An agent-based evolutionary approach for manufacturing system layout design

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

PCR-based identification of Burkholderia pseudomallei

DNA amplification techniques are being used increasingly in clinical laboratories to confirm the identity of medically important bacteria. A PCR-based identification method has been in use in our centre for 10 years for Burkholderia pseudomallei and was used to confirm the identity of bacteria isolated from cases of melioidosis in Ceará since 2003. This particular method has been used as a reference standard for less discriminatory methods. In this study we evaluated three PCR-based methods of B. pseudomallei identification and used DNA sequencing to resolve discrepancies between PCR-based results and phenotypic identification methods. The established semi-nested PCR protocol for B. pseudomallei 16-23s spacer region produced a consistent negative result for one of our 100 test isolates (BCC #99), but correctly identified all 71 other B. pseudomallei isolates tested. Anomalous sequence variation was detected at the inner, reverse primer binding site for this method. PCR methods were developed for detection of two other B. pseudomallei bacterial metabolic genes. The conventional lpxO PCR protocol had a sensitivity of 0.89 and a specificity of 1.00, while a real-time lpxO protocol performed even better with sensitivity and specificity of 1.00, and 1.00. This method identified all B. pseudomallei isolates including the PCR-negative discrepant isolate. The phaC PCR protocol detected the gene in all B. pseudomallei and all but three B. cepacia isolates, making this method unsuitable for PCR-based identification of B. pseudomallei. This experience with PCR-based B. pseudomallei identification methods indicates that single PCR targets should be used with caution for identification of these bacteria, and need to be interpreted alongside phenotypic and alternative molecular methods such as gene sequencing.

Molecular screening of Plasmodium sp. asymptomatic carriers among transfusion centers from Brazilian Amazon region

The transmission of malaria in Brazil is heterogeneous throughout endemic areas and the presence of asymptomatic Plasmodium sp. carriers (APCs) in the Brazilian Amazon has already been demonstrated. Malaria screening in blood banks is based on the selection of donors in respect to possible risks associated with travel or residence, clinical evidence and/or inaccurate diagnostic methods thereby increasing the probability of transfusion-transmitted infection. We evaluated the frequency of APCs in four blood services in distinct areas of the Brazilian Amazon region. DNA was obtained from 400 human blood samples for testing using the phenol-chloroform method followed by a nested-PCR protocol with species-specific primers. The positivity rate varied from 1 to 3% of blood donors from the four areas with an average of 2.3%. All positive individuals had mixed infections for Plasmodium vivax and Plasmodium falciparum. No significant differences in the results were detected among these areas; the majority of cases originated from the transfusion centres of Porto Velho, Rondônia State and Macapá, Amapá State. Although it is still unclear whether APC individuals may act as reservoirs of the parasite, efficient screening of APCs and malaria patients in Brazilian blood services from endemic areas needs to be improved.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Tuning metadata for better movie content-based recommendation systems

The increasing number of television channels, on-demand services and online content, is expected to contribute to a better quality of experience for a costumer of such a service. However, the lack of efficient methods for finding the right content, adapted to personal interests, may lead to a progressive loss of clients. In such a scenario, recommendation systems are seen as a tool that can fill this gap and contribute to the loyalty of users. Multimedia content, namely films and television programmes are usually described using a set of metadata elements that include the title, a genre, the date of production, and the list of directors and actors. This paper provides a deep study on how the use of different metadata elements can contribute to increase the quality of the recommendations suggested. The analysis is conducted using Netflix and Movielens datasets and aspects such as the granularity of the descriptions, the accuracy metric used and the sparsity of the data are taken into account. Comparisons with collaborative approaches are also presented.

Sectorization: measures and an electromagnetism based approach

Sectorization means dividing a set of basic units into sectors or parts, a procedure that occurs in several contexts, such as political, health and school districting, social networks and sales territory or airspace assignment, to achieve some goal or to facilitate an activity. This presentation will focus on three main issues: Measures, a new approach to sectorization problems and an application in waste collection. When designing or comparing sectors different characteristics are usually taken into account. Some are commonly used, and they are related to the concepts of contiguity, equilibrium and compactness. These fundamental characteristics will be addressed, by defining new generic measures and by proposing a new measure, desirability, connected with the idea of preference. A new approach to sectorization inspired in Coulomb’s Law, which establishes a relation of force between electrically charged points, will be proposed. A charged point represents a small region with specific characteristics/values creating relations of attraction/repulsion with the others (two by two), proportional to the charges and inversely proportional to their distance. Finally, a real case about sectorization and vehicle routing in solid waste collection will be mentioned.

SHõWA: A Self-healing Framework for Web-based Applications

The complexity of systems is considered an obstacle to the progress of the IT industry. Autonomic computing is presented as the alternative to cope with the growing complexity. It is a holistic approach, in which the systems are able to configure, heal, optimize, and protect by themselves. Web-based applications are an example of systems where the complexity is high. The number of components, their interoperability, and workload variations are factors that may lead to performance failures or unavailability scenarios. The occurrence of these scenarios affects the revenue and reputation of businesses that rely on these types of applications. In this article, we present a self-healing framework for Web-based applications (SHõWA). SHõWA is composed by several modules, which monitor the application, analyze the data to detect and pinpoint anomalies, and execute recovery actions autonomously. The monitoring is done by a small aspect-oriented programming agent. This agent does not require changes to the application source code and includes adaptive and selective algorithms to regulate the level of monitoring. The anomalies are detected and pinpointed by means of statistical correlation. The data analysis detects changes in the server response time and analyzes if those changes are correlated with the workload or are due to a performance anomaly. In the presence of per- formance anomalies, the data analysis pinpoints the anomaly. Upon the pinpointing of anomalies, SHõWA executes a recovery procedure. We also present a study about the detection and localization of anomalies, the accuracy of the data analysis, and the performance impact induced by SHõWA. Two benchmarking applications, exercised through dynamic workloads, and different types of anomaly were considered in the study. The results reveal that (1) the capacity of SHõWA to detect and pinpoint anomalies while the number of end users affected is low; (2) SHõWA was able to detect anomalies without raising any false alarm; and (3) SHõWA does not induce a significant performance overhead (throughput was affected in less than 1%, and the response time delay was no more than 2 milliseconds).

Ten years experience with Jorge Lobo's disease in the state of Acre, Amazon region, Brazil

Jorge Lobo's disease is a cutaneous and subcutaneous mycosis that affects patients in the Amazon region. The number of patients is relatively small, but the real situation of the disease as public health problem is not known, because Jorge Lobo's disease is not a notifiable disease. This study aims to report the clinical evolution in patients affected and to determine the prevalence and areas of occurrence of the disease. A retrospective study was carried out based on the analysis of the clinical records, which included a collection of photographs of patients in the Department of Sanitary Dermatology, in Rio Branco, and patients seen in the interior of the state. In a decade, in Rio Branco, 249 cases of the disease were reported, 30 were females and 219 males. Of these patients, 153 had localized lesions, 94 of them were on one ear, 55 had multifocal lesions and 41 had disseminated lesions. The average time between the onset of symptoms and diagnosis was 19 years. The average age at the time of diagnosis was 53 years, and ages ranged from 14 to 96 years.

Contributions for best practices in social recruitment: pilot study in the Northern Region of Portugal

Recruitment is based on a conglomerate of techniques and procedures put in place to attract qualified. The recruitment process has suffered changes, becoming even more sophisticated, involving a whole organisation and a whole community. A new source of recruitment has emerged with the use of online social networks using facilitators in its development and usage, allowing the search for candidates to be fast, cheap and "global". In Portugal, the information available and studies conducted into this phenomenon are still irrelevant, with little reported on the importance of online social recruitment. The purpose of this article is to contribute to what is understood by the professional process of recruitment through online social media by recruitment companies in the Northern Region of Portugal, analysing the use of online media by recruitment professionals, facilitator support tools and the associated best practices.

Algorithms for information extraction and signal annotation on long-term biosignals using clustering techniques

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

A qualitive reasoning approach for improving query results for sketch based queries by topological analysis of spatial aggregation

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

Landslide susceptibility assessment in Karanganyar regency - Indonesia - Comparison of knowledge-based and Data-driven Models

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

Robust facial expression analysis for affect-based interaction

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

HIV AND HCV COINFECTION: PREVALENCE, ASSOCIATED FACTORS AND GENOTYPE CHARACTERIZATION IN THE MIDWEST REGION OF BRAZIL

A cross-sectional study on prevalence, associated factors and genotype distribution of HCV infection was conducted among 848 HIV-infected patients recruited at reference centers in the Midwest Region of Brazil. The prevalence rate of HIV-HCV coinfection was 6.9% (95% CI: 5.2 to 8.6). In multivariable analysis, increasing age, use of illicit drugs (injection and non-injection), a history of blood transfusion before 1994, and the absence of a steady partnership were significant independent associated factors for HIV-HCV coinfection. The phylogenetic analysis based on the NS5B region revealed the presence of two major circulating genotypes of HCV: genotypes 1 (58.3%) and 3 (41.7%). The prevalence of HIV-HCV coinfection was lower than those reported in studies conducted with HIV-infected patients in different regions of Brazil, due to the fact that illicit drug use is not a frequent mode of HIV transmission in this region of Brazil. Serologic screening of HIV-patients for HCV before initiating antiretroviral treatment, a comprehensive identification of associated factors, and the implementation of effective harm reduction programs are highly recommended to provide useful information for treatment and to prevent HCV coinfection in these patients.

Implementation of an IoT-based Sensor Network Integrating IoT-based Sensor Networks with Large-Scale Message Distribution

As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.