Prospective system analysis of stationary battery systems under the frame of Constructive Technology Assessment

Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.

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.

Barriers preventing the successful integration of mental health services into Primary Health Care in Nigeria : a mixed methods approach

RESUMO: A Nigéria tem uma população estimada em cerca de 170 milhões de pessoas. O número de profissionais de saúde mental é muito diminuto, contando apenas com 150 psiquiatras o que perfaz aproximadamente um rácio de psiquiatra: população de mais de 1:1 milhão de pessoas. O Plano Nacional de Saúde Mental de 1991 reconheceu esta insuficiência e recomendou a integração dos serviços de saúde mental nos cuidados de saúde primários (CSP). Depois de mais de duas décadas, essa política não foi ainda implementada. Este estudo teve como objetivos mapear a estrutura organizacional dos serviços de saúde mental da Nigéria, e explorar os desafios e barreiras que impedem a integração bem-sucedida dos serviços de saúde mental nos cuidados de saúde primários, isto segundo a perspectiva dos profissionais dos cuidados de saúde primários. Com este objetivo, desenvolveu-se um estudo exploratório sequencial e utilizou-se um modelo misto para a recolha de dados. A aplicação em simultâneo de abordagens qualitativas e quantitativas permitiram compreender os problemas relacionados com a integração dos serviços de saúde mental nos CSP na Nigéria. No estudo qualitativo inicial, foram realizadas entrevistas com listagens abertas a 30 profissionais dos CSP, seguidas de dois grupos focais com profissionais dos CSP de duas zonas governamentais do estado de Oyo de forma a obter uma visão global das perspectivas destes profissionais locais sobre os desafios e barreiras que impedem uma integração bem-sucedida dos serviços de saúde mental nos CSP. Subsequentemente, foram realizadas entrevistas com quatro pessoas-chave, especificamente coordenadores e especialistas em saúde mental. Os resultados do estudo qualitativo foram utilizados para desenvolver um questionário para análise quantitativa das opiniões de uma amostra maior e mais representativa dos profissionais dos CSP do Estado de Oyo, bem como de duas zonas governamentais locais do Estado de Osun. As barreiras mais comummente identificadas a partir deste estudo incluem o estigma e os preconceitos sobre a doença mental, a formação inadequada dos profissionais dos CPS sobre saúde mental, a perceção pela equipa dos CSP de baixa prioridade de ação do Governo, o medo da agressão e violência pela equipa dos CSP, bem como a falta de disponibilidade de fármacos. As recomendações para superar estes desafios incluem a melhoria sustentada dos esforços da advocacia à saúde mental que vise uma maior valorização e apoio governamental, a formação e treino organizados dos profissionais dos cuidados primários, a criação de redes de referência e de apoio com instituições terciárias adjacentes, e o engajamento da comunidade para melhorar o acesso aos serviços e à reabilitação, pelas pessoas com doença mental. Estes resultados fornecem indicações úteis sobre a perceção das barreiras para a integração bem sucedida dos serviços de saúde mental nos CSP, enquanto se recomenda uma abordagem holística e abrangente. Esta informação pode orientar as futuras tentativas de implementação da integração dos serviços de saúde mental nos cuidados primários na Nigéria.------------ABSTRACT: Nigeria has an estimated population of about 170 million people but the number of mental health professionals is very small, with about 150 psychiatrists. This roughly translates to a psychiatrist:population ratio of more than 1:1 million people. The National Mental Health Policy of 1991 recognized this deficiency and recommended the integration of mental health into primary health care (PHC) delivery system. After more than two decades, this policy has yet to be implemented. This study aimed to map out the organizational structure of the mental health systems in Nigeria, and to explore the challenges and barriers preventing the successful integration of mental health into primary health care, from the perspective of the primary health care workers. A mixed methods exploratory sequential study design was employed, which entails the use of sequential timing in the combined methods of data collection. A combination of qualitative and uantitative approaches in sequence, were utilized to understand the problems of mental health services integration into PHC in Nigeria. The initial qualitative phase utilized free listing interviews with 30 PHC workers, followed by two focus group discussions with primary care workers from two Local Government Areas (LGA) of Oyo State to gain useful insight into the local perspectives of PHC workers about the challenges and barriers preventing successful integration of mental health care services into PHC. Subsequently, 4 key informant interviews with PHC co-ordinators and mental health experts were carried out. The findings from the qualitative study were utilized to develop a quantitative study questionnaire to understand the opinions of a larger and more representative sample of PHC staff in two more LGAs of Oyo State, as well as 2 LGAs from Osun State. The common barriers identified from this study include stigma and misconceptions about mental illness, inadequate training of PHC staff about mental health, low government priority, fear of aggression and violence by the PHC staff, as well as non-availability of medications. Recommendations for overcoming these challenges include improved and sustained efforts at mental health advocacy to gain governmental attention and support, organized training and retraining for primary care staff, establishment of referral and supportive networks with neighbouring tertiary facilities and community engagement to improve service utilization and rehabilitation of mentally ill persons. These findings provide useful insight into the barriers to the successful integration of mental health into PHC, while recommending a holistic and comprehensive approach. This information can guide future attempts to implement the integration of mental health into primary care in Nigeria.

Overcoming the “European Paradox”: The role of Regional Innovation Systems (RIS) in translating R&D investments into economic and employment growth

The emergence of the so-called “European Paradox” shows that R&D investment is not maximally effective and that increasing the scale of public R&D expenditures is not sufficient to generate employment and sustained economic growth. Increasing Governmental R&D Investment is far from being a “panacea” for stagnant growth. It is worth noting that Government R&D Investment does not have a statistically significant impact on employment, indicating the need to assess the trade-offs of policies that could lead to significant increases in government expenditure. Surprisingly, Governmental R&D Employment does not contribute to “mass-market” employment, despite its quite important role in reducing Youth-Unemployment. Despite the negative side-effects of Governmental R&D Employment on both GVA and GDP, University R&D Employment appears to have a quite important role in reducing Unemployment, especially Youth-Unemployment, while it also does not have a downside in terms of economic growth. Technological Capacity enhancement is the most effective instrument for reducing Unemployment and is a policy without any downside regarding sustainable economical development. In terms of wider policy implications, the results reinforce the idea that European Commission Research and Innovation policies must be restructured, shifting from a transnational framework to a more localised, measurable and operational approach.

Optimization of export support systems: How to promote exports from Portugal to Germany in the area of information technology and electronics

This work project focuses on developing new approaches which enhance Portuguese exports towards a defined German industry sector within the information technology and electronics fields. Firstly and foremost, information was collected and a set of expert and top managers’ interviews were performed in order to acknowledge the demand of the German market while identifying compatible Portuguese supply capabilities. Among the main findings, Industry 4.0 presents itself as a valuable opportunity in the German market for Portuguese medium sized companies in the embedded systems area of expertise for machinery and equipment companies. In order to achieve the purpose of the work project, an embedded systems platform targeting machinery and equipment companies was suggested as well as it was developed several recommendations on how to implement it. An alternative approach for this platform was also considered within the German market namely the eHealth sector having the purpose of enhancing the current healthcare service provision.

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

The potential field method and the nonlinear attractor dynamics approach: what are the differences?

One of the most popular approaches to path planning and control is the potential field method. This method is particularly attractive because it is suitable for on-line feedback control. In this approach the gradient of a potential field is used to generate the robot's trajectory. Thus, the path is generated by the transient solutions of a dynamical system. On the other hand, in the nonlinear attractor dynamic approach the path is generated by a sequence of attractor solutions. This way the transient solutions of the potential field method are replaced by a sequence of attractor solutions (i.e., asymptotically stable states) of a dynamical system. We discuss at a theoretical level some of the main differences of these two approaches.

Integrated management systems as complex adaptive systems

It is a difficult task to avoid the “smart systems” topic when discussing smart prevention and, similarly, it is a difficult task to address smart systems without focusing their ability to learn. Following the same line of thought, in the current reality, it seems a Herculean task (or an irreparable omission) to approach the topic of certified occupational health and safety management systems (OHSMS) without discussing the integrated management systems (IMSs). The available data suggest that seldom are the OHSMS operating as the single management system (MS) in a company so, any statement concerning OHSMS should mainly be interpreted from an integrated perspective. A major distinction between generic systems can be drawn between those that learn, i.e., those systems that have “memory” and those that have not. These former systems are often depicted as adaptive since they take into account past events to deal with novel, similar and future events modifying their structure to enable success in its environment. Often, these systems, present a nonlinear behavior and a huge uncertainty related to the forecasting of some events. This paper seeks to portray, for the first time as we were able to find out, the IMSs as complex adaptive systems (CASs) by listing their properties and dissecting the features that enable them to evolve and self-organize in order to, holistically, fulfil the requirements from different stakeholders and thus thrive by assuring the successful sustainability of a company. Based on the revision of literature carried out, this is the first time that IMSs are pointed out as CASs which may develop fruitful synergies both for the MSs and for CASs communities. By performing a thorough revision of literature and based on some concepts embedded in the “DNA” of the subsystems implementation standards it is intended, specifically, to identify, determine and discuss the properties of a generic IMS that should be considered to classify it as a CAS.

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients’ route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Strategic planning of electricity systems: Integrating renewable energies

Tese de Doutoramento - Programa Doutoral em Engenharia Industrial e Sistemas (PDEIS)

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.