Building anonymised database samples

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.

Mortality after Discharge from Intensive Care: the Impact of Organ System Failure and Nursing Workload Use at Discharge

OBJECTIVES: Mortality after ICU discharge accounts for approx. 20-30% of deaths. We examined whether post-ICU discharge mortality is associated with the presence and severity of organ dysfunction/failure just before ICU discharge. PATIENTS AND METHODS: The study used the database of the EURICUS-II study, with a total of 4,621 patients, including 2,958 discharged alive to the general wards (post-ICU mortality 8.6%). Over a 4-month period we collected clinical and demographic characteristics, including the Simplified Acute Physiology Score (SAPS II), Nine Equivalents of Nursing Manpower Use Score, and Sequential Organ Failure Assessment (SOFA) score. RESULTS: Those who died in the hospital after ICU discharge had a higher SAPS II score, were more frequently nonoperative, admitted from the ward, and had stayed longer in the ICU. Their degree of organ dysfunction/failure was higher (admission, maximum, and delta SOFA scores). They required more nursing workload resources while in the ICU. Both the amount of organ dysfunction/failure (especially cardiovascular, neurological, renal, and respiratory) and the amount of nursing workload that they required on the day before discharge were higher. The presence of residual CNS and renal dysfunction/failure were especially prognostic factors at ICU discharge. Multivariate analysis showed only predischarge organ dysfunction/failure to be important; thus the increased use of nursing workload resources before discharge probably reflects only the underlying organ dysfunction/failure. CONCLUSIONS: It is better to delay the discharge of a patient with organ dysfunction/failure from the ICU, unless adequate monitoring and therapeutic resources are available in the ward.

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.

The two-component system of a novel copper resistant operon of Marinobacter hydrocarbonoclasticus

Dissertation for the Master’s Degree in Structural and Functional Biochemistry

CMOS indoor light energy harvesting system for wireless sensing applications

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

Diving into the depth of primary motor cortex: a high-resolution investigation of the motor system using 7Tesla fMRI

Dissertação para a obtenção do Grau de Mestre em Engenharia Biomédica

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Integration of a mobile autonomous robot in a surveillance multi-agent system

This dissertation aims to guarantee the integration of a mobile autonomous robot equipped with many sensors in a multi-agent distributed and georeferenced surveillance system. The integration of a mobile autonomous robot in this system leads to new features that will be available to clients of surveillance system may use. These features may be of two types: using the robot as an agent that will act in the environment or by using the robot as a mobile set of sensors. As an agent in the system, the robot can move to certain locations when alerts are received, in order to acknowledge the underlying events or take to action in order to assist in resolving this event. As a sensor platform in the system, it is possible to access information that is read from the sensors of the robot and access complementary measurements to the ones taken by other sensors in the multi-agent system. To integrate this mobile robot in an effective way it is necessary to extend the current multi-agent system architecture to make the connection between the two systems and to integrate the functionalities provided by the robot into the multi-agent system.

A piezoelectric based energy harvester interface for a CMOS wireless sensor IC

In this thesis a piezoelectric energy harvesting system, responsible for regulating the power output of a piezoelectric transducer subjected to ambient vibration, is designed to power an RF receiver with a 6 mW power consump-tion. The electrical characterisation of the chosen piezoelectric transducer is the starting point of the design, which subsequently presents a full-bridge cross-coupled rectifier that rectifies the AC output of the transducer and a low-dropout regulator responsible for delivering a constant voltage system output of 0.6 V, with low voltage ripple, which represents the receiver’s required sup-ply voltage. The circuit is designed using CMOS 130 nm UMC technology, and the system presents an inductorless architecture, with reduced area and cost. The electrical simulations run for the complete circuit lead to the conclusion that the proposed piezoelectric energy harvesting system is a plausible solution to power the RF receiver, provided that the chosen transducer is subjected to moderate levels of vibration.

Design of a low-voltage CMOS RF receiver for energy harvesting sensor node

In this thesis a CMOS low-power and low-voltage RF receiver front-end is presented. The main objective is to design this RF receiver so that it can be powered by a piezoelectric energy harvesting power source, included in a Wireless Sensor Node application. For this type of applications the major requirements are: the low-power and low-voltage operation, the reduced area and cost and the simplicity of the architecture. The system key blocks are the LNA and the mixer, which are studied and optimized with greater detail, achieving a good linearity, a wideband operation and a reduced introduction of noise. A wideband balun LNA with noise and distortion cancelling is designed to work at a 0.6 V supply voltage, in conjunction with a double-balanced passive mixer and subsequent TIA block. The passive mixer operates in current mode, allowing a minimal introduction of voltage noise and a good linearity. The receiver analog front-end has a total voltage conversion gain of 31.5 dB, a 0.1 - 4.3 GHz bandwidth, an IIP3 value of -1.35 dBm, and a noise figure lower than 9 dB. The total power consumption is 1.9 mW and the die area is 305x134.5 m2, using a standard 130 nm CMOS technology.

Prospective system analysis of stationary battery systems under the frame of Constructive Technology Assessment

Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.

PV systems linked to the grid: parameter identification with a heuristic procedure

This paper focuses on a PV system linked to the electric grid by power electronic converters, identification of the five parameters modeling for photovoltaic systems and the assessment of the shading effect. Normally, the technical information for photovoltaic panels is too restricted to identify the five parameters. An undemanding heuristic method is used to find the five parameters for photovoltaic systems, requiring only the open circuit, maximum power, and short circuit data. The I–V and the P–V curves for a monocrystalline, polycrystalline and amorphous photovoltaic systems are computed from the parameters identification and validated by comparison with experimental ones. Also, the I–V and the P–V curves under the effect of partial shading are obtained from those parameters. The modeling for the converters emulates the association of a DC–DC boost with a two-level power inverter in order to follow the performance of a testing commercial inverter employed on an experimental system.

Video metadata extraction in a videoMail system

Currently the world swiftly adapts to visual communication. Online services like YouTube and Vine show that video is no longer the domain of broadcast television only. Video is used for different purposes like entertainment, information, education or communication. The rapid growth of today’s video archives with sparsely available editorial data creates a big problem of its retrieval. The humans see a video like a complex interplay of cognitive concepts. As a result there is a need to build a bridge between numeric values and semantic concepts. This establishes a connection that will facilitate videos’ retrieval by humans. The critical aspect of this bridge is video annotation. The process could be done manually or automatically. Manual annotation is very tedious, subjective and expensive. Therefore automatic annotation is being actively studied. In this thesis we focus on the multimedia content automatic annotation. Namely the use of analysis techniques for information retrieval allowing to automatically extract metadata from video in a videomail system. Furthermore the identification of text, people, actions, spaces, objects, including animals and plants. Hence it will be possible to align multimedia content with the text presented in the email message and the creation of applications for semantic video database indexing and retrieving.

Injuries caused by aquatic animals in Brazil: an analysis of the data present in the information system for notifiable diseases

AbstractINTRODUCTION:We present a review of injuries in humans caused by aquatic animals in Brazil using the Information System for Notifiable Diseases [ Sistema de Informação de Agravos de Notificação (SINAN)] database.METHODS:A descriptive and retrospective epidemiological study was conducted from 2007 to 2013.RESULTS:A total of 4,118 accidents were recorded. Of these accidents, 88.7% (3,651) were caused by venomous species, and 11.3% (467) were caused by poisonous, traumatic or unidentified aquatic animals. Most of the events were injuries by stingrays (69%) and jellyfish (13.1%). The North region was responsible for the majority of reports (66.2%), with a significant emphasis on accidents caused by freshwater stingrays (92.2% or 2,317 cases). In the South region, the region with the second highest number of records (15.7%), jellyfish caused the majority of accidents (83.7% or 452 cases). The Northeastern region, with 12.5% of the records, was notable because almost all accidents were caused by toadfish (95.6% or 174 cases).CONCLUSIONS:Although a comparison of different databases has not been performed, the data presented in this study, compared to local and regional surveys, raises the hypothesis of underreporting of accidents. As the SINAN is the official system for the notification of accidents by venomous animals in Brazil, it is imperative that its operation be reviewed and improved, given that effective measures to prevent accidents by venomous animals depend on a reliable database and the ability to accurately report the true conditions.