Normalization is important for a large range of phenomena in biological neural systems such as light adaptation in the retina, context dependent decision making and probabilistic inference. In a normalizing circuit the activity of one neuron/-group of neurons is divisively rescaled in relation to the activity of other neurons/­­groups. This creates neural responses invariant to certain stimulus dimensions and dynamically adapts the range over which a neural system can respond discriminatively on stimuli. This thesis examines whether a biologically realistic normalizing circuit can be implemented by a spiking neural network model based on the columnar structure found in cortex. This was done by constructing and evaluating a highly structured spiking neural network model, modelling layer 2/3 of a cortical hypercolumn using a group of neurons as the basic computational unit. The results show that the structure of this hypercolumn module does not per se create a normalizing network. For most model versions the modulatory effect is better described as subtractive inhibition. However three mechanisms that shift the modulatory effect towards normalization were found: An increase in membrane variance for increased modulatory inputs; variability in neuron excitability and connections; and short-term depression on the driving synapses. Moreover it is shown that by combining those mechanisms it is possible to create a spiking neural network that implements approximate normalization over at least ten times increase in input magnitude. These results point towards possible normalizing mechanisms in a cortical hypercolumn; however more studies are needed to assess whether any of those could in fact be a viable explanation for normalization in the biological nervous system. / Normalisering är viktigt för en lång rad fenomen i biologiska nervsystem såsom näthinnans ljusanpassning, kontextberoende beslutsfattande och probabilistisk inferens. I en normaliserande krets skalas aktiviteten hos en nervcell/grupp av nervceller om i relation till aktiviteten hos andra nervceller/grupper. Detta ger neurala svar som är invarianta i förhållande till vissa dimensioner hos stimuli, och anpassar dynamiskt för vilka inputmagnituder ett system kan särskilja mellan stimuli. Den här uppsatsen undersöker huruvida en biologiskt realistisk normal­iserande krets kan implementeras av ett spikande neuronnätverk konstruerat med utgångspunkt från kolumnstrukturen i kortex. Detta gjordes genom att konstruera och utvärdera ett hårt strukturerat rekurrent spikande neuronnätverk, som modellerar lager 2/3 av en kortikal hyperkolumn med en grupp av neuroner som grundläggande beräkningsenhet. Resultaten visar att strukturen i hyperkolumn­modulen inte i sig skapar ett normaliserande nätverk. För de flesta nätverks­versioner implementerar nätverket en modulerande effekt som bättre beskrivs som subtraktiv inhibition. Dock hittades tre mekanismer som skapar ett mer normaliserande nätverk: Ökad membranvarians för större modulerande inputs; variabilitet i excitabilitet och inkommande kopplingar; och korttidsdepression på drivande synapser. Det visas också att genom att kombinera dessa mekanismer är det möjligt att skapa ett spikande neuronnät som approximerar normalisering över ett en åtminstone tio gångers ökning av storleken på input. Detta pekar på möjliga normaliserande mekanismer i en kortikal hyperkolumn, men ytterligare studier är nödvändiga för att avgöra om en eller flera av dessa kan vara en förklaring till hur normalisering är implementerat i biologiska nervsystem.

In this study, the impact of multiple image preprocessing methods on Convolutional Neural Networks (CNN) was studied. Metrics such as accuracy, precision, recall and F1-score (Hossin et al. 2011) were evaluated. Specifically, this study is geared towards malaria classification using the data set made available by the U.S. National Library of Medicine (Malaria Datasets n.d.). This data set contains images of thin blood smears, where uninfected and parasitized blood cells have been segmented. In the study, 3 CNN models were proposed for the parasitization classification task. Each model was trained on the original data set and 4 preprocessed data sets. The preprocessing methods used to create the 4 data sets were grayscale, normalization, histogram equalization and contrast limited adaptive histogram equalization (CLAHE). The impact of CLAHE preprocessing yielded a 1.46% (model 1) and 0.61% (model 2) improvement over the original data set, in terms of F1-score. One model (model 3) provided inconclusive results. The results show that CNN’s can be used for parasitization classification, but the impact of preprocessing is limited. / I denna studie studerades effekten av flera bildförbehandlingsmetoder på Convolutional Neural Networks (CNN). Mätvärden såsom accuracy, precision, recall och F1-score (Hossin et al. 2011) utvärderades. Specifikt är denna studie inriktad på malariaklassificering med hjälp av ett dataset som tillhandahålls av U.S. National Library of Medicine (Malaria Datasets n.d.). Detta dataset innehåller bilder av tunna blodutstryk, med segmenterade oinfekterade och parasiterade blodceller. I denna studie föreslogs 3 CNN-modeller för parasiteringsklassificeringen. Varje modell tränades på det ursprungliga datasetet och 4 förbehandlade dataset. De förbehandlingsmetoder som användes för att skapa de 4 dataseten var gråskala, normalisering, histogramutjämning och kontrastbegränsad adaptiv histogramutjämning (CLAHE). Effekten av CLAHE-förbehandlingen gav en förbättring av 1.46% (modell 1) och 0.61% (modell 2) jämfört med det ursprungliga datasetet, vad gäller F1-score. En modell (modell 3) gav inget resultat. Resultaten visar att CNN:er kan användas för parasiteringsklassificering, men effekten av förbehandling är begränsad.

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Prior to 1960's, the fingerprint analysis was carried out manually by human experts and for forensic purposes only. Automated fingerprint identification systems (AFIS) have been developed during the last 50 years. The success of AFIS resulted in that its use expanded beyond forensic applications and became common also in civilian applications. Mobile phones and computers equipped with fingerprint sensing devices for fingerprint-based user identification are common today. Despite the intense development efforts, a major problem in automatic fingerprint identification is to acquire reliable matching features from fingerprint images with poor quality. Images where the fingerprint pattern is heavily degraded usually inhibit the performance of an AFIS system. The performance of AFIS systems is also reduced when matching fingerprints of individuals with large age variations. This doctoral thesis presents contributions within the field of fingerprint image enhancement, segmentation and minutiae detection. The reliability of the extracted fingerprint features is highly dependent on the quality of the obtained fingerprints. Unfortunately, it is not always possible to have access to high quality fingerprints. Therefore, prior to the feature extraction, an enhancement of the quality of fingerprints and a segmentation are performed. The segmentation separates the fingerprint pattern from the background and thus limits possible sources of error due to, for instance, feature outliers. Most enhancement and segmentation techniques are data-driven and therefore based on certain features extracted from the low quality fingerprints at hand. Hence, different types of processing, such as directional filtering, are employed for the enhancement. This thesis contributes by proposing new research both for improving fingerprint matching and for the required pre-processing that improves the extraction of features to be used in fingerprint matching systems. In particular, the majority of enhancement and segmentation methods proposed herein are adaptive to the characteristics of each fingerprint image. Thus, the methods are insensitive towards sensor and fingerprint variability. Furthermore, introduction of the higher order statistics (kurtosis) for fingerprint segmentation is presented. Segmentation of the fingerprint image reduces the computational load by excluding background regions of the fingerprint image from being further processed. Also using a neural network to obtain a more robust minutiae detector with a patch rejection mechanism for speeding up the minutiae detection is presented in this thesis.

This work aims to study the procedures of fingerprint identification system and to present some efficient algorithms for pre-processing and minutiae extraction. Most pre-processing steps consist of normalization, segmentation and orientation estimation, and background which focus on decreasing the variance of fingerprints, separating fore and background areas and tracking the direction of ridge lines, respectively. Minutiae extractionis typically divided into two approaches: binarization based method and directgray scale extraction. However, we put emphasis on binarization based method in thisresearch since it is more commonly used method in research papers. The results of simulationbased on a set of fingerprints downloaded from FVC 2006 database showed thatalgorithms we used are accurate and reliable.

Recently, there has been interest to integrate VMC++ into the commercial treatment planning system at VCU as another Monte Carlo code option, since it has been shown to increase efficiency dramatically without introducing a significant amount of systematic error. Also, independent validation of VMC++ for photon beams is of interest since this has not been performed previously in literature. This study included several tests required to integrate VMC++. Output factor normalization was performed and found to agree with experiment to within 1% for all field sizes except 1x1 cm2. Geometric validation was successful. Dosimetric validation was performed with respect to DOSXYZnrc on a water phantom, resulting in agreement within statistical uncertainty except for slight differences at the surface of the phantom. Dosimetric comparison was made for a head-and-neck patient case, showing that 5% of the voxels did not agree within 2.8% of maximum dose. The ability of VMC++ to compute dose-to-water was compared to an in-house algorithm and found to agree within statistical uncertainty.

The thesis is focused on discrediting texts on the personalities of Czechoslovak dissidents in years 1977-1979 and 1985-1988. It studies the historical background of these years and describes this problem in the way of critical discourse analysis. Therefore, there is used description of the historical period with analysis of texts in three newspapers, called Rude Právo, Mladá Fronta and Lidová Demokracie. The objective of the work is collection of texts of the newspapers in mentioned period and demonstration of typical discrediting text. First of all, there is pointed what it means "dissent". There are described groups and people, who were connected with these activities. Secondly, there is shown special cause about lawsuit with Václav Havel and Tomáš Řezáč. The perspective is focused on exceptional and special action which was linked with discrediting texts and official law. After that are summarized aspects and significance of discrediting texts. There is hope that this thesis dispels the complex problem of discrediting texts, and that the case for ideology developed through media is clear.

Charles University in Prague Faculty of Social Sciences Institute of Communication Studies and Journalism Perception of Media Contents, Status and Role in Czechoslovakia in 1977-1989 Diploma thesis Author: Zbyněk Vlasák Consultant: PhDr. Jakub Končelík, Ph.D. Abstract This thesis called Perception of Media Contents, Status and Role in Czechoslovakia in 1977-1989 analyzes possible principles and circumstances of perceiving the role of the media in a specific environment of the normalisation period using methods of oral history. Furthermore, the thesis examines the function of the media in the everyday life of normalisation households and identifies the sources of images responsible for bipolarization of the outside world and their nature. It also deals with the public view on the importance of free media for the functioning of a democratic society. Last but not least, the thesis tracks the possibility of obtaining information from official, unofficial and foreign media. To be able to conduct the above mentioned analyses, the base of this thesis lie in historiography, several chapters deal with formal and informal pressure exerted on the official media sources and circumstances of foreign media broadcast on the Czechoslovak territory. We do not omit the international context of the period 1977-1989 and...

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This thesis deals with so called normalization of Czech literature which took place after the Prague Spring of 1968 in the perspective of literary field theory formulated by Pierre Bourdieu. Based on various textual data it reconstructs the literary field refraction focusing on the relationship between literary field and the field of power, position which newly appeared and habitus formulated. It offers few findings which might be subject to further verification in more detailed analysis.