Sensor Integration for Smart Cities Using Multi-Hop Networks

Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.

Hybrid link-state path-vector protocol ++

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores Mestrado Integrado em Engenharia Electrotécnica e de Computadores

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

Analysis of Synaptic Proteins in the Cerebrospinal Fluid as a New Tool in the Study of Inborn Errors of Neurotransmission

Abstract In a few rare diseases, specialised studies in cerebrospinal fluid (CSF) are required to identify the underlying metabolic disorder. We aimed to explore the possibility of detecting key synaptic proteins in the CSF, in particular dopaminergic and gabaergic, as new procedures that could be useful for both pathophysiological and diagnostic purposes in investigation of inherited disorders of neurotransmission. Dopamine receptor type 2 (D2R), dopamine transporter (DAT) and vesicular monoamine transporter type 2 (VMAT2) were analysed in CSF samplesfrom 30 healthy controls (11 days to 17 years) by western blot analysis. Because VMAT2 was the only protein with intracellular localisation, and in order to compare results, GABA vesicular transporter, which is another intracellular protein, was also studied. Spearman’s correlation and Student’s t tests were applied to compare optical density signals between different proteins. All these synaptic proteins could be easily detected and quantified in the CSF. DAT, D2R and GABA VT expression decrease with age, particularly in the first months of life, reflecting the expected intense synaptic activity and neuronal circuitry formation. A statistically significant relationship was found between D2R and DAT expression, reinforcing the previous evidence of DAT regulation by D2R. To our knowledge, there are no previous studies on human CSF reporting a reliable analysis of these proteins. These kinds of studies could help elucidate new causes of disturbed dopaminergic and gabaergic transmission as well as understanding different responses to L-dopa in inherited disorders affecting dopamine metabolism. Moreover, this approach to synaptic activity in vivo can be extended to different groups of proteins and diseases.

A framework for scientific computing with GPUs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Modeling assembly program with constraints. A contribution to WCET problem

Dissertação para obtenção do Grau de Mestre em Lógica Computacional

A learning approach to swarm-based path detection and tracking

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

EVIDENCE OF Leishmania (Leishmania) infantum INFECTION IN DOGS FROM JUIZ DE FORA, MINAS GERAIS STATE, BRAZIL, BASED ON IMMUNOCHROMATOGRAPHIC DUAL-PATH PLATFORM (DPP®) AND PCR ASSAYS

In Brazil, domestic dogs are branded as the primary reservoir for zoonotic visceral leishmaniasis, due to the clear positive correlation observed between human and canine infection rates. This study aimed to carry out a serological survey of canine visceral leishmaniasis (CVL) in dogs housed at a public kennel in the municipality of Juiz de Fora, Minas Gerais State, Brazil, using the immunochromatographic TR DPP® CVL rapid test. Additionally, conventional and/or real time PCR assay was used to detect and confirm L. infantum infection in the DPP positive dogs only. Of the 400 dogs studied, most did not present clinical signs for CVL (p < 0.05), and fifteen (3.8%) were seropositive in the DPP test. There was no statistically significant difference between the DPP seropositive dogs and the clinical signs of the disease (p > 0.05). Both conventional and real time PCR tests confirmed L. infantum infection in nine (75.0%) of the twelve DPP seropositive dogs that remained alive during the follow-up period. This study is the first seroepidemiologic survey of CVL held in the city of Juiz de Fora, and the results reinforce the idea that this disease is currently in a process of expansion and urbanization in Brazil. Furthermore, this study highlights the use of the DPP test as an alternative for diagnosing CVL in large and mid-sized cities, due to its ease of implementation.

Parallelization of web processing services on cloud computing: A case study of Geostatistical Methods

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

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Tradução, Adaptação e Validação da Escala Jones Dependency Tool

A avaliação do grau de dependência dos utentes é um dos aspectos que contribui para a melhoria dos cuidados, dado que permite uma melhor adequação dos recursos humanos às situações vivenciadas no quotidiano dos serviços de urgência. A carga de trabalho em enfermagem está estreitamente relacionada com o grau de dependência, pelo que a sua avaliação assume-se como um elemento fundamental numa politica de gestão de qualidade. Com o intuito de avaliar, numa fase inicial, o grau de dependência dos utentes que recorrem aos serviços de urgência foi criada uma escala – Jones Dependency Tool (JDT) – sendo que o objectivo major é a avaliação da carga de trabalho em Enfermagem relacionando com o grau de dependência dos utentes. O presente estudo visa traduzir, adaptar e validar para Portugal o referido instrumento. O estudo encontra-se dividido em duas partes. A primeira constituída pela tradução e adaptação cultural da JDT para língua portuguesa e a segunda, pela análise da fidelidade e da validade do instrumento. O processo de validação para a língua portuguesa ocorreu numa amostra de 129 utentes de dois serviços de urgência da região de lisboa. Através dos testes estatísticos realizados, a versão Portuguesa revelou-se um instrumento confiável e válido para a realização do grau de dependência dos utentes que recorrem ao serviço de urgência.

Biogenic amines in wine: gene transcription as a tool for selection of Oenococcus oeni starter strains

Dissertation presented to obtain the Ph.D degree in Biology