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.

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.

A new empirical system for rock slope stability analysis in exploitation stage

An empirical system was developed to obtain a quality index for rock slopes in road infrastructures, named Slope Quality Index (SQI), and it was applied to a set of real slopes.The SQI is supported in nine factors affecting slope stability that contemplate the evaluation of different parameters. Consequently, each factor is classified by the degree of importance and influence by assigned weights. These weights were established through a statistical analysis of replies to a survey that was distributed to several experienced professionals in the field. The proposed SQI varies between1 and 5, corresponding to slopes in very good and very bad condition state, respectively. Besides the advantage linked to a quantitative and qualitative evaluation of slopes, theSQI also allows identifying the most critical factors on the slope stability, which is a fundamental issue for an efficient management of the slope network in the road infrastructure, namely in the planning of conservation and maintenance operations.

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.

Simulation of a rectifier malfunction on a offshore wind system with HVDC transmission

A new integrated mathematical model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase is presented in this paper. The mathematical model considers an offshore variable-speed wind turbine on a floating platform, equipped with a permanent magnet synchronous generator using full-power three-level converter to inject energy into the electric network, through a high voltage direct current transmission submarine cable. The model for the drive train is a discrete three mass, incorporating the dynamic of the moving surface. A case study is presented to access conclusion about the malfunction.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.