A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

Produtos têxteis inteligentes incorporando filamentos compósitos com nanotubos de carbono

Programa Doutoral em Engenharia Têxtil.

Towards effective control of P2P traffic aggregates in network infrastructures

Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Ag-TiNx electrodes deposited on piezoelectric poly(vinylidene fluoride) for biomedical sensor applications

Electroactive polymers are one of the most interesting class of polymers used as smart materials in various applications, such as the development of sensors and actuators for biomedical applications in areas such as smart prosthesis, implantable biosensors and biomechanical signal monitoring, among others. For acquiring or applying the electrical signal from/to the piezoelectric material, suitable electrodes can be produced from Ti based coatings with tailored multifunctional properties, conductivity and antibacterial characteristics, through Ag inclusions. This work reports on Ag-TiNx electrodes, deposited by d. c. and pulsed magnetron sputtering at room temperature on poly(vinylidene fluoride), PVDF, the all-round best piezoelectric polymer.. Composition of the electrodes was assessed by microanalysis X-ray system (EDS - energy dispersive spectrometer). The XRD results revealed that the deposition conditions preserve the polymer structure and suggested the presence of crystalline fcc-TiN phase and fcc-Ag phase in samples with N2 flow above 3 sccm. According to the results obtained from SEM analysis, the coatings are homogeneous and Ag clusters were found for samples with nitrogen flow above 3 sccm. With increasing nitrogen flow, the sheet resistivity tend to be lower than the samples without nitrogen, leading also to a decrease of the piezoelectric response. It is concluded that the deposition conditions do significantly affect the piezoelectric polymer, which maintain its characteristics for sensor/actuator applications.

Structural, mechanical and piezoelectric properties of polycrystalline AlN films sputtered on titanium bottom electrodes

Polycrystalline AlN coatings deposited on Ti-electrodes films were sputtered by using nitrogen both as reactive gas and sputtering gas, in order to obtain high purity coatings with appropriate properties to be further integrated into wear resistance coatings as a piezoelectric monitoring wear sensor. The chemical composition, the structure and the morphology of the films were investigated by X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy and atomic force microscopy techniques. These measurements show the formation of highly (101), (102) and (103) oriented AlN films with good piezoelectric and mechanical properties suitable for applications in electronic devices. Through the use of lower nitrogen flow a densification of the AlN coating occurs in the microstructure, with an improvement of the crystallinity along with the increase of the hardness. Thermal stability of aluminum nitride coatings at high temperature was also examined. It was found an improvement of the piezoelectric properties of the highly (10x) oriented AlN films which became c-axis (002) oriented after annealing. The mechanical behavior after heat treatment shows an important enhancement of the surface hardness and Young’s modulus, which decrease rapidly with the increase of the indentation depth until approach constant values close to the substrate properties after annealing. Thus, thermal annealing energy promotes not only the rearrangement of Al–N network, but also the occurrence of a nitriding process of unsaturated Al atoms which cause a surface hardening of the film.

Towards "green" smart materials for force and strain sensors: The case of polyaniline

Stress/strain sensors constitute a class of devices with a global ever-growing market thanks to their use in many fields of modern life. They are typically constituted by thin metal foils deposited on flexible supports. However, the low inherent resistivity and limited flexibility of their constituents make them inadequate for several applications, such as measuring large movements in robotic systems and biological tissues. As an alternative to the traditional compounds, in the present work we will show the advantages to employ a smart material, polyaniline (PANI), prepared by an innovative environmentally friendly route, for force/strain sensor applications wherein simple processing, environmental friendliness and sensitivity are particularly required.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Sensory intensity assessment of olive oils using an electronic tongue

Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

Monitorização e controlo em ambientes industriais através de rede de sensores sem fios

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

Sistema de visão robótico baseado no sensor kinect para orientação no espaço e contorno de obstáculos

Dissertação de mestrado em Engenharia Eletrónica Industrial e Computadores (área de especialização em Robótica)