Run-time monitoring in real-time operating systems

Embedded systems are increasingly complex and dynamic, imposing progressively higher developing time and costs. Tuning a particular system for deployment is thus becoming more demanding. Furthermore when considering systems which have to adapt themselves to evolving requirements and changing service requests. In this perspective, run-time monitoring of the system behaviour becomes an important requirement, allowing to dynamically capturing the actual scheduling progress and resource utilization. For this to succeed, operating systems need to expose their internal behaviour and state, making it available to external applications, and a runtime monitoring mechanism must be available. However, such mechanism can impose a burden in the system itself if not wisely used. In this paper we explore this problem and propose a framework, which is intended to provide this run-time mechanism whilst achieving code separation, run-time efficiency and flexibility for the final developer.

Controlo fotogramétrico da condição de estruturas quebra-mar

Dissertação de natureza Científica para obtenção do grau de Mestre em Engenharia Civil

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Monitoring chlorophyll-a with remote sensing techniques in the Tagus Estuary

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Gestão e Sistemas Ambientais

Run-time monitoring approach for the shark kernel

Typically common embedded systems are designed with high resource constraints. Static designs are often chosen to address very specific use cases. On contrast, a dynamic design must be used if the system must supply a real-time service where the input may contain factors of indeterminism. Thus, adding new functionality on these systems is often accomplished by higher development time, tests and costs, since new functionality push the system complexity and dynamics to a higher level. Usually, these systems have to adapt themselves to evolving requirements and changing service requests. In this perspective, run-time monitoring of the system behaviour becomes an important requirement, allowing to dynamically capturing the actual scheduling progress and resource utilization. For this to succeed, operating systems need to expose their internal behaviour and state, making it available to the external applications, usually using a run-time monitoring mechanism. However, such mechanism can impose a burden in the system itself if not wisely used. In this paper we explore this problem and propose a framework, which is intended to provide this run-time mechanism whilst achieving code separation, run-time efficiency and flexibility for the final developer.

Immunodiagnostic confirmation of hydatid disease in patients with a presumptive diagnosis of infection

Information obtained from the routine application of hydatid immunodiagnostic techniques in different clinical situations over a seven-year period is presented. The Immunoelectrophoresis test was used until it was replaced by the simpler, more sensitive and equally specific arc 5 double diffusion (DD5) test. Examination of sera from 1,888 patients with signs and/or symptoms compatible with hydatid disease revealed that the presurgical confirmation of Echinococcus granulosus infection is only obtained by detection of anti-antigen 5 antibodies. The latter were not found in 1,539 presumptive hydatidosis patients whose definitive diagnoses corresponded to other disease conditions. However, false positive latex agglutination test results were obtained in two cases. In all patients whose preoperative serum showed three or more uncharacteristic bands in the absence of anti-antigen 5 antibodies, hydatid cysts were found sur gically. DD5 testing of a fluid sample collected by puncture established its hydatid etiology. Post-operative monitoring of hydatidosis patients demonstrated that persistence of DD5-positivity two years after surgery established the presence of other cysts. Further evidence was obtained in patients with hydatid cysts in intrathoracic, abdominal or other locations associating cyst membrane integrity, antigen release and immunodiagnostic test positivity.

Práticas de Inclusão de Alunos com perturbações do espetro do autismo

Este artigo surge no âmbito de um estudo mais vasto que tem como principal objetivo identificar as Necessidades de Formação dos Docentes de Ensino Regular e de Educação Especial para a inclusão de alunos com Perturbações do Espetro do Autismo (PEA) nas escolas do ensino regular. Para a realização desse estudo, realizámos observações diretas em sala de aula e auscultámos os vários agentes educativos que podem contribuir para a inclusão efetiva destes alunos, nomeadamente os docentes de ensino regular (1º ciclo) e educação especial, diretores de agrupamentos de escolas com unidades de ensino estruturado para alunos autistas e encarregados de educação dos alunos com PEA. Paralelamente, analisámos os documentos de suporte ao desenvolvimento do processo educativo destes alunos. Mais especificamente, com as observações em sala de aula do ensino regular, pretendemos conhecer as práticas pedagógicas desenvolvidas e as formas de organização e gestão curricular da turma e de apoio e acompanhamento específico a estes alunos. Neste artigo apresentamos a análise das observações, tendo em conta: (i) o contexto de observação; (ii) as estratégias e atividades desenvolvidas; (iii) a relação comunicativa estabelecida.Desta análise, é possível inferir necessidades de formação que se situam tanto ao nível da compreensão da problemática das crianças como do planeamento e gestão curricular da turma.

The contribution of multitemporal information from multispectral satellite images for automatic land cover classification at the national scale

Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems

Insignificant impact of prescribed fire on surface soil in a Pinus pinaster plantation, northern Portugal

Following a prescribed fire in a Pinus pinaster forest site located in the north-west Portugal, monitoring of any changes in selected soil characteristics and soil hydrology was undertaken to assess the effects of burning on the following: pH, electrical conductivity, water content, organic carbon and porosity. Thirty plots were established on a regular grid. At each sample plot before and after the fire, samples were collected (disturbed samples from depths of 0-1cm and 1-5cm; undisturbed core samples from 0-5cm). The results indicate that there was no measurable impact on the properties of the soil following this carefully conducted prescribed fire. The fire only affected the litter layer, as intended. Confirmation of this minimal impact on the soil was provided by regrowth of grasses and herbs already occurring two months after the fire. The implication is, therefore, that provided this wildfire-risk reduction strategy is carried out under existing strict guidelines, any impact on soil quality will be minimal.

Primary bioreceptivity of limestones from the mediterranean basin to phototrophic microorganisms

Dissertação apresentada para a obtenção do grau de Doutor em Conservação e Restauro pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Benchmarking de identificação de ano: criação de um site para benchmarking de técnicas de identificação de dano

Dissertação para obtenção do grau de Mestre em Engenharia Mecânica na Área de Manutenção e Produção

Utilização de plataformas de fonte aberta no controlo de condição

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Characterisation of adventitious lung sounds in people with dementia

Introduction: Lower Respiratory Tract Infections (LRTIs) are highly prevalent in institutionalised people with dementia, constituting an important cause of morbidity and mortality. Computerised auscultation of Adventitious Lung Sounds (ALS) has shown to be objective and reliable to assess and monitor respiratory diseases, however its application in people with dementia is unknown. Aim: This study characterised ALS (crackles and wheezes) in institutionalised people with dementia. Methods: An exploratory descriptive study, including 6 long-term care institutions was conducted. The sample included a dementia group (DG) of 30 people with dementia and a match healthy group (HG) of 30 elderly people. Socio-demographic and anthropometric data, cognition, type and severity of dementia, cardio-respiratory parameters, balance, mobility and activities and participation were collected. Lung sounds were recorded with a digital stethoscope following Computerised Respiratory Sound Analysis (CORSA) guidelines. Crackles’ location, number (N), frequency (F), two-cycle duration (2CD), initial deflection width (IDW) and largest deflection width (LDW) and wheezes’ number (N), ratio (R) and frequency (F) were analysed per breathing phase. Statistical analyses were performed using PASW Statistics(v.19). Results: There were no significant differences between the two groups in relation to the mean N of crackles during inspiration and expiration in both trachea and thorax. DG trachea crackles had significant higher F during inspiration and lower IDW, 2CD and LDW during expiration when compared with HG. At the thorax, the LDW during inspiration was also significantly lower in the DG. A significant higher N of inspiratory wheezes was found in the HG. Both groups had a low ratio of high frequency wheezes. Conclusion: Computerised analyses of ALS informed on the respiratory system and function of people with dementia and elderly people. Hence, this could be the step towards prevention, early diagnosis and continuous monitoring of respiratory diseases in people with cognitive impairment.

Design and implementation of an autonomous, proactive, and reactive software infrastructure to help improving the management level of projects

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.