending... [to full text]

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In several field studies it was concluded that highly transmissive features transmit the majority of solute mass in horizontally-fractured bedrock aquifers. The purpose of this investigation is to develop a new technique for determining the location and relative role of hydraulically connected fracture features with respect to solute transport. To explore this, a radial-divergent tracer experiment was conducted in a four-borehole array completed through a horizontally-fractured dolomite of Silurian age in Smithville, Ontario, Canada. The injection interval included several hydraulically-identified features located in the Upper Eramosa member of the Lockport formation. 496 L of Lissamine FF (a conservative fluorescent dye tracer at a concentration of 200 mg/L) was injected at a rate of 23.25 L/min +/- 1 %. The arrival of fluorescent tracer was detected in a series of open monitoring wells located in a down gradient direction using a submersible fluorometer equipped with a pressure transducer. Correlating the fluorescence signals at depth with hydraulically-identified features provided an in-situ measure that identified the vertical intersection and relative role of each feature with respect to mass transport. FRAC3DVS a discrete fracture finite element model was used to simulate the tracer experiment. Based on the results of the tracer experiment and numerical simulations, it is concluded that the highly transmissive features identified using hydraulic techniques do not always carry all of the mass in transport. The majority of mass transport, however, followed at least one of the largest features in every borehole, just not every large feature. Results of this experiment suggest it is imperative that a distinction between large fracture features that transmit and do not transmit mass be made. / Thesis (Master, Civil Engineering) -- Queen's University, 2008-07-14 21:22:05.427

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In 2003, Pomeroy et al. published a research study that described a gene expression based prediction of central nervous system embryonal tumour (CNS) outcome. Over a half of decade, many models and approaches have been developed based on experimental data consisting of 99 samples with 7,129 genes. The way, how meaningful knowledge from these models can be extracted, and how this knowledge for further research is still a hot topic. This thesis addresses this and has developed an information method that includes modelling of interactive patterns, important genes discovery and visualisation of the obtained knowledge. The major goal of this thesis is to discover important genes responsible for CNS tumour and import these genes into a well structured knowledge framework system, called Brain-Gene-Ontology. In this thesis, we take the first step towards finding the most accurate model for analysing the CNS tumour by offering a comparative study of global, local and personalised modelling. Five traditional modelling approaches and a new personalised method – WWKNN (weighted distance, weighted variables K-nearest neighbours) – are investigated. To increase the classification accuracy and one-vs.-all based signal to- noise ratio is also developed for pre-processing experimental data. For the knowledge discovery, CNS-based ontology system is developed. Through ontology analysis, 21 discriminate genes are found to be relevant for different CNS tumour classes, medulloblastoma tumour subclass and medulloblastoma treatment outcome. All the findings in this thesis contribute for expanding the information space of the BGO framework.

Universiẗat, Diss., 2007--Giessen.

Zugl.: Magdeburg, Univ., Diss., 2006

Zugl.: Innsbruck, Univ., Diss., 2008

Stuttgart, Univ., Diss., 2002.

Universiẗat, Diss., 1991--Köln.