Video metadata extraction in a videoMail system

Currently the world swiftly adapts to visual communication. Online services like YouTube and Vine show that video is no longer the domain of broadcast television only. Video is used for different purposes like entertainment, information, education or communication. The rapid growth of today’s video archives with sparsely available editorial data creates a big problem of its retrieval. The humans see a video like a complex interplay of cognitive concepts. As a result there is a need to build a bridge between numeric values and semantic concepts. This establishes a connection that will facilitate videos’ retrieval by humans. The critical aspect of this bridge is video annotation. The process could be done manually or automatically. Manual annotation is very tedious, subjective and expensive. Therefore automatic annotation is being actively studied. In this thesis we focus on the multimedia content automatic annotation. Namely the use of analysis techniques for information retrieval allowing to automatically extract metadata from video in a videomail system. Furthermore the identification of text, people, actions, spaces, objects, including animals and plants. Hence it will be possible to align multimedia content with the text presented in the email message and the creation of applications for semantic video database indexing and retrieving.

Risk of employing an evolvable production system

Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

Should my company use Bitcoin?

This work project analyses the possibility for a company to trade their goods and services for bitcoins, by joining the Bitcoin network. It analyses the technological and business requirements to join the Bitcoin Network by looking at Bitcoin’s potential to act as a mean of exchange for trade, unit of account and store of value. The analysis points to the motives, benefits and risks for investors to use the Bitcoin as a traditional currency and recommends on strategies for addressing those risks and maximizing benefits. Other than companies this report, to a lesser extent, will also analyse the Bitcoin from an investor’s point of view, this is, should an investor buy bitcoins for trade and make savings on a regular and everyday basis? A major finding in this work project is that companies could start using the Bitcoin system as a legit form of payment since the benefits of using this technology outweigh the costs and risks, given the right approach. This form of payment will contribute for the upgrade of a company’s business’ image, attract a new pool of consumers and businesses that already trade in bitcoins and pressure existing financial institutions and electronic payment vendors to upgrade their service levels.

Assessment of overlay masonry strengthening system under in-plane monotonic and cyclic loading using the diagonal tensile test

The development of novel strengthening techniques to address the seismic vulnerability of masonry elements is gradually leading to simpler, faster and more effective strengthening strategies. In particular, the use of fabric reinforced cementitious matrix systems is considered of great potential, given the increase of ductility achieved with simple and economic strengthening procedures. To assess the effectiveness of these strengthening systems, and considering that the seismic action is involved, one important component of the structural behaviour is the in-plane cyclic response. In this work is discussed the applicability of the diagonal tensile test for the assessment of the cyclic response of strengthened masonry. The results obtained allowed to assess the contribution of the strengthening system to the increase of the load carrying capacity of masonry elements, as well as to evaluate the damage evolution and the stiffness degradation mechanisms developing under cyclic loading.

Exploring the use of HPFRC and GFRP grids for the production of manhole covers

Corrosion of the steel reinforced concrete elements is one of the common pathologies that limits the long-term performance of urban infrastructures. This problem causes the loss of structural serviceability by decreasing the concrete-steel bond strength and reducing the cross section of the reinforcements. The present study introduces a new system for developing free-corrosion resistance prefabricated manhole covers for applications in the aggressive environments, i.e. wastewater collector systems, sewer systems, stormwater systems, etc. Fibre reinforced cement composites were applied in this system in order to suppress the corrodible steel mesh and maintain the structural ductility as well. Application of fibre reinforced polymer (FRP) system is adopted as the additional solution for increasing the load carrying capacity of these elements without concerns about corrosion. The effectiveness of the applied strategy in developing the manhole covers in terms of load carrying capacity and failure mode is evaluated in this research. Furthermore, this paper discusses a FEM-based simulation, aiming to address the possibility of calibrating the constitutive model parameters related to fracture modes I and II.

Lightweight adjustable partition system: evaluation of resistance to horizontal loads and functional failure from impacts

This paper presents and discusses the results of the serviciability and use condition tests carried on an innovative solution for partitions, designated AdjustMembrane developed within a research project. The proposed system is a modular non-loadbearing wall, tensioned between the pavements and ceiling slabs, which are used as anchoring elements. It allows several advantages, related with the weight reduction to achieve a good sustainable performance, such as the reduction of construction costs, energy, and materials, and it is easy to recycle and to reuse, allowing self-construction. Apart from a general presentation of the partition technology, this paper presents and discusses the results of experimental tests carried out. From the results obtained, it is possible to conclude that the solution fulfils the requirements for this typology of wall in terms of resistance to horizontal loads induced by soft and hard body impacts.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Local seismic cultures: the use of timber frame structures in the south of Portugal

Given the fact that using timber frame structures has proven to improve the seismic behavior of vernacular architecture, as has been reported in past earthquakes in many countries, its preservation as a traditional earthquake resistant practice is important. This paper firstly intends to evaluate whether the use of timber frames as a traditional seismic resistant technique for vernacular architecture in the South of Portugal, traditionally a seismic region, is still active. Secondly, the city of Vila Real de Santo António was selected as a case study because it also followed a Pombaline development contemporary to the reconstruction of Lisbon. The plan included the provision of timber frame partition walls for some of the buildings and, thus, an overview of the type of constructions originally conceived is provided. Finally, the alterations done in the original constructions and the current state of the city center are described and the effect of these changes on the seismic vulnerability of the city is discussed.

Different module placements in a modular façade system for natural ventilation

Nowadays natural ventilation has gained prominence because its correct use can reduce energy consumption for cooling systems and improve thermal comfort among users. In this paper, we report on the modelling initiative, based on the wind tunnel tests that were carried out for the determination of the influence of natural ventilation in buildings. Indeed, the renewal of air in a closed environment without using an air conditioning system with mechanical elements can lead to energy savings and, in addition, provide air quality.The wind tunnel tests were carried out by varying the positioning of six ventilation modules in the façade system configuration. The modules were positioned below the window-sill (ventilated window-sill) as well as separately above and below the façade. The wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. The results supported the positioning of the six ventilation modules below the window-sill, forming a â ventilated window-sillâ as the most effective natural ventilation solution.

Study of natural ventilation for a modular façade system in wind tunnel tests

Wind tunnel tests are a reliable tool to determine the effect of natural ventilation on buildings. This paper presents results of wind tunnel tests conducted to evaluate the influence of ventilation modules positioning on a façade system. Modules positioning was modified, resulting in different façade configurations. The tests were carried out with the use of a model, varying the position of the ventilation modules in the façade configuration. The cases tested were six ventilation modules positioned below the window-sill (ventilated window-sill), and three ventilation modules positioned above and below the façade. The façade system proposed was movable and interchangeable so that the same basic model could be used to test the possibilities for ventilation. Wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. Singleâ sided and Cross ventilation were considered for wind speed measurements. Results show the use of six ventilation modules positioned below the window-sill, forming "a ventilated window-sill" is the best solution in terms of natural ventilation.

Grasses and legumes as cover crop in no-tillage system in northeastern Pará Brazil

Studies to select one or more species of coverage plants adapted to Amazonian soil and climate conditions of the Amazon are a promising strategy for the improvement of environmental quality, establishing no-till agricultural systems, and thereby reducing the impacts of monoculture farming. The aim of this study was to assess the persistence time, half-life time, macronutrient content and accumulation, and C:N ratio of straw coverage in a Ultisol in northeastern Pará. Experimental design was randomized blocks with five treatments and five replicates. Plants were harvested after 105 days, growth and biomass production was quantified. After 84 days, soil coverage was 97, 85, 52, 50, and 15% for signalgrass (Brachiaria brizantha) (syn. Urochloa), dense crowngrass (Panicum purpurascens), jack bean (Canavalia ensiformes), pearl millet (Pennisetum americanum) and sunn hemp (Crotalaria juncea,), respectively. Signalgrass yielded the greatest dry matter production (9,696 kg ha-1). It also had high C:N ratio (38.4), long half-life (86.5 days) and a high persistence in the field. Jack bean also showed high dry matter production (8,950 kg ha-1), but it had low C:N ratio (17.4) and lower half-life time (39 days) than the grasses. These attributes indicate that signalgrass and jack bean have a high potential for use as cover plants in no-till agricultural systems in the State of Pará.