Design and implementation of 3D buildings integration for a Webgl-Based Virtual Globe: a case study of Valencian Cadastre and Fide Building Mode

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Optimization of fMRI Processing Parameters for Simutaneous Acquisition of EEG/fMRI in Focal Epilepsy

In the context of focal epilepsy, the simultaneous combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) holds a great promise as a technique by which the hemodynamic correlates of interictal spikes detected on scalp EEG can be identified. The fact that traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the lobes, brings the need of mapping with more precision the epileptogenic cortical regions. On the other hand, fMRI suggested localizations more consistent with the ictal clinical manifestations detected. This study was developed in order to improve the knowledge about the way parameters involved in the physical and mathematical data, produced by the EEG/fMRI technique processing, would influence the final results. The evaluation of the accuracy was made by comparing the BOLD results with: the high resolution EEG maps; the malformative lesions detected in the T1 weighted MR images; and the anatomical localizations of the diagnosed symptomatology of each studied patient. The optimization of the set of parameters used, will provide an important contribution to the diagnosis of epileptogenic focuses, in patients included on an epilepsy surgery evaluation program. The results obtained allowed us to conclude that: by associating the BOLD effect with interictal spikes, the epileptogenic areas are mapped to localizations different from those obtained by the EEG maps representing the electrical potential distribution across the scalp (EEG); there is an important and solid bond between the variation of particular parameters (manipulated during the fMRI data processing) and the optimization of the final results, from which smoothing, deleted volumes, HRF (used to convolve with the activation design), and the shape of the Gamma function can be certainly emphasized.

An RF LC Q-enhanced CMOS iter using integrated inductors with layout optimization

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Purification of complex biopharmaceuticals with new processes, advanced analytics and computer-aided process design tools

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Design of multidimensional compact constellations with high power efficiency

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Modeling of integrated inductors for RF circuit design

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica

Optimization of ring oscillators

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Optimal design and operation of compact simulated moving bed processes for enantioseparations

Simulated moving bed (SMB) chromatography is attracting more and more attention since it is a powerful technique for complex separation tasks. Nowadays, more than 60% of preparative SMB units are installed in the pharmaceutical and in the food in- dustry [SDI, Preparative and Process Liquid Chromatography: The Future of Process Separations, International Strategic Directions, Los Angeles, USA, 2002. http://www. strategicdirections.com]. Chromatography is the method of choice in these ¯elds, be- cause often pharmaceuticals and ¯ne-chemicals have physico-chemical properties which di®er little from those of the by-products, and they may be thermally instable. In these cases, standard separation techniques as distillation and extraction are not applicable. The noteworthiness of preparative chromatography, particulary SMB process, as a sep- aration and puri¯cation process in the above mentioned industries has been increasing, due to its °exibility, energy e±ciency and higher product purity performance. Consequently, a new SMB paradigm is requested by the large number of potential small- scale applications of the SMB technology, which exploits the °exibility and versatility of the technology. In this new SMB paradigm, a number of possibilities for improving SMB performance through variation of parameters during a switching interval, are pushing the trend toward the use of units with smaller number of columns because less stationary phase is used and the setup is more economical. This is especially important for the phar- maceutical industry, where SMBs are seen as multipurpose units that can be applied to di®erent separations in all stages of the drug-development cycle. In order to reduce the experimental e®ort and accordingly the coast associated with the development of separation processes, simulation models are intensively used. One impor- tant aspect in this context refers to the determination of the adsorption isotherms in SMB chromatography, where separations are usually carried out under strongly nonlinear conditions in order to achieve higher productivities. The accurate determination of the competitive adsorption equilibrium of the enantiomeric species is thus of fundamental importance to allow computer-assisted optimization or process scale-up. Two major SMB operating problems are apparent at production scale: the assessment of product quality and the maintenance of long-term stable and controlled operation. Constraints regarding product purity, dictated by pharmaceutical and food regulatory organizations, have drastically increased the demand for product quality control. The strict imposed regulations are increasing the need for developing optically pure drugs.(...)

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Contribution to the marine propeller hydrodynamic design for small boats in the Amazon region

ABSTRACTIn the Amazon, river navigation is very important due to the length of navigable rivers and the lack of alternative road networks. Boats usually operate in unfavorable conditions, since there is no hydrodynamic relation among propellers, geometry, and the dimensions of the boat hull. Currently, there is no methodology for propeller hydrodynamic optimization with low computational cost and easy implementation in the region. The aim of this work was to develop a mathematical approach for marine propeller design applied to boats typically found on Amazon rivers. We developed an optimized formulation for the chord and pitch angle distributions, taking into account the classical model of Glauert. A theoretical analysis for the thrust and torque relationships on an annular control volume was performed. The mathematical model used was based on the Blade Element Momentum Theory (BEMT). We concluded that the new methodology proposed in this work demonstrates a good physical behavior when compared with the theory of Glauert and the experimental data of the Wageningen B3-50 propeller.

Optimization of filling systems for low pressure by Flow 3D

Dissertação de mestrado integrado em Engenharia Mecânica