Modelling the Influence of Origin, Packing and Storage on Water Activity, Colour and Texture of Almonds, Hazelnuts and Walnuts Using Artificial Neural Networks

The present work assessed the influence of different factors on some physical and chemical properties of nuts. The factors evaluated were the presence or absence of the inner skin, geographical origin, storage conditions (ambient temperature, in a stove at 30 and 50 °C, in a chamber at 30 and 50 °C and 90 % RH, refrigerated and freezing) and type of package (none, low density polyethylene and low density polyethylene). The fruits studied were almonds, hazelnuts and walnuts from different countries. The properties measured were moisture content, water activity, colour coordinates (L*, a* and b*) and texture parameters (hardness and friability). Experimental data were modelled using neural networks. The results showed that the almonds from Spain and Romania had aw greater than 0.6, and therefore, its stability was not guaranteed, contrarily to the other samples that presented values of aw lower than 0.6. The colour coordinate lightness varied from 40.60 to 49.30 in the fresh samples but decreased during storage, indicating darkening. In general, an increase in hardness and friability was observed with the different storage conditions. Neuron weight analysis has shown that the origin was a good predictor for moisture content and texture; whereas, the storage condition was a good predictor for aw and colour. In conclusion, it was possible to verify that the properties of nuts are very different depending on origin; they are better preserved at lower temperatures and the type of package used did not impact the properties studied

Breast density classification using deep learning

Breast density screenings are an accepted means to determine a patient\u27s predisposed risk of breast cancer development. Although the direct correlation is not fully understood, breast cancer risk increases with higher levels of mammographic breast density. Radiologists visually assess a patient\u27s breast density using mammogram images and assign a density score based on four breast density categories outlined by the Breast Imaging and Reporting Data Systems (BI-RADS). There have been efforts to develop automated tools that assist radiologists with increasing workloads and to help reduce the intra- and inter-rater variability between radiologists. In this thesis, I explored two deep-learning-based approaches on breast density classification. First, I developed and experimented with algorithms using deep learning models (such as Inception V3 and ViT) to classify patients according to BI-RADS using various types of digital mammograms. Second, with the need to provide not only such classification but also a quantitative measure of breast density to help standardize assessments across radiologists, I applied a deep learning based semantic segmentation model, DeepLabV3, to predict density percentages which then were used to provide a linear and probability scale

Nonlinear Dynamics, Synchronisation and Chaos in Coupled FHN Cardiac and Neural Cells

Physiological systems are amongst the most challenging systems to investigate from a mathematically based approach. The eld of mathematical biology is a relatively recent one when compared to physics. In this thesis I present an introduction to the physiological aspects needed to gain access to both cardiac and neural systems for a researcher trained in a mathematically based discipline. By using techniques from nonlinear dynamical systems theory I show a number of results that have implications for both neural and cardiac cells. Examining a reduced model of an excitable biological oscillator I show how rich the dynamical behaviour of such systems can be when coupled together. Quantifying the dynamics of coupled cells in terms of synchronisation measures is treated at length. Most notably it is shown that for cells that themselves cannot admit chaotic solutions, communication between cells be it through electrical coupling or synaptic like coupling, can lead to the emergence of chaotic behaviour. I also show that in the presence of emergent chaos one nds great variability in intervals of activity between the constituent cells. This implies that chaos in both cardiac and neural systems can be a direct result of interactions between the constituent cells rather than intrinsic to the cells themselves. Furthermore the ubiquity of chaotic solutions in the coupled systems may be a means of information production and signaling in neural systems

Dynamical Modeling and Control of Multiphase Heat Transport Systems Based on Loop Heat Pipes

Effective heat transport systems in aerospace are based on multiphase loop heat pipes (LHPs). For a precise thermal control of the electronics, electrical heaters are additionally used to control the operating temperature of the LHP. This work focusses on the dynamical modeling and model-based control design for LHP-based heat transport systems. The results of this work can be used for the optimization of current control parameters and the efficient control design for future LHP applications

Dynamical Modeling and Control of Multiphase Heat Transport Systems Based on Loop Heat Pipes

Effective heat transport systems in aerospace are based on multiphase loop heat pipes (LHPs). For a precise thermal control of the electronics, electrical heaters are additionally used to control the operating temperature of the LHP. This work focusses on the dynamical modeling and model-based control design for LHP-based heat transport systems. The results of this work can be used for the optimization of current control parameters and the efficient control design for future LHP applications

Modelagem de aparência baseada em biofísica para tecidos do fígado humano

A representação gráfica de tecidos humanos é uma importante demanda para aplicações de áreas como ensino, entretenimento e treinamento médico. Frequentemente, a simulação de tais materiais envolve considerar características dinâmicas vinculadas as suas funções no corpo humano e que influenciam diretamente também em sua aparência. O fígado humano, apesar de um órgão interno, portanto, de difícil acesso, possui diferentes modelos de representação apresentados na literatura da Computação Gráfica (CG). Entretanto, tais modelos desconsideram as influências das propriedades ópticas dos elementos biofísicos que compõem os tecidos hepáticos, fornecendo assim, aproximações cuja parametrização controla apenas um estado específico do material orgânico, em geral, avaliando visualmente o resultado. O presente trabalho apresenta a modelagem dos tecidos do fígado humano através da descrição dos elementos biofísicos que compõem suas camadas estruturais: o parênquima e a cápsula de Glisson. Além disso, tal modelo implementa a interação luz-matéria em termos de eventos como a absorção, dispersão, reflexão e transmissão de luz, como processos biológicos que produzem a coloração específica do material, ou seja, sua resposta espectral. A abordagem matemática do modelo é definida como numérica e estocástica, para a qual é apresentada uma solução para garantir sua convergência. Reunindo recentes descrições sobre a estrutura dos tecidos hepáticos e sua interação com a luz apresentadas na literatura biomédica, o modelo desenvolvido representa a primeira solução baseada em biofísica para um órgão interno do corpo humano. Os resultados de imagens geradas através do modelo são apresentados junto a fotografias de tecidos análogos, assim como, curvas de respostas espectrais e espaciais disponíveis na literatura biomédica são comparadas com as produzidas pelo modelo desenvolvido, evidenciando a capacidade deste na representação gráfica do tecido hepático

Dynamical Modeling and Control of Multiphase Heat Transport Systems Based on Loop Heat Pipes

Effective heat transport systems in aerospace are based on multiphase loop heat pipes (LHPs). For a precise thermal control of the electronics, electrical heaters are additionally used to control the operating temperature of the LHP. This work focusses on the dynamical modeling and model-based control design for LHP-based heat transport systems. The results of this work can be used for the optimization of current control parameters and the efficient control design for future LHP applications

Cloud Computing: caracterización de los impactos positivos obtenidos por la utilización del modelo Cloud Computing por las pymes, basado en la tipología de modelos de negocio de este tipo de empresas

[ES] El Cloud Computing produce importantes beneficios a las empresas usuarias, en especial a las pymes. A través de él estas empresas tienen mejor acceso a las tecnologías de la información que necesitan para su funcionamiento. Según las estadísticas de utilización del cloud computing, estas empresas hacen un uso limitado de este tipo de servicios. El objetivo del presente trabajo es contribuir a potenciar la utilización del cloud por parte de las pymes. Según nuestro diagnóstico, el primer problema es del desconocimiento del cloud por parte de las pymes. Para abordar este problema se realiza una descripción del cloud computing y se analizan los beneficios que les proporciona a las empresas usuarias. Para contribuir a convencer a los empresarios de las ventajas que el uso del cloud les proporciona, se aborda el cloud desde una óptica empresarial y para ello se propone un modelo de negocio tipo para las pymes, para posteriormente relacionar los bloques en que se puede descomponer el citado modelo de negocio con las tecnologías de la información y la comunicación adecuadas para el funcionamiento de la empresa, accedidas a través del Cloud.Fons Gómez, FJ. (2014). Cloud Computing: caracterización de los impactos positivos obtenidos por la utilización del modelo Cloud Computing por las pymes, basado en la tipología de Modelos de Negocio de este tipo de empresas. http://hdl.handle.net/10251/38864.Archivo delegad