Lightweight monitoring of transactional memory programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

Prenatal toxoplasmosis diagnosis from amniotic fluid by PCR

Toxoplasmosis is one of the most common infections all over the world. Most cases are asymptomatic, except in immunosuppressed individuals and fetuses, which can be seriously damaged. Prenatal diagnosis should be made as soon as possible since treatment of the mother can minimize fetal sequelae. Our aim in this study was to test the polymerase chain reaction technique (PCR) in 86 samples of amniotic fluid from women who seroconverted during pregnancy. DNA was amplified using external primers and, in a second step, internal primers, in a nested PCR system. Samples were also inoculated into mice and the newborn were evaluated by T. gondii serology, skull x-ray, transfontanel ultrasound, fundoscopic examination, lumbar puncture and clinical examination. PCR was positive in seven cases and negative in 79. Among PCR-positive cases, two were negative by inoculation into mice and by clinical evaluation; among PCR-negative ones, three had clinical evidence of toxoplasmosis and one was positive after inoculation into mice. PCR showed values of sensitivity = 62.5% and specificity = 97.4%; the values of inoculation into mice where 42.9% and 100%, respectively. Although PCR should not be used alone for prenatal diagnosis of congenital toxoplasmosis, it is a promising method and deserves more studies to improve its efficacy.

Corporate finance in general equilibrium models with incomplete markets: A survey

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Narrative Memory in Hyperfiction and Games

The aim of this paper is to address some theoretical issues concerning the narrative practice in cyberspace. From a narratological perspective it intends to clarify the functioning of time and space in storytelling. For that purpose it traces the concept(s) of memory inherited from rhetoric; the use of memory as a narrative device in traditional accounts; the adaptations imposed by hyperfiction. Using practical examples (including two Portuguese case studies - InStory 2006, and Noon 2007) it will show how narrative memory strategies can be helpful in game literacy. The main purpose is to contribute to serious game research and (trans)literary studies.

Dynamic adaptation of interaction models for stateful web services

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Smart windows with permanent memory effect

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Microscopy image segmentation by active contour models

In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.

Evaluation of Taenia solium and Taenia crassiceps cysticercal antigens for immunodiagnosis of neurocysticercosis using ELISA on cerebrospinal fluid samples

The efficacy of whole parasite and vesicular fluid antigen extracts from Taenia solium and Taenia crassiceps cysticerci for immunodiagnosis of neurocysticercosis was evaluated using ELISA on cerebrospinal fluid samples. Anticysticercal IgG antibodies were assayed in cerebrospinal fluid samples from 23 patients with neurocysticercosis and 35 patients with other neurological disorders. The ELISA reaction for the whole Taenia solium cysticercal extract showed 91.3% sensitivity and 94.3% specificity, whereas the sensitivity and specificity of the ELISA for the whole Taenia crassiceps cysticercal extract were 87% and 94.3%, respectively. The ELISA reactions for vesicular fluid from Taenia solium or Taenia crassiceps showed 91.3% sensitivity and 97.1% specificity. Considering the results obtained from the four antigen preparations, vesicular fluid from Taenia solium and Taenia crassiceps cysticerci may be useful as a source of antigens for immunological reactions that are used for detecting specific antibodies in cerebrospinal fluid samples from patients with neurocysticercosis.

Participatory Surveillance and Mathematical Models in Epidemiologic Research: Successes and Challenges

Theoretical epidemiology aims to understand the dynamics of diseases in populations and communities. Biological and behavioral processes are abstracted into mathematical formulations which aim to reproduce epidemiological observations. In this thesis a new system for the self-reporting of syndromic data — Influenzanet — is introduced and assessed. The system is currently being extended to address greater challenges of monitoring the health and well-being of tropical communities.(...)

Amyotrophic Lateral Sclerosis:Mammalian Cell Models,Copper-Zinc Superoxide Dismutaseand Biological Characteristics

"Amyotrophic Lateral Sclerosis (ALS) is the most severe and common adult onset disorder that affects motor neurons in the spinal cord, brainstem and cortex, resulting in progressive weakness and death from respiratory failure within two to five years of symptoms onset(...)

Enterprise reference lexicon building from business models

Nowadays, a significant increase on the demand for interoperable systems for exchanging data in business collaborative environments has been noticed. Consequently, cooperation agreements between each of the involved enterprises have been brought to light. However, due to the fact that even in a same community or domain, there is a big variety of knowledge representation not semantically coincident, which embodies the existence of interoperability problems in the enterprises information systems that need to be addressed. Moreover, in relation to this, most organizations face other problems about their information systems, as: 1) domain knowledge not being easily accessible by all the stakeholders (even intra-enterprise); 2) domain knowledge not being represented in a standard format; 3) and even if it is available in a standard format, it is not supported by semantic annotations or described using a common and understandable lexicon. This dissertation proposes an approach for the establishment of an enterprise reference lexicon from business models. It addresses the automation in the information models mapping for the reference lexicon construction. It aggregates a formal and conceptual representation of the business domain, with a clear definition of the used lexicon to facilitate an overall understanding by all the involved stakeholders, including non-IT personnel.

Gas tungsten arc welding of NiTi shape memory alloy

Shape memory alloys are characterized by the ability of recovering their initial shape after being deformed and by superelasticity. Since the discovery of these alloys, a new field of interest emerged not only for the scientific community but also to many industries. However, these alloys present poor machinability which constitute a constrain in the design of complex components for new applications. Thus, the demand for joining techniques able to join these alloys without compromising their properties became of great importance to enlarge the complexity of existing applications. Literature shows that these alloys are joined mainly using laser welding. In the present study, similar NiTi butt joints, were produced using TIG welding. The welds were performed in 1.5 mm thick plates across the rolling direction. A special fixture and gas assist device was designed and manufactured. Also a robot arm was adapted to accommodate the welding torch to assure the repeatability of the welding parameters. Welds were successfully achieved without macroscopic defects, such as pores and distortions. Very superficial oxidation was seen on the top surface due to insufficient shielding gas flow on the weld face. The welded joints were mechanically tested and structurally characterized. Testing methods were used to evaluate macro and microstructure, as well as the phase transformation temperatures, the mechanical single and cyclic behaviour and the shape recovery ability. Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), microhardness measurements were techniques also used to evaluate the welded joints. A depletion in Ni in the fusion zone was seen, as well as a shift in Ms temperature. For strain values of 4% the accumulated irrecoverable strain was of about 30% and increased with the strain imposed during cycling. Nevertheless, a complete recovery of initial shape was observed when testing the shape memory effect on a dedicated device that introduces a deformation of 6.7%. That is, the welding procedure does not remove the ability of the specimens to recover their initial shape.

Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

Real-time collaborative editing of OutSystems DSL models

Real-time collaborative editing systems are common nowadays, and their advantages are widely recognized. Examples of such systems include Google Docs, ShareLaTeX, among others. This thesis aims to adopt this paradigm in a software development environment. The OutSystems visual language lends itself very appropriate to this kind of collaboration, since the visual code enables a natural flow of knowledge between developers regarding the developed code. Furthermore, communication and coordination are simplified. This proposal explores the field of collaboration on a very structured and rigid model, where collaboration is made through the copy-modify-merge paradigm, in which a developer gets its own private copy from the shared repository, modifies it in isolation and later uploads his changes to be merged with modifications concurrently produced by other developers. To this end, we designed and implemented an extension to the OutSystems Platform, in order to enable real-time collaborative editing. The solution guarantees consistency among the artefacts distributed across several developers working on the same project. We believe that it is possible to achieve a much more intense collaboration over the same models with a low negative impact on the individual productivity of each developer.