ŠUMAVA - NATURE AND PEOPLE - THROUGH THE EYES OF KAREL KLOSTERMANN (with special attention to the frequency,ways and possibilities of individual colours' usage) The aim of this thesis is to designate and describe qualities of the residents of the central Bohemian Forest and the attributes of local nature in the way they were depicted by the writer Karel Klostermann (1848-1923). The results of individual analyses performed in this thesis present the inhabitants of the Bohemian Forest as a society that is conservative, religion-based, maybe even superstitious and bearing a certain distrust to the surrounding world. The Bohemian Forest's landscape is very demanding, the impact of which is visible in the inhabitants' character traits - the increased directness and, in certain aspects, vulgarity of people living under these conditions. Nature is often approached as a literary image that is further developed in accordance with the spirit of impressionism. This is concluded, among other sources, from the specific use of colours that is further analyzed. The emphasis of sense perception pervades almost every descriptive passage.

[pt] Esta dissertação de mestrado apresenta um método para simular cenas de mar para TV/Cinema com um grande número de agentes de vários tipos (embarcações, portos, pessoas, ...) para produções com elevado grau de realismo de imagem e comportamento dos agentes. Este método usa modelagem em lógica nebulosa (fuzzy) e programação no sistema MASSIVE de maneira a integrar os resultados com sistemas de rendering e composição de imagens de alta resolução. Um objetivo importante desta dissertação é criar um sistema que facilita o trabalho de modeladores e designers envolvidos no pipeline de produção. / [en] This MSc dissertation presents a method to simulate sea scenes for TV / Film with a large number of agents of various types (vessels, ports, people ...) for productions with a high degree of realism in both image and agent s behavior. This method uses modeling in fuzzy logic and programming in the MASSIVE system as the main approach to integrate the results with rendering systems and high-resolution images composition. An important goal of this dissertation is to create a system that facilitates the work of modelers and designers involved in the production pipeline.

Investigamos o papel de condutâncias iônicas lentas na transmissão/codificação de informação entre neurônios que disparam em rajadas ou bursts. Para isso, desenvolvemos um protocolo experimental no qual a interação em tempo real entre computador e neurônio biológico permite isolar o efeito da dinâmica de um determinado tipo de canal iônico e estudar sua inuência nos mecanismos de codificação de informação. Os experimentos foram realizados com neurônios do gânglio estomatogástrico do siri azul, Callinectes sapidus, que não possuem condutâncias lentas capazes de fazê-los apresentar rajadas de disparos quando in vitro, condição na qual apresentam comportamento quiescente ou disparam tonicamente. Durante os experimentos, alteramos artificialmente o comportamento de um destes neurônios, conectando-o a um computador que introduz uma corrente capaz de fazê-lo apresentar rajadas. Essa corrente possui uma componente senoidal (vinda de um gerador de funções) e uma componente devido a uma condutância iônica lenta modelada matematicamente. A condutância lenta pode ser escolhida entre duas versões: uma em que a condutância é calculada em tempo real, a partir do valor instantâneo do potencial de membrana do neurônio biológico, e outra em que o valor da condutância é oriundo de uma série temporal previamente gravada. A fonte de informação utilizada nos experimentos é um neurônio artificial pré-sináptico, que possui uma distribuição de potenciais de ação (spikes) escolhida pelo experimentador, e é conectado ao neurônio biológico modificado através de um modelo de sinapse química inibidora. A quantidade de informação do neurônio artificial (variabilidade dos padrões de disparo) codificada pelo neurônio biológico é inferida calculando-se a informação mútua média entre eles para as duas versões da condutância lenta (dinâmica ou previamente gravada). Nossos experimentos reproduziram qualitativamente as observações feitas por nosso grupo no circuito pilórico intacto do siri, que possui neurônios conectados por mutua inibição que naturalmente apresentam bursts. Além disso, observamos que vários picos de informação mútua média, presentes quando a condutância é dinâmica, desaparecem quando esta é substituída pela série temporal previamente gravada da condutância. Assim, pudemos confirmar os resultados previamente obtidos com simulações computacionais em que foram utilizados apenas modelos matemáticos e na ausência de ruído e demonstramos que as condutâncias iônicas lentas constituem um mecanismo biofísico que permite a codificação de estímulos sinápticos em neurônios que apresentam rajadas. / We investigated the role of slow ionic conductances on information processing by bursting neurons. A real time experimental protocol was developed to allow interacting computer models and biological neurons to address the effect of dynamical details of a single type of ion channel in information coding mechanisms. We experimented on Callinectes sapidus (blue crab) stomatogastric ganglion neurons. Such neurons were chosen because they do not present the slow conductances that can led to bursting activity in vitro (in such conditions they can be found either in a quiescent or in a tonic firing state). The experiments consisted in artificially changing the behavior of one of these neurons by injecting a computer generated current to achieve bursting. Such current has a sinusoidal component (from a function generator) and a component due to mathematical model of a slow ionic conductance. The slow conductance was implemented in two versions: in one of them the instantaneous value of the conductance is computed in real time and according to the membrane potential of the biological neuron, in another version the value of the conductance simply comes from a time series previously stored in the computer. A pre-synaptic artificial neuron, with a spike distribution chosen by the experimenter, provided input for the biological neuron through an artificial chemical inhibitory synapse. The amount of information (variability of spike patterns from the artificial neuron) coded by the biological neuron was inferred by calculating the average mutual information along stimulus and response bursts for the two conditions of the slow conductance (dynamically calculated or from file previously stored). Our experiments reproduced the results found in intact pyloric central pattern generator bursting neurons connected by mutual inhibition. Moreover, we show that the average mutual information peaks, found when the conductance is dynamically calculated, disappear when we use the previously recorded time series of the conductance. Such results validate those only found previously in numerical simulations in the absence of noise and point the role of the slow ionic conductances in a biophysical mechanism that allow bursting motor neurons to encode in a nontrivial fashion the information they receive through a single synapse.

People with hearing loss (HL) often express a desire for the particular hearing device that will yield the best speech recognition. The problem with fulfilling that desire is that a vast number of hearing devices are available from which to choose. In recent years, medical device regulatory agencies have generally viewed hearing devices (i.e., hearing aids), particularly the hardware and even the software, as substantially equivalent. The purpose of this manuscript is to: 1) Synthesize a number of variables about the person, environment in which hearing occurs, as well as characteristics of the hearing aids that can impact speech recognition. 2) Describe a created tool entitled Realistic Expectations 2 (RE2), which has application to the clinical needs of estimating expected speech recognition with and without hearing aids. RE2 is available as a supplemental file to this manuscript and may be useful for comparing estimates against measures of speech recognition ability in addition to assisting with the explanation of the operation and limitations of hearing aids. When expected speech recognition is achieved, subsequent development of speech and language can continue based on circumstance, cognitive status, and cultural-specific learning, as well as personal and societal betterment efforts like education, rehabilitation, and therapy.

The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.

Potential employees use organization career webpages as a first source of information about potential jobs. A content analysis of the career webpages of twenty organizations that recruit from male-dominant occupations and twenty organizations that recruit for female-dominant occupations were examined for gender-specific textual markers and for textual markers for the characteristics of job expectations of comfort, reward and responsibility. Specific focus was made on college recruitment pages for employment into first post-college jobs. This study found that there is an underlying gender issue on organization’s college recruiting online presence. Organizations that have a recruitment strategy to hire women are challenged to appropriately appeal to women in their online recruitment messaging frameworks. Additionally, the rhetoric of job expectations is elusive and so is inadequate to foster the development of accurate expectations for a first post-college job.

The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.

Shader programming is important for realistic material and global illumination real-time rendering, especially in 3D industrial fields nowadays, more and more customers of Visual Components Oy, a Finnish 3D software company have been found to be no longer only content with the correct simulation result, but also the result of realistic real-time rendering. This thesis project will provide a deep research on real world material classification, property definition and global illumination techniques in industrial fields. On the other hand, the Shader program for different materials and global illumination techniques are also created according to the classification and definition in this thesis work. Moreover, an external rendering tool Redway3D is evaluated as the reference and regarded as the considerable solution in the future development work.

Portfolio optimisation has a number of constraints resulting from some practical matters and regulations. The closed-form mathematical solution of portfolio optimisation problems usually cannot include these constraints. Exhaustive search to reach the exact solution can take prohibitive amount of computational time. Portfolio optimisation models are also usually impaired by the estimation error problem caused by lack of ability to predict the future accurately. A number of Multi-Objective Genetic Algorithms are proposed to solve the problem with two objectives subject to cardinality constraints, floor constraints and round-lot constraints. Fuzzy logic is incorporated into the Vector Evaluated Genetic Algorithm (VEGA) to but solutions tend to cluster around a few points. Strength Pareto Evolutionary Algorithm 2 (SPEA2) gives solutions which are evenly distributed portfolio along the effective front while MOGA is more time efficient. An Evolutionary Artificial Neural Network (EANN) is proposed. It automatically evolves the ANN's initial values and structures hidden nodes and layers. The EANN gives a better performance in stock return forecasts in comparison with those of Ordinary Least Square Estimation and of Back Propagation and Elman Recurrent ANNs. Adaptation algorithms for selecting a pair of forecasting models, which are based on fuzzy logic-like rules, are proposed to select best models given an economic scenario. Their predictive performances are better than those of the comparing forecasting models. MOGA and SPEA2 are modified to include a third objective to handle model risk and are evaluated and tested for their performances. The result shows that they perform better than those without the third objective.

The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.