Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.

Novel affinity pairs "tag-receptor" for the purification of fusion proteins

Fundação para a Ciência e Tecnologia - SFRH/BD/48804/2008 and the project PTDC/BI/65383/2006 assigned to Prof. Cecíla Roque and also to Associate Laboratory REQUIMTE (Pest-C/EQB/LA0006/2011)

A domain specific language for domotic systems

To cope with modernity, the interesting of having a fully automated house has been increasing over the years, as technology evolves and as our lives become more stressful and overloaded. An automation system provides a way to simplify some daily tasks, allowing us to have more spare time to perform activities where we are really needed. There are some systems in this domain that try to implement these characteristics, but this kind of technology is at its early stages of evolution being that it is still far away of empowering the user with the desired control over a habitation. The reason is that the mentioned systems miss some important features such as adaptability, extension and evolution. These systems, developed from a bottom-up approach, are often tailored for programmers and domain experts, discarding most of the times the end users that remain with unfinished interfaces or products that they have difficulty to control. Moreover, complex behaviors are avoided, since they are extremely difficult to implement mostly due to the necessity of handling priorities, conflicts and device calibration. Besides, these solutions are only reachable at very high costs, yet they still have the limitation of being difficult to configure by non-technical people once in runtime operation. As a result, it is necessary to create a tool that allows the execution of several automated actions, with an interface that is easy to use but at the same time supports all the main features of this domain. It is also desirable that this tool is independent of the hardware so it can be reused, thus a Model Driven Development approach (MDD) is the ideal option, as it is a method that follows those principles. Since the automation domain has some very specific concepts, the use of models should be combined with a Domain Specific Language (DSL). With these two methods, it is possible to create a solution that is adapted to the end users, but also to domain experts and programmers due to the several levels of abstraction that can be added to diminish the complexity of use. The aim of this thesis is to design a Domain Specific Language (DSL) that uses the Model Driven Development approach (MDD), with the purpose of supporting Home Automation (HA) concepts. In this implementation, the development of simple and complex scenarios should be supported and will be one of the most important concerns. This DSL should also support other significant features in this domain, such as the ability to schedule tasks, which is something that is limited in the current existing solutions.

Enhancing and implementing a pairs trading strategy

This paper designs a pairs trading model with the intent to identify existing profitable market opportunities to invest, i.e. traditionally strong correlated stocks that have diverged from its historical norm. It comprises a broad literature review on this strategy whose relevant findings (strategy improvements) are contemplated in the model. The authors combine the statistical results of the model with a backtesting analysis in order to provide guidance on the best investment opportunities.

Framework for the semantic alignment of enterprise’s domain knowledge

Nowadays, the consumption of goods and services on the Internet are increasing in a constant motion. Small and Medium Enterprises (SMEs) mostly from the traditional industry sectors are usually make business in weak and fragile market sectors, where customized products and services prevail. To survive and compete in the actual markets they have to readjust their business strategies by creating new manufacturing processes and establishing new business networks through new technological approaches. In order to compete with big enterprises, these partnerships aim the sharing of resources, knowledge and strategies to boost the sector’s business consolidation through the creation of dynamic manufacturing networks. To facilitate such demand, it is proposed the development of a centralized information system, which allows enterprises to select and create dynamic manufacturing networks that would have the capability to monitor all the manufacturing process, including the assembly, packaging and distribution phases. Even the networking partners that come from the same area have multi and heterogeneous representations of the same knowledge, denoting their own view of the domain. Thus, different conceptual, semantic, and consequently, diverse lexically knowledge representations may occur in the network, causing non-transparent sharing of information and interoperability inconsistencies. The creation of a framework supported by a tool that in a flexible way would enable the identification, classification and resolution of such semantic heterogeneities is required. This tool will support the network in the semantic mapping establishments, to facilitate the various enterprises information systems integration.

Production and diagnostic application of recombinant domain III of West Nile envelope protein in Brazil

INTRODUCTION: West Nile virus (WNV) is a flavivirus with a natural cycle involving mosquitoes and birds. Over the last 11 years, WNV has spread throughout the Americas with the imminent risk of its introduction in Brazil. METHODS: Envelope protein domain III of WNV (rDIII) was bacterially expressed and purified. An enzyme-linked immunosorbent assay with WNV rDIII antigen was standardized against mouse immune fluids (MIAFs) of different flavivirus. RESULTS: WNV rDIII reacted strongly with St. Louis encephalitis virus (SLEV) MIAF but not with other flaviviruses. CONCLUSIONS: This antigen may be a potentially useful tool for serologic diagnosis and may contribute in future epidemiological surveillance of WNV infections in Brazil.

8-Phase Ring oscillator for modern receivers

The evolution of receiver architectures, built in modern CMOS technologies, allows the design of high efficient receivers. A key block in modern receivers is the oscillator. The main objective of this thesis is to design a very low power and low area 8-Phase Ring Oscillator for biomedical applications (ISM and WMTS bands). Oscillators with multiphase outputs and variable duty cycles are required. In this thesis we are focused in 12.5% and 50% duty-cycles approaches. The proposed circuit uses eight inverters in a ring structure, in order to generate the output duty cycle of 50%. The duty cycle of 1/8 is achieved through the combination of the longer duty cycle signals in pairs, using, for this purpose, NAND gates. Since the general application are not only the wireless communications context, as well as industrial, scientific and medical plans, the 8-Phase Oscillator is simulated to be wideband between 100 MHz and 1 GHz, and be able to operate in the ISM bands (447 MHz-930 MHz) and WMTS (600 MHz). The circuit prototype is designed in UMC 130 nm CMOS technology. The maximum value of current drawn from a DC power source of 1.2 V, at a maximum frequency of 930 MHz achieved, is 17.54 mA. After completion of the oscillator layout studied (occupied area is 165 μm x 83 μm). Measurement results confirm the expected operating range from the simulations, and therefore, that the oscillator fulfil effectively the goals initially proposed in order to be used as Local Oscillator in RF Modern Receivers.

Multipacket reception in the presence of in-band full-duplex communication

In-Band Full-DupleX (IB-FDX) is defined as the ability for nodes to transmit and receive signals simultaneously on the same channel. Conventional digital wireless networks do not implement it, since a node’s own transmission signal causes interference to the signal it is trying to receive. However, recent studies attempt to overcome this obstacle, since it can potentially double the spectral efficiency of current wireless networks. Different mechanisms exist today that are able to reduce a significant part of the Self- Interference (SI), although specially tuned Medium Access Control (MAC) protocols are required to optimize its use. One of IB-FDX’s biggest problems is that the nodes’ interference range is extended, meaning the unusable space for other transmissions and receptions is broader. This dissertation proposes using MultiPacket Reception (MPR) to address this issue and adapts an already existing Single-Carrier with Frequency-Domain Equalization (SC-FDE) receiver to IB-FDX. The performance analysis suggests that MPR and IB-FDX have a strong synergy and are able to achieve higher data rates, when used together. Using analytical models, the optimal transmission patterns and transmission power were identified, which maximize the channel capacity with the minimal energy consumption. This was used to define a new MAC protocol, named Full-duplex Multipacket reception Medium Access Control (FM-MAC). FM-MAC was designed for a single-hop cellular infrastructure, where the Access Point (AP) and the terminals implement both IB-FDX and MPR. It divides the coverage range of the AP into a closer Full-DupleX (FDX) zone and a farther Half-DupleX (HDX) zone and adds a tunable fairness mechanism to avoid terminal starvation. Simulation results show that this protocol provides efficient support for both HDX and FDX terminals, maximizing its capacity when more FDX terminals are used.

A Saint Louis encephalitis and Rocio virus serosurvey in Brazilian horses

Introduction Arboviruses are an important public health problem in Brazil, in especially flaviviruses, including the Saint Louis encephalitis virus (SLEV) and the Rocio virus (ROCV), are especially problematic. These viruses are transmitted to humans or other vertebrates through arthropod bites and may cause diseases with clinical manifestations that range from asymptomatic infection, viral hemorrhagic fever to encephalitis. Methods A serological survey of horses from various regions of Brazil using an enzyme-linked immunosorbent assay (ELISA) with recombinant SLEV domain III peptides and ROCV E protein as antigens. Results Overall, 415 (55.1%) of the 753 horses that were screened were seropositive for flavivirus and, among them, monotypic reactions were observed to SLEV in 93 (12.3%) and to ROCV in 46 (6.1%). These results suggested that these viruses, or other closely related viruses, are infecting horses in Brazil. However, none of the studied horses presented central nervous system infection symptoms. Conclusions Our results suggest that SLEV and ROCV previously circulated among horses in northeast, west-central and southeast Brazil.

Leptospirosis in animals and human contacts in Egypt: broad range surveillance

INTRODUCTION: Leptospirosis is a re-emerging zoonotic disease of humans and animals worldwide. The disease is caused by pathogenic species of the genus Leptospira. These organisms are maintained in nature via chronic renal infection of carrier animals, which excrete the organisms in their urine. Humans become infected through direct or indirect exposure to infected animals and their urine or through contact with contaminated water and soil. This study was conducted to investigate Leptospira infections as a re-emerging zoonosis that has been neglected in Egypt. METHODS: Samples from 1,250 animals (270 rats, 168 dogs, 625 cows, 26 buffaloes, 99 sheep, 14 horses, 26 donkeys and 22 camels), 175 human contacts and 45 water sources were collected from different governorates in Egypt. The samples were collected from different body sites and prepared for culture, PCR and the microscopic agglutination test (MAT). RESULTS: The isolation rates of Leptospira serovars were 6.9%, 11.3% and 1.1% for rats, dogs and cows, respectively, whereas the PCR results revealed respective detection rates of 24%, 11.3% and 1.1% for rats, dogs and cows. Neither the other examined animal species nor humans yielded positive results via these two techniques. Only six Leptospira serovars (Icterohaemorrhagiae, Pomona, Canicola, Grippotyphosa, Celledoni and Pyrogenes) could be isolated from rats, dogs and cows. Moreover, the seroprevalence of leptospiral antibodies among the examined humans determined using MAT was 49.7%. CONCLUSIONS: The obtained results revealed that rats, dogs and cows were the most important animal reservoirs for leptospirosis in Egypt, and the high seroprevalence among human contacts highlights the public health implications of this neglected zoonosis.

Semantic relations extraction from unstructured information for domain ontologies enrichment

Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

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.

Frequency-domain receiver design for doubly-selective channels

This work is devoted to the broadband wireless transmission techniques, which are serious candidates to be implemented in future broadband wireless and cellular systems, aiming at providing high and reliable data transmission and concomitantly high mobility. In order to cope with doubly-selective channels, receiver structures based on OFDM and SC-FDE block transmission techniques, are proposed, which allow cost-effective implementations, using FFT-based signal processing. The first subject to be addressed is the impact of the number of multipath components, and the diversity order, on the asymptotic performance of OFDM and SC-FDE, in uncoded and for different channel coding schemes. The obtained results show that the number of relevant separable multipath components is a key element that influences the performance of OFDM and SC-FDE schemes. Then, the improved estimation and detection performance of OFDM-based broadcasting systems, is introduced employing SFN (Single Frequency Network) operation. An initial coarse channel is obtained with resort to low-power training sequences estimation, and an iterative receiver with joint detection and channel estimation is presented. The achieved results have shown very good performance, close to that with perfect channel estimation. The next topic is related to SFN systems, devoting special attention to time-distortion effects inherent to these networks. Typically, the SFN broadcast wireless systems employ OFDM schemes to cope with severely time-dispersive channels. However, frequency errors, due to CFO, compromises the orthogonality between subcarriers. As an alternative approach, the possibility of using SC-FDE schemes (characterized by reduced envelope fluctuations and higher robustness to carrier frequency errors) is evaluated, and a technique, employing joint CFO estimation and compensation over the severe time-distortion effects, is proposed. Finally, broadband mobile wireless systems, in which the relative motion between the transmitter and receiver induces Doppler shift which is different or each propagation path, is considered, depending on the angle of incidence of that path in relation to the direction of travel. This represents a severe impairment in wireless digital communications systems, since that multipath propagation combined with the Doppler effects, lead to drastic and unpredictable fluctuations of the envelope of the received signal, severely affecting the detection performance. The channel variations due this effect are very difficult to estimate and compensate. In this work we propose a set of SC-FDE iterative receivers implementing efficient estimation and tracking techniques. The performance results show that the proposed receivers have very good performance, even in the presence of significant Doppler spread between the different groups of multipath components.

Modern piracy

A definição de pirataria ou a desmistificação da sua origem, no tempo e espaço, revela maiores dificuldades do que atualmente. Com este trabalho propusemo-nos a estudar como é que a pirataria era perpetrada e entendida no passado, bem como no presente. Também nos propomos a identificar limitações legais e as medidas operativas no combate à pirataria, como por exemplo: limites conceptuais, lacunas, estratégias, entre outros. Por outro lado, atendemos as soluções encontradas no combate à pirataria sem deixar de observar fraqueza da lei e conflitos entre jurisdições. Por fim, o curso da história dá-nos a seguinte percepção: a pirataria era tida como crime se fosse contra os interesses das nações. O desinteresse dos Estados para reprimir a pirataria possibilitou o seu aumento, proliferação, domínio e sofisticação em certas regiões do Mundo. O presente trabalho tem como objetivo trazer para o centro da discussão os direitos humanos numa perspetiva tripla: proibição da pirataria, supressão e raízes, aliando o estudo de possíveis respostas a dar a esta epidemia.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.