Developing an aquaponics system to learn sustainability and social compromise skills

The goal of this project, one of the proposals of the EPS@ISEP Spring 2014, was to develop an Aquaponics System. Over recent years Aquaponics systems have received increased attention since they contribute to reduce the strain on resources within 1st and 3rd world countries. Aquaponics is the combination of Hydroponics and Aquaculture, mimicking a natural environment in order to successfully apply and enhance the understanding of natural cycles within an indoor process. Using this knowledge of natural cycles, it was possible to create a system with capabilities similar to that of a natural environment with the support of electronics, enhancing the overall efficiency of the system. The multinational team involved in the development of this system was composed of five students from five countries and fields of study. This paper describes their solution, including the overall design, the technology involved and the benefits it can bring to the current market. The team was able to design and render the Computer Aided Design (CAD) drawings of the prototype, assemble all components, successfully test the electronics and comply with the budget. Furthermore, the designed solution was supported by a product sustainability study and included a specific marketing plan. Last but not least, the students enrolled in this project obtained new multidisciplinary knowledge and increased their team work and cross-cultural communication skills.

Proactive services ecosystem framework

Dissertation presented to obtain the degree of Doctor in Electrical and Computer Engineering, specialization on Collaborative Enterprise Networks

Brain-computer interface (BCI): a methodological proposal to assess the impacts of medical applications in 2022

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).

Characterization and surface reconstruction of objects in tomographic images of composite materials

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Development and modulation of magnetic responsive supported ionic liquid membranes

The work presented in this thesis aims at developing a new separation process based on the application of supported magnetic ionic liquid membranes, SMILMs, using magnetic ionic liquids, MILs. MILs have attracted growing interest due to their ability to change their physicochemical characteristics when exposed to variable magnetic field conditions. The magnetic responsive behavior of MILs is thus expected to contribute for the development of more efficient separation processes, such as supported liquid membranes, where MILs may be used as a selective carrier. Driven by the MILs behavior, these membranes are expected to switch reversibly their permeability and selectivity by in situ and non-invasive adjustment of the conditions (e.g. intensity, direction vector and uniformity) of an external applied magnetic field. The development of these magnetic responsive membrane processes were anticipated by studies, performed along the first stage of this PhD work, aiming at getting a deep knowledge on the influence of magnetic field on MILs properties. The influence of the magnetic field on the molecular dynamics and structural rearrangement of MILs ionic network was assessed through a 1H-NMR technique. Through the 1H-NMR relaxometry analysis it was possible to estimate the self-diffusion profiles of two different model MILs, [Aliquat][FeCl4] and [P66614][FeCl4]. A comparative analysis was established between the behavior of magnetic and non-magnetic ionic liquids, MILs and ILs, to facilitate the perception of the magnetic field impact on MILs properties. In contrast to ILs, MILs show a specific relaxation mechanism, characterized by the magnetic dependence of their self-diffusion coefficients. MILs self-diffusion coefficients increased in the presence of magnetic field whereas ILs self-diffusion was not affected. In order to understand the reasons underlying the magnetic dependence of MILs self-diffusion, studies were performed to investigate the influence of the magnetic field on MILs’ viscosity. It was observed that the MIL´s viscosity decreases with the increase of the magnetic field, explaining the increase of MILs self-diffusion according to the modified Stokes- Einstein equation. Different gas and liquid transport studies were therefore performed aiming to determine the influence of the magnetic behavior of MILs on solute transport through SMILMs. Gas permeation studies were performed using pure CO2 andN2 gas streams and air, using a series of phosphonium cation based MILs, containing different paramagnetic anions. Transport studies were conducted in the presence and absence of magnetic field at a maximum intensity of 1.5T. The results revealed that gas permeability increased in the presence of the magnetic field, however, without affecting the membrane selectivity. The increase of gas permeability through SMILMs was related to the decrease of the MILs viscosity under magnetic field conditions.(...)

A data-driven analytics approach in the study of pneumonia’s fatalities

As huge amounts of data become available in organizations and society, specific data analytics skills and techniques are needed to explore this data and extract from it useful patterns, tendencies, models or other useful knowledge, which could be used to support the decision-making process, to define new strategies or to understand what is happening in a specific field. Only with a deep understanding of a phenomenon it is possible to fight it. In this paper, a data-driven analytics approach is used for the analysis of the increasing incidence of fatalities by pneumonia in the Portuguese population, characterizing the disease and its incidence in terms of fatalities, knowledge that can be used to define appropriate strategies that can aim to reduce this phenomenon, which has increased more than 65% in a decade.

Detection of road accident accumulation zones with a visual analytics approach

Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

The human eye as human-machine interface

Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Thermal conditions affecting heat transfer in FDM/FFE: a contribution towards the numerical modelling of the process

The performance of parts produced by Free Form Extrusion (FFE), an increasingly popular additive manufacturing technique, depends mainly on their dimensional accuracy, surface quality and mechanical performance. These attributes are strongly influenced by the evolution of the filament temperature and deformation during deposition and solidification. Consequently, the availability of adequate process modelling software would offer a powerful tool to support efficient process set-up and optimisation. This work examines the contribution to the overall heat transfer of various thermal phenomena developing during the manufacturing sequence, including convection and radiation with the environment, conduction with support and between adjacent filaments, radiation between adjacent filaments and convection with entrapped air. The magnitude of the mechanical deformation is also studied. Once this exercise is completed, it is possible to select the material properties, process variables and thermal phenomena that should be taken in for effective numerical modelling of FFE.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

An interactive web-based tool for breast reduction surgery simulation

In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.