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.

Process simulation support in BPM tools: The case of BPMN

Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

Limitations and improvements to the risk assessment process in Olive Oil Mills: the views of OSH practitioners

Although most of the accidents occurred in Olive Oil Mill (OOM) resulted from “basic” risks, there is a need to apply adequate tools to support risk decisions that can meet the specificities of this sector. This study aims to analyse the views of Occupational, Safety & Health (OSH) practitioners about the risk assessment process in OOM, identifying the key difficulties inherent to the risk assessment process in these sector, as well as identifying some improvements to the current practice. This analysis was based on a questionnaire that was developed and applied to 13 OSH practitioners working at OOM. The results showed that the time available to perform the risk assessment is the more frequent limitation. They believe that the methodologies available are not an important limitation to this process. However, a specific risk assessment methodology, that includes acceptance criteria adjusted to the OOM reality, using risk metrics supported on the frequency of accidents and workdays lost, were indicated as being also an important contributions improve the process. A semi-quantitative approach, complemented with the use of the sector accident statistics, can be a good solution for this sector. However, further strategies should also be adopted, mainly those that can lead to an easy application of the risk assessment process.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

A demonstration case on the derivation of process-level logical architectures for ambient assisted living ecosystems

When representing the requirements for an intended software solution during the development process, a logical architecture is a model that provides an organized vision of how functionalities behave regardless of the technologies to be implemented. If the logical architecture represents an ambient assisted living (AAL) ecosystem, such representation is a complex task due to the existence of interrelated multidomains, which, most of the time, results in incomplete and incoherent user requirements. In this chap- ter, we present the results obtained when applying process-level modeling techniques to the derivation of the logical architecture for a real industrial AAL project. We adopt a V-Model–based approach that expresses the AAL requirements in a process-level perspec- tive, instead of the traditional product-level view. Additionally, we ensure compliance of the derived logical architecture with the National Institute of Standards and Technology (NIST) reference architecture as nonfunctional requirements to support the implementa- tion of the AAL architecture in cloud contexts.

A high order model for piezoelectric rods: an asymptotic approach

Preprint submitted to International Journal of Solids and Structures. ISSN 0020-7683

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

VET: a strategic approach for economic, organisational and personal development in EU countries

Vocational Education and Training (VET) is a continuous long-term process of economic, organisational and personal development. It envisions the construction of dynamic skills to improve performance, productivity and organisational, personal and social development. This article focuses on generating skills. It frames training as a process of work-linked training and as a primary source for generating skills whilst seeking to boost creativity. It sheds light upon the discussion pertaining to learning transfer as a necessary condition to structure performance and competitiveness. It highlights the Learning Transfer System Inventory (LTSI), because it allows to measure the effectiveness of training and it identifies the organisations' weaknesses. The data used were collected from the Eurostat Database.

A 3D computer assisted Orthopedic Surgery Planning approach based on planar radiography

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

Valorization of eucalyptus wood by glycerol-organosolv pretreatment within the biorefinery concept: an integrated and intensified approach

The efficient utilization of lignocellulosic biomass and the reduction of production cost are mandatory to attain a cost-effective lignocellulose-to-ethanol process. The selection of suitable pretreatment that allows an effective fractionation of biomass and the use of pretreated material at high-solid loadings on saccharification and fermentation (SSF) processes are considered promising strategies for that purpose. Eucalyptus globulus wood was fractionated by organosolv process at 200 C for 69 min using 56% of glycerol-water. A 99% of cellulose remained in pretreated biomass and 65% of lignin was solubilized. Precipitated lignin was characterized for chemical composition and thermal behavior, showing similar features to commercial lignin. In order to produce lignocellulosic ethanol at high-gravity, a full factory design was carried to assess the liquid to solid ratio (3e9 g/g) and enzyme to solid ratio (8e16 FPU/g) on SSF of delignified Eucalyptus. High ethanol concentration (94 g/L) corresponding to 77% of conversion at 16FPU/g and LSR ¼ 3 g/g using an industrial and thermotolerant Saccharomyces cerevisiae strain was successfully produced from pretreated biomass. Process integration of a suitable pretreatment, which allows for whole biomass valorization, with intensified saccharification-fermentation stages was shown to be feasible strategy for the co-production of high ethanol titers, oligosaccharides and lignin paving the way for cost-effective Eucalyptus biorefinery.

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.

Organization of construction activity in medieval Portugal: a comparative approach

This paper aims to identify and characterize the organizational models of construction site and building activity in late fifteenth and early sixteenth centuries, through the analysis of specific Portuguese case studies, related with important buildings financed by the royal power. This paper also intends to develop a comparative analysis between those different organizational models, identifying the main features of each one, as well as their similarities and differences. In this sense, we intend to present a comparative analysis between the two main models of organization of the construction site, through a methodology of crossing different types of sources, including written ones, such as books of accounts, but also iconographic and material sources, as well as the buildings and monuments still preserved today. In terms of written sources, the construction site accounting books allow us to study several specific aspects of the construction process, but also allow us to infer the organizational models of the construction activity.

Antibacterial properties of multifunctional coatings Ag-ZrCN for biomedical devices: a novel approach

PhD in Sciences Specialty in Physics