Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

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

Doctoral Program in Computer Science

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.

Secure multiParty computation protocols

Dissertação de Mestrado em Engenharia Informática

A spectrum-driven damage Identification technique : application and validation through the numerical simulation of the Z24 Bridge

The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.

Using the GPU to design complex profile extrusion dies

In the present work the benefits of using graphics processing units (GPU) to aid the design of complex geometry profile extrusion dies, are studied. For that purpose, a3Dfinite volume based code that employs unstructured meshes to solve and couple the continuity, momentum and energy conservation equations governing the fluid flow, together with aconstitutive equation, was used. To evaluate the possibility of reducing the calculation time spent on the numerical calculations, the numerical code was parallelized in the GPU, using asimple programing approach without complex memory manipulations. For verificationpurposes, simulations were performed for three benchmark problems: Poiseuille flow, lid-driven cavity flow and flow around acylinder. Subsequently, the code was used on the design of two real life extrusion dies for the production of a medical catheter and a wood plastic composite decking profile. To evaluate the benefits, the results obtained with the GPU parallelized code were compared, in terms of speedup, with a serial implementation of the same code, that traditionally runs on the central processing unit (CPU). The results obtained show that, even with the simple parallelization approach employed, it was possible to obtain a significant reduction of the computation times.

Induced magnetoelectric effect driven by magnetization in BaFe12O19 -/P(VDF-TrFE) composites

Films of BaFe12O19/P(VDF-TrFE) composites with 5, 10 and 20 %wt Barium ferrite content have been fabricated. BaFe12O19 microparticles have the shape of thin hexagonal platelets, the easy direction of magnetization remaining along the c axis, which is perpendicular to the plates. This fact allows for ferrite particles orientation in-plane and out-of-plane within the composite films, as confirmed by measured hysteresis loops. While the in-plane induced magnetoelectric effect (ME) is practically zero, these composite films show a good out-of-plane magnetoelectric effect. with maximum ME coupling coefficient changes of 3, 17 and 2 mV/cm.Oe for the 5, 10 and 20%wt Barium ferrite content films, respectively. We infer that this ME behavior appears as driven by the magnetization process arising when we applied the external magnetic field. We have also measured linear and reversible magnetoelectric effect for low applied bias field, when magnetization process is still reversible.

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.

Politically driven cycles in fiscal policy: in depth analysis of the functional components of government expenditures

NIPE - WP 02/2016

Platelet lysate-based pro-angiogenic nanocoatings

Human platelet lysate (PL) is a cost-effective and human source of autologous multiple and potent pro-angiogenic factors, such as vascular endothelial growth factor A (VEGF A), fibroblast growth factor b (FGF b) and angiopoietin-1. Nanocoatings previously characterized were prepared by layer-by-layer assembling incorporating PL with marine-origin polysaccharides and were shown to activate human umbilical vein endothelial cells (HUVECs). Within 20 h of incubation, the more sulfated coatings induced the HUVECS to the form tube-like structures accompanied by an increased expression of angiogenicassociated genes, such as angiopoietin-1 and VEGF A. This may be a cost-effective approach to modify 2D/3D constructs to instruct angiogenic cells towards the formation of neo-vascularization, driven by multiple and synergistic stimulations from the PL combined with sulfated polysaccharides. Statement of Significance The presence, or fast induction, of a stable and mature vasculature inside 3D constructs is crucial for new tissue formation and its viability. This has been one of the major tissue engineering challenges, limiting the dimensions of efficient tissue constructs. Many approaches based on cells, growth factors, 3D bioprinting and channel incorporation have been proposed. Herein, we explored a versatile technique, layer-by-layer assembling in combination with platelet lysate (PL), that is a cost-effective source of many potent pro-angiogenic proteins and growth factors. Results suggest that the combination of PL with sulfated polyelectrolytes might be used to introduce interfaces onto 2D/3D constructs with potential to induce the formation of cell-based tubular structures.

Embedding, evolution, and validation of model-driven spreadsheets

This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved.Finally,wehave designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)