Vision-based hand Wheel-chair control

Several studies have shown that people with disabilities benefit substantially from access to a means of independent mobility and assistive technology. Researchers are using technology originally developed for mobile robots to create easier to use wheelchairs. With this kind of technology people with disabilities can gain a degree of independence in performing daily life activities. In this work a computer vision system is presented, able to drive a wheelchair with a minimum number of finger commands. The user hand is detected and segmented with the use of a kinect camera, and fingertips are extracted from depth information, and used as wheelchair commands.

Zeolite-based nanomaterials for the control of opportunistic pathogenic microorganisms

Dissertação de mestrado em Applied Biochemistry (área de especialização em Biomedicine)

A UML-based approach for modeling industrial control applications

The main purpose of the poster is to present how the Unified Modeling Language (UML) can be used for diagnosing and optimizing real industrial production systems. By using a car radios production line as a case study, the poster shows the modeling process that can be followed during the analysis phase of complex control applications. In order to guarantee the continuity mapping of the models, the authors propose some guidelines to transform the use cases diagrams into a single object diagram, which is the main diagram for the next phases of the development.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.

FPGA field oriented control of an axial flux motor-in-wheel

This paper presents the design and the prototype implementation of a three-phase power inverter developed to drive a motor-in-wheel. The control system is implemented in a FPGA (Field Programmable Gate Array) device. The paper describes the Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique that were implemented. The control platform uses a Spartan-3E FPGA board, programmed with Verilog language. Simulation and experimental results are presented to validate the developed system operation under different load conditions. Finally are presented conclusions based on the experimental results.

Predictive control of a current-source inverter for solar photovoltaic grid interface

Solar photovoltaic systems are an increasing option for electricity production, since they produce electrical energy from a clean renewable energy resource, and over the years, as a result of the research, their efficiency has been increasing. For the interface between the dc photovoltaic solar array and the ac electrical grid is necessary the use of an inverter (dc-ac converter), which should be optimized to extract the maximum power from the photovoltaic solar array. In this paper is presented a solution based on a current-source inverter (CSI) using continuous control set model predictive control (CCS-MPC). All the power circuits and respective control systems are described in detail along the paper and were tested and validated performing computer simulations. The paper shows the simulation results and are drawn several conclusions.

A FEM-based model to study the behaviour of corroded RC beams shear repaired by NSM CFRP rods technique

This paper presents the main features of finite element FE numerical model developed using the computer code FEMIX to predict the near-surface mounted NSM carbon-fiber-reinforced polymer CFRP rods shear repair contribution to corroded reinforced concrete RC beams. In the RC beams shear repaired with NSM technique, the Carbon Fibre Reinforced Polymer (CFRP) rods are placed inside pre-cut grooves onto the concrete cover of the RC beam’s lateral faces and are bonded to the concrete with high epoxy adhesive. Experimental and 3D numerical modelling results are presented in this paper in terms of load-deflection curves, and failure modes for 4 short corroded beams: two corroded beams (A1CL3-B and A1CL3-SB) and two control beams (A1T-B and A1T-SB), the beams noted with B were let repaired in bending only with NSM CFRP rods while the ones noted with SB were repaired in both bending and shear with NSM technique. The corrosion of the tensile steel bars and its effect on the shear capacity of the RC beams was discussed. Results showed that the FE model was able to capture the main aspects of the experimental load-deflection curves of the RC beams, moreover it has presented the experimental failure modes and FE numerical modelling crack patterns and both gave similar results for non-shear repaired beams which failed in diagonal tension mode of failure and for shear-repaired beams which failed due to large flexural crack at the middle of the beams along with the concrete crushing, three dimensional crack patterns were produced for shear-repaired beams in order to investigate the splitting cracks occurred at the middle of the beams and near the support.

A FEM-based model to study the behaviour of corroded RC beams shear repaired by NSM CFRP rods technique

This paper presents the main features of finite element FE numerical model developed using the computer code FEMIX to predict the near-surface mounted NSM carbon-fiber-reinforced polymer CFRP rods shear repair contribution to corroded reinforced concrete RC beams. In the RC beams shear repaired with NSM technique, the Carbon Fibre Reinforced Polymer (CFRP) rods are placed inside pre-cut grooves onto the concrete cover of the RC beam’s lateral faces and are bonded to the concrete with high epoxy adhesive. Experimental and 3D numerical modelling results are presented in this paper in terms of load-deflection curves, failure modes and slip information of the tensile steel bars for 4 short corroded beams: two corroded beams (A1CL3-B and A1CL3-SB) and two control beams (A1T-B and A1T-SB), the beams noted with B were let repaired in bending only with NSM CFRP rods while the ones noted with SB were repaired in both bending and shear with NSM technique. The corrosion of the tensile steel bars and its effect on the shear capacity of the RC beams was discussed. Results showed that the FE model was able to capture the main aspects of the experimental load-deflection curves of the RC beams, moreover it has presented the experimental failure modes and FE numerical modelling crack patterns and both gave similar results for non-shear repaired beams which failed in diagonal tension mode of failure and for shear-repaired beams which failed due to large flexural crack at the middle of the beams along with the concrete crushing, three dimensional crack patterns were produced for shear-repaired beams in order to investigate the splitting cracks occurred at the middle of the beams and near the support.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

[Letter to the editor] Sustained effects of a neural-based intervention in a refractory case of Tourette syndrome

There are only a few treatments available for Tourette syndrome (TS). These treatments frequently do notwork in patients with moderate to severe TS [1]. Neuroimaging studies show a correlation between tics severity and increased activation over motor pathways, along with reduced activation over the control areas of the cortico-striato-thalamo-cortical circuits [2]. Moreover, the temporal pattern of tic generation suggests that cortical activation especially in the SMA precedes subcortical activation [3]. Following this assumption, here we explored the brain effects of 10-daily sessions of cathodal transcranial Direct Current Stimulation (tDCS) delivered over the pre-SMA in a patient with refractory and severe TS and also assessed whether those changes were long lasting (up to 6 months).

Development and characterization of lipid-based nanosystems for controlled release of bioactive compounds

Tese de Doutoramento em Engenharia Química e Biológica.

Recommendations on quality control and quality assurance in cervical cytology

Objective: We aimed to critically evaluate the importance of quality control (QC) and quality assurance (QA) strategies in the routine work of uterine cervix cytology. Study Design: We revised all the main principles of QC and QA that are already being implemented worldwide and then discussed the positive aspects and limitations of these as well as proposing alternatives when pertinent. Results: A literature review was introduced after highlighting the main historical revisions, and then a critical evaluation of the principal innovations in screening programmes was conducted, with recommendations being postulated. Conclusions: Based on the analysed data, QC and QA are two essential arms that support the quality of a screening programme.