Methodology for enterprise interoperability assessment

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Study of multi-component systems in polybenzimidazole membrane formation and their impact on membrane performance

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Assessing self-organization and emergence in Evolvable Assembly Systems (EAS)

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Lightweight robust behavior industrial agent methodology

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Biological effects of acrylic engineered particulate-systems

Polymeric particulate-systems are of great relevance due to their possible biomedical applications, among them as carriers for the nano- or microencapsulation of drugs. However, due to their unique specific properties, namely small size range, toxicity issues must be discarded before allowing its use on health-related applications. Several polymers, as poly(methyl methacrylate) (PMMA), have proved to be suitable for the preparation of particulate-systems. However, a major drawback of its use refers to incomplete drug release from particles matrix. Recent strategies to improve PMMA release properties mention the inclusion of other acrylic polymers as Eudragit (EUD) on particles formulation. Though PMMA and EUD are accepted by the FDA as biocompatible, their safety on particle composition lacks sufficient toxicological data. The main objective of this thesis was to evaluate the biological effects of engineered acrylic particulate-systems. Preparation, physicochemical characterization and in vitro toxicity evaluation were assessed on PMMA and PMMA-EUD (50:50) particles. The emulsification-solvent evaporation methodology allowed the preparation of particles with spherical and smooth surfaces within the micrometer range (±500 nm), opposing surface charges and different levels of hydrophobicity. It was observed that particles physicochemical properties (size and charge) were influenced by biological media composition, such as serum concentration, ionic strength or pH. In what concerns to the in vitro toxicological studies, particle cellular uptake was observed on different cell lines (macrophages, osteoblasts and fibroblasts). Cytotoxicity effects were only found after 72 h of cells exposure to the particles, while no oxidative damage was observed neither on osteoblasts nor fibroblasts. Also, no genotoxicity was found in fibroblast using the comet assay to assess DNA damage. This observation should be further confirmed with other validated genotoxicity assays (e.g. Micronucleus Assay). The present study suggests that the evaluated acrylic particles are biocompatible, showing promising biological properties for potential use as carriers in drug-delivery systems.

Indoor location-based analytics systems: Portuguese market compettive assessment and entry procing strategy of BIPs' technology in Sonae Sierra Shopping malls stores

This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.

Antioxidant extraction process for Andean Oca by a photodiode array detector using response surface methodology

Application of Experimental Design techniques has proven to be essential in various research fields, due to its statistical capability of processing the effect of interactions among independent variables, known as factors, in a system’s response. Advantages of this methodology can be summarized in more resource and time efficient experimentations while providing more accurate results. This research emphasizes the quantification of 4 antioxidants extraction, at two different concentration, prepared according to an experimental procedure and measured by a Photodiode Array Detector. Experimental planning was made following a Central Composite Design, which is a type of DoE that allows to consider the quadratic component in Response Surfaces, a component that includes pure curvature studies on the model produced. This work was executed with the intention of analyzing responses, peak areas obtained from chromatograms plotted by the Detector’s system, and comprehending if the factors considered – acquired from an extensive literary review – produced the expected effect in response. Completion of this work will allow to take conclusions regarding what factors should be considered for the optimization studies of antioxidants extraction in a Oca (Oxalis tuberosa) matrix.

Development of process control strategies exploiting knowledge from systems biology: application to MDCK suspension cells

Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.

Assessing initial embodied energy in building structures using LCA methodology

The considerable amount of energy consumed on Earth is a major cause for not achieving sustainable development. Buildings are responsible for the highest worldwide energy consumption, nearly 40%. Strong efforts have been made in what concerns the reduction of buildings operational energy (heating, hot water, ventilation, electricity), since operational energy is so far the highest energy component in a building life cycle. However, as operational energy is being reduced the embodied energy increases. One of the building elements responsible for higher embodied energy consumption is the building structural system. Therefore, the present work is going to study part of embodied energy (initial embodied energy) in building structures using a life cycle assessment methodology, in order to contribute for a greater understanding of embodied energy in buildings structural systems. Initial embodied energy is estimated for a building structure by varying the span and the structural material type. The results are analysed and compared for different stages, and some conclusions are drawn. At the end of this work it was possible to conclude that the building span does not have considerable influence in embodied energy consumption of building structures. However, the structural material type has influence in the overall energetic performance. In fact, with this research it was possible that building structure that requires more initial embodied energy is the steel structure; then the glued laminated timber structure; and finally the concrete structure.

The emergence of product certification systems as trade barriers

This paper addresses the growing difficulties automobile manufacturers face within their after sales business: an increasing number of trade obstacles set up by import countries discriminates against the foreign suppliers and impedes the international sales of genuine parts. The purpose of the study is to explore the emergence of trade restrictive product certification systems, which affect spare parts exports of automobile manufacturers. The methodology used includes review of the literature and an empirical study based on qualitative interviews with representatives of major stakeholders of the automotive after sales business. Relevant key drivers, which initiate the introduction of technical regulations in importing countries, are identified and analysed to evaluate their effect on the emerging trade policy. The analysis of the key drivers outlines that several interacting components, such as the global competitiveness of the country, macroeconomic and microeconomic factors, and certain country-specific variables induce trade restrictive product certification systems. The findings allow for an early detection of the emergence of product certification systems and provide a means to early recognise the risks and opportunities for the sales of automotive spare parts in the automakers’ target markets. This allows the manufacturers to react immediately and adapt in time to the upcoming changes.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

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.