Visualization and interaction in a simulation system for flood emergencies

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

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.

Angiotensinergic neurotransmission in the peripheral autonomic nervous system.

Angiotensin (Ang) II has for long been identified as a neuropeptide located within neurons and pathways of the central nervous system involved in the control of thirst and cardio-vascular homeostasis. The presence of Ang II in ganglionic neurons of celiac, dorsal root, and trigeminal ganglia has only recently been described in humans and rats. Ang II-containing fibers were also found in the mesenteric artery and the heart, together with intrinsic Ang II-containing cardiac neurons. Ganglionic neurons express angiotensinogen and co-localize it with Ang II. Its intraneuronal production as a neuropeptide appears to involve angiotensinogen processing enzymes other than renin. Immunocytochemical and gene expression data suggest that neuronal Ang II acts as a neuromodulatory peptide and co-transmitter in the peripheral autonomic, and also sensory nervous system. Neuronal Ang II probably competes with humoral Ang II for effector cell activation. Its functional role, however, still remains to be determined. Angiotensinergic neurotransmission in the autonomic nervous system is a potential new target for therapeutic interventions in many common diseases such as essential hypertension, heart failure, and cardiac arrhythmia.

MyHits: a new interactive resource for protein annotation and domain identification.

The MyHits web server (http://myhits.isb-sib.ch) is a new integrated service dedicated to the annotation of protein sequences and to the analysis of their domains and signatures. Guest users can use the system anonymously, with full access to (i) standard bioinformatics programs (e.g. PSI-BLAST, ClustalW, T-Coffee, Jalview); (ii) a large number of protein sequence databases, including standard (Swiss-Prot, TrEMBL) and locally developed databases (splice variants); (iii) databases of protein motifs (Prosite, Interpro); (iv) a precomputed list of matches ('hits') between the sequence and motif databases. All databases are updated on a weekly basis and the hit list is kept up to date incrementally. The MyHits server also includes a new collection of tools to generate graphical representations of pairwise and multiple sequence alignments including their annotated features. Free registration enables users to upload their own sequences and motifs to private databases. These are then made available through the same web interface and the same set of analytical tools. Registered users can manage their own sequences and annotations using only web tools and freeze their data in their private database for publication purposes.

Recommender System Based on Consumer Product Reviews

Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

Acid sensing by the Drosophila olfactory system.

The odour of acids has a distinct quality that is perceived as sharp, pungent and often irritating. How acidity is sensed and translated into an appropriate behavioural response is poorly understood. Here we describe a functionally segregated population of olfactory sensory neurons in the fruitfly, Drosophila melanogaster, that are highly selective for acidity. These olfactory sensory neurons express IR64a, a member of the recently identified ionotropic receptor (IR) family of putative olfactory receptors. In vivo calcium imaging showed that IR64a+ neurons projecting to the DC4 glomerulus in the antennal lobe are specifically activated by acids. Flies in which the function of IR64a+ neurons or the IR64a gene is disrupted had defects in acid-evoked physiological and behavioural responses, but their responses to non-acidic odorants remained unaffected. Furthermore, artificial stimulation of IR64a+ neurons elicited avoidance responses. Taken together, these results identify cellular and molecular substrates for acid detection in the Drosophila olfactory system and support a labelled-line mode of acidity coding at the periphery.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Social and medical vulnerability factors of emergency department frequent users in a universal health insurance system.

OBJECTIVES: The objectives were to identify the social and medical factors associated with emergency department (ED) frequent use and to determine if frequent users were more likely to have a combination of these factors in a universal health insurance system. METHODS: This was a retrospective chart review case-control study comparing randomized samples of frequent users and nonfrequent users at the Lausanne University Hospital, Switzerland. The authors defined frequent users as patients with four or more ED visits within the previous 12 months. Adult patients who visited the ED between April 2008 and March 2009 (study period) were included, and patients leaving the ED without medical discharge were excluded. For each patient, the first ED electronic record within the study period was considered for data extraction. Along with basic demographics, variables of interest included social (employment or housing status) and medical (ED primary diagnosis) characteristics. Significant social and medical factors were used to construct a logistic regression model, to determine factors associated with frequent ED use. In addition, comparison of the combination of social and medical factors was examined. RESULTS: A total of 359 of 1,591 frequent and 360 of 34,263 nonfrequent users were selected. Frequent users accounted for less than a 20th of all ED patients (4.4%), but for 12.1% of all visits (5,813 of 48,117), with a maximum of 73 ED visits. No difference in terms of age or sex occurred, but more frequent users had a nationality other than Swiss or European (n = 117 [32.6%] vs. n = 83 [23.1%], p = 0.003). Adjusted multivariate analysis showed that social and specific medical vulnerability factors most increased the risk of frequent ED use: being under guardianship (adjusted odds ratio [OR] = 15.8; 95% confidence interval [CI] = 1.7 to 147.3), living closer to the ED (adjusted OR = 4.6; 95% CI = 2.8 to 7.6), being uninsured (adjusted OR = 2.5; 95% CI = 1.1 to 5.8), being unemployed or dependent on government welfare (adjusted OR = 2.1; 95% CI = 1.3 to 3.4), the number of psychiatric hospitalizations (adjusted OR = 4.6; 95% CI = 1.5 to 14.1), and the use of five or more clinical departments over 12 months (adjusted OR = 4.5; 95% CI = 2.5 to 8.1). Having two of four social factors increased the odds of frequent ED use (adjusted = OR 5.4; 95% CI = 2.9 to 9.9), and similar results were found for medical factors (adjusted OR = 7.9; 95% CI = 4.6 to 13.4). A combination of social and medical factors was markedly associated with ED frequent use, as frequent users were 10 times more likely to have three of them (on a total of eight factors; 95% CI = 5.1 to 19.6). CONCLUSIONS: Frequent users accounted for a moderate proportion of visits at the Lausanne ED. Social and medical vulnerability factors were associated with frequent ED use. In addition, frequent users were more likely to have both social and medical vulnerabilities than were other patients. Case management strategies might address the vulnerability factors of frequent users to prevent inequities in health care and related costs.

Vertical distributions of plankton in the upper 35m of the peruvian upwelling zone - application of a shipboard electronic plankton counting system

Analiza el proyecto ICANE y suma modificaciones para estudiar la distribución de zooplancton pequeño

Continuous arterial spin labeling of mouse cerebral blood flow using an actively-detuned two-coil system at 9.4T.

Among numerous magnetic resonance imaging (MRI) techniques, perfusion MRI provides insight into the passage of blood through the brain's vascular network non-invasively. Studying disease models and transgenic mice would intrinsically help understanding the underlying brain functions, cerebrovascular disease and brain disorders. This study evaluates the feasibility of performing continuous arterial spin labeling (CASL) on all cranial arteries for mapping murine cerebral blood flow at 9.4 T. We showed that with an active-detuned two-coil system, a labeling efficiency of 0.82 ± 0.03 was achieved with minimal magnetization transfer residuals in brain. The resulting cerebral blood flow of healthy mouse was 99 ± 26 mL/100g/min, in excellent agreement with other techniques. In conclusion, high magnetic fields deliver high sensitivity and allowing not only CASL but also other MR techniques, i.e. (1)H MRS and diffusion MRI etc, in studying murine brains.

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Automation in clinical bacteriology: what system to choose?

With increased activity and reduced financial and human resources, there is a need for automation in clinical bacteriology. Initial processing of clinical samples includes repetitive and fastidious steps. These tasks are suitable for automation, and several instruments are now available on the market, including the WASP (Copan), Previ-Isola (BioMerieux), Innova (Becton-Dickinson) and Inoqula (KIESTRA) systems. These new instruments allow efficient and accurate inoculation of samples, including four main steps: (i) selecting the appropriate Petri dish; (ii) inoculating the sample; (iii) spreading the inoculum on agar plates to obtain, upon incubation, well-separated bacterial colonies; and (iv) accurate labelling and sorting of each inoculated media. The challenge for clinical bacteriologists is to determine what is the ideal automated system for their own laboratory. Indeed, different solutions will be preferred, according to the number and variety of samples, and to the types of sample that will be processed with the automated system. The final choice is troublesome, because audits proposed by industrials risk being biased towards the solution proposed by their company, and because these automated systems may not be easily tested on site prior to the final decision, owing to the complexity of computer connections between the laboratory information system and the instrument. This article thus summarizes the main parameters that need to be taken into account for choosing the optimal system, and provides some clues to help clinical bacteriologists to make their choice.