Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Project management under uncertainty: a study on solution methods

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and scheduling techniques to cope with the increasing flexibility in resources, as can be expressed in "Flexible Resource Constraint Project Scheduling Problem" (FRCPSP) formulations, should be a promising line of research to generate more adequate project management tools. In reality, this approach has been frequently used, by project managers in an ad-hoc way.

Local non-negative initial data scalar characterization of the Kerr solution

For any vacuum initial data set, we define a local, non-negative scalar quantity which vanishes at every point of the data hypersurface if and only if the data are Kerr initial data. Our scalar quantity only depends on the quantities used to construct the vacuum initial data set which are the Riemannian metric defined on the initial data hypersurface and a symmetric tensor which plays the role of the second fundamental form of the embedded initial data hypersurface. The dependency is algorithmic in the sense that given the initial data one can compute the scalar quantity by algebraic and differential manipulations, being thus suitable for an implementation in a numerical code. The scalar could also be useful in studies of the non-linear stability of the Kerr solution because it serves to measure the deviation of a vacuum initial data set from the Kerr initial data in a local and algorithmic way.

Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

Comunicação Android com câmaras ONVIF e gestão de Perfis de Media

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Redes de inovação em pequenas e médias empresas: um estudo de caso no setor têxtil

Dissertação de mestrado em Engenharia Industrial

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Hot-dip galvanized steel dip-coatedwith ureasilicate hybrid in simulated concrete pore solution: Assessment of coating morphology and corrosion protection efficiency

The barrier effect and the performance of an organic–inorganic hybrid (OIH) sol–gel coating are highlydependent on the coating deposition method as well as processing conditions. In this work, studies onthe influence of experimental parameters using the dip coating method were performed. Factors suchas residence time (Rt), a curing step between each dip step and the number of layers of sol–gel OIHfilms deposited on HDGS to prevent corrosion in highly alkaline environments were studied. These OIHcoatings were obtained using a functionalized siloxane, 3-isociantepropyltriethoxysilane that reactedwith a diamino-functionalized oligopolymer (Jeffamine®D-230). The barrier efficiency of OIH coatings insimulated concrete pore solutions (SCPS) was assessed in the first moments of contact, by electrochemicalimpedance spectroscopy and potentiodynamic methods. The durability and stability of the OIH coatings inSCPS was monitored during eight days by macrocell current density. The morphological characterizationof the surface was performed by scanning electronic microscopy before and after exposure to SCPS.Glow discharge optical emission spectroscopy was used to obtain quantitative composition profiles toinvestigate the thickness of the OIH coatings as a function of the number of layers deposited and theinfluence of the Rt in the coating thickness.

Ureasilicate hybrid coatings for corrosion protection of galvanized steel in chloride-contaminated simulated concrete pore solution

Organic-inorganic hybrid (OIH) sol-gel coatings based on ureasilicates (U(X)) have promising properties for use as eco-friendly coatings on hot dip galvanized steel (HDGS) and may be considered potential substitutes for pre-treatment systems containing Cr(VI). These OIH coatings reduce corrosion activity during the initial stages of contact of the HDGS samples with highly alkaline environments (cementitious media) and allow the mitigation of harmful effects of an initial excessive reaction between cement pastes and the zinc layer. However, the behavior of HDGS coated with U(X) in the presence of chloride ions has never been reported. In this paper, the performance of HDGS coated with five different U(X) coatings was assessed by electrochemical measurements in chloride-contaminated simulated concrete pore solution (SCPS). U(X) sol-gel coatings were produced and deposited on HDGS by a dip coating method. The coatings performance was evaluated by electrochemical impedance spectroscopy, potentiodynamic polarization curves measurements, macrocell current density and polarization resistance in contact with chloride-contaminated SCPS. The SEM/EDS analyses of the coatings before and after the tests were also performed. The results showed that the HDGS samples coated with the OIH coatings exhibited enhanced corrosion resistance to chloride ions when compared to uncoated galvanized steel.

PEGylated DOTA-AHA-based Gd(III) chelates – A relaxometric study

Three PEGylated derivatives of 1,4,7,10-tetraazacyclododecane-1-((6-amino)hexanoic)-4,7,10-triacetic acid) (DOTA-AHA) with different molecular weights were prepared and characterized. Their Gd(III) chelates were studied in aqueous solution using variable-temperature 1H nuclear magnetic relaxation dispersion (NMRD) and 17ONMR spectroscopy in view of the determination of their relaxivity and the parameters that govern it. The relaxivity varied from 5.1 to 6.5 mM-1.s-1 (37 ºC and 60 MHz) with the increasing molecular weight of the PEG chain, being slightly higher than that of the parent chelate Gd(DOTA-AHA), due to a small contribution of a slow global rotation of the complexes. A variable temperature 1H NMR study of several Ln(III) chelates of DOTA-A(PEG750)HA allowed the determination of the isomeric M/m ratio (M = square antiprismatic isomer and m = twisted square antiprismatic isomer, the latter presenting a much faster water exchange) which for the Gd(III) chelate was estimated in circa 1:0.2, very close to that of [Gd(DOTA)]-. This explains why the PEGylated Gd(III) chelate has a water rate exchange similar to that of [Gd(DOTA)]-. The predominance of the M isomer is a consequence of the bulky PEG moiety which does not favor the stabilization of the m isomer in sterically crowded systems at the substituent site, contrary to what happens with less packed asymmetrical DOTA-type chelates with substitution in one of the four acetate C(α) atoms.

Gestão e instalação de redes de sensores sem fios (domótica)

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Aplicação web para configuração e acesso a câmaras ONVIF

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.