Approche basée sur des patrons pour concevoir des logiciels d’enseignement adaptés aux technologies du Web

Les applications Web en général ont connu d’importantes évolutions technologiques au cours des deux dernières décennies et avec elles les habitudes et les attentes de la génération de femmes et d’hommes dite numérique. Paradoxalement à ces bouleversements technologiques et comportementaux, les logiciels d’enseignement et d’apprentissage (LEA) n’ont pas tout à fait suivi la même courbe d’évolution technologique. En effet, leur modèle de conception est demeuré si statique que leur utilité pédagogique est remise en cause par les experts en pédagogie selon lesquels les LEA actuels ne tiennent pas suffisamment compte des aspects théoriques pédagogiques. Mais comment améliorer la prise en compte de ces aspects dans le processus de conception des LEA? Plusieurs approches permettent de concevoir des LEA robustes. Cependant, un intérêt particulier existe pour l’utilisation du concept patron dans ce processus de conception tant par les experts en pédagogie que par les experts en génie logiciel. En effet, ce concept permet de capitaliser l’expérience des experts et permet aussi de simplifier de belle manière le processus de conception et de ce fait son coût. Une comparaison des travaux utilisant des patrons pour concevoir des LEA a montré qu’il n’existe pas de cadre de synergie entre les différents acteurs de l’équipe de conception, les experts en pédagogie d’un côté et les experts en génie logiciel de l’autre. De plus, les cycles de vie proposés dans ces travaux ne sont pas complets, ni rigoureusement décrits afin de permettre de développer des LEA efficients. Enfin, les travaux comparés ne montrent pas comment faire coexister les exigences pédagogiques avec les exigences logicielles. Le concept patron peut-il aider à construire des LEA robustes satisfaisant aux exigences pédagogiques ? Comme solution, cette thèse propose une approche de conception basée sur des patrons pour concevoir des LEA adaptés aux technologies du Web. Plus spécifiquement, l’approche méthodique proposée montre quelles doivent être les étapes séquentielles à prévoir pour concevoir un LEA répondant aux exigences pédagogiques. De plus, un répertoire est présenté et contient 110 patrons recensés et organisés en paquetages. Ces patrons peuvent être facilement retrouvés à l’aide du guide de recherche décrit pour être utilisés dans le processus de conception. L’approche de conception a été validée avec deux exemples d’application, permettant de conclure d’une part que l’approche de conception des LEA est réaliste et d’autre part que les patrons sont bien valides et fonctionnels. L’approche de conception de LEA proposée est originale et se démarque de celles que l’on trouve dans la littérature car elle est entièrement basée sur le concept patron. L’approche permet également de prendre en compte les exigences pédagogiques. Elle est générique car indépendante de toute plateforme logicielle ou matérielle. Toutefois, le processus de traduction des exigences pédagogiques n’est pas encore très intuitif, ni très linéaire. D’autres travaux doivent être réalisés pour compléter les résultats obtenus afin de pouvoir traduire en artéfacts exploitables par les ingénieurs logiciels les exigences pédagogiques les plus complexes et les plus abstraites. Pour la suite de cette thèse, une instanciation des patrons proposés serait intéressante ainsi que la définition d’un métamodèle basé sur des patrons qui pourrait permettre la spécification d’un langage de modélisation typique des LEA. L’ajout de patrons permettant d’ajouter une couche sémantique au niveau des LEA pourrait être envisagée. Cette couche sémantique permettra non seulement d’adapter les scénarios pédagogiques, mais aussi d’automatiser le processus d’adaptation au besoin d’un apprenant en particulier. Il peut être aussi envisagé la transformation des patrons proposés en ontologies pouvant permettre de faciliter l’évaluation des connaissances de l’apprenant, de lui communiquer des informations structurées et utiles pour son apprentissage et correspondant à son besoin d’apprentissage.

Modelling of a Stirling engine with parabolic dish for thermal to electric conversion of solar energy

Stirling engines with parabolic dish for thermal to electric conversion of solar energy is one of the most promising solutions of renewable energy technologies in order to reduce the dependency from fossil fuels in electricity generation. This paper addresses the modelling and simulation of a solar powered Stirling engine system with parabolic dish and electric generator aiming to determine its energy production and efficiency. The model includes the solar radiation concentration system, the heat transfer in the ther- mal receiver, the thermal cycle and the mechanical and electric energy conversion. The thermodynamic and energy transfer processes in the engine are modelled in detail, including all the main processes occur- ring in the compression, expansion and regenerator spaces. Starting from a particular configuration, an optimization of the concentration factor is also carried out and the results for both the transient and steady state regimes are presented. It was found that using a directly illuminated thermal receiver with- out cavity the engine efficiency is close to 23.8% corresponding to a global efficiency of 10.4%. The com- ponents to be optimized are identified in order to increase the global efficiency of the system and the trade-off between system complexity and efficiency is discussed.

A non-ordinary state-based peridynamics formulation for thermoplastic fracture

In this study, a three-dimensional (3D) non-ordinary state-based peridynamics (NOSB-PD) formulation for thermomechanical brittle and ductile fracture is presented. The Johnson–Cook (JC) constitutive and damage model is used to taken into account plastic hardening, thermal softening and fracture. The for- mulation is validated by considering two benchmark examples: 1) The Taylor-bar impact and 2) the Kalthoff– Winkler tests. The results show good agreements between the numerical simulations and the experimental results.

Circadian Phase Control - Genetic Algorithm and Non-linear Control Approach

This paper deals with the phase control for Neurospora circadian rhythm. The nonlinear control, given by tuning the parameters (considered as controlled variables) in Neurospora dynamical model, allows the circadian rhythms tracking a reference one. When there are many parameters (e.g. 3 parameters in this paper) and their values are unknown, the adaptive control law reveals its weakness since the parameters converging and control objective must be guaranteed at the same time. We show that this problem can be solved using the genetic algorithm for parameters estimation. Once the unknown parameters are known, the phase control is performed by chaos synchronization technique.

Large scale underground energy storage for renewables integration: general criteria for reservoir identification and viable technologies.

The increasing integration of renewable energies in the electricity grid contributes considerably to achieve the European Union goals on energy and Greenhouse Gases (GHG) emissions reduction. However, it also brings problems to grid management. Large scale energy storage can provide the means for a better integration of the renewable energy sources, for balancing supply and demand, to increase energy security, to enhance a better management of the grid and also to converge towards a low carbon economy. Geological formations have the potential to store large volumes of fluids with minimal impact to environment and society. One of the ways to ensure a large scale energy storage is to use the storage capacity in geological reservoir. In fact, there are several viable technologies for underground energy storage, as well as several types of underground reservoirs that can be considered. The geological energy storage technologies considered in this research were: Underground Gas Storage (UGS), Hydrogen Storage (HS), Compressed Air Energy Storage (CAES), Underground Pumped Hydro Storage (UPHS) and Thermal Energy Storage (TES). For these different types of underground energy storage technologies there are several types of geological reservoirs that can be suitable, namely: depleted hydrocarbon reservoirs, aquifers, salt formations and caverns, engineered rock caverns and abandoned mines. Specific site screening criteria are applicable to each of these reservoir types and technologies, which determines the viability of the reservoir itself, and of the technology for any particular site. This paper presents a review of the criteria applied in the scope of the Portuguese contribution to the EU funded project ESTMAP – Energy Storage Mapping and Planning.

Linking thermal imaging to physiological indicators in Carica papaya L. under different watering regimes

Water deficit is the most limiting factor for yield and fruit-quality parameters in papaya crop (Carica papaya L.), deficit-irrigation (DI) strategies offering a feasible alternative to manage limiting water resources. When DI is applied, it is crucial to assess the physiological status of the crop in order to maintain the plant within a threshold value of water stress so as no to affect yield or fruit-quality parameters. The aim of this work was to evaluate the feasibility of thermal imaging in young papaya plants to assess the physiological status of this crop when it is subjected to different DI regimes, studying the relationships between the changes in leaf temperature (Tleaf) and in the major physiological parameters (i.e., stomatal conductance to water vapor, gs; transpiration, E; and net photosynthesis, An). The trial was conducted in a greenhouse from March to April of 2012. Plants were grown in pots and subjected to four irrigation treatments: (1) a full irrigation treatment (control), maintained at field capacity; (2) a partial root-zone drying treatment, irrigated with 50% of the total water applied to control to only one side of roots, alternating the sides every 7 days; (3) a regulated deficit irrigation (50% of the control, applied to both sides of plant); (4) and a non-irrigated treatment, in which irrigation was withheld from both sides of the split root for 14 days, followed by full irrigation until the end of the study. Significant relationships were found between Tleaf and major physiological variables such as gs, E and An. Additionally, significant relationships were found between the difference of leaf-to-air temperature (ΔTleaf–air) and gas-exchange measurements, which were used to establish the optimum range of ΔTleaf–air as a preliminary step to the crop-water monitoring and irrigation scheduling in papaya, using thermal imaging as the main source of information. According to the results, we conclude that thermal imaging is a promising technique to monitor the physiological status of papaya during drought conditions.

Linking thermal imaging to physiological indicators in Carica papaya L. under different watering regimes

Water deficit is the most limiting factor for yield and fruit-quality parameters in papaya crop (Carica papaya L.), deficit-irrigation (DI) strategies offering a feasible alternative to manage limiting water resources. When DI is applied, it is crucial to assess the physiological status of the crop in order to maintain the plant within a threshold value of water stress so as no to affect yield or fruit-quality parameters. The aim of this work was to evaluate the feasibility of thermal imaging in young papaya plants to assess the physiological status of this crop when it is subjected to different DI regimes, studying the relationships between the changes in leaf temperature (Tleaf) and in the major physiological parameters (i.e., stomatal conductance to water vapor, gs; transpiration, E; and net photosynthesis, An). The trial was conducted in a greenhouse from March to April of 2012. Plants were grown in pots and subjected to four irrigation treatments: (1) a full irrigation treatment (control), maintained at field capacity; (2) a partial root-zone drying treatment, irrigated with 50% of the total water applied to control to only one side of roots, alternating the sides every 7 days; (3) a regulated deficit irrigation (50% of the control, applied to both sides of plant); (4) and a non-irrigated treatment, in which irrigation was withheld from both sides of the split root for 14 days, followed by full irrigation until the end of the study. Significant relationships were found between Tleaf and major physiological variables such as gs, E and An. Additionally, significant relationships were found between the difference of leaf-to-air temperature (ΔTleaf–air) and gas-exchange measurements, which were used to establish the optimum range of ΔTleaf–air as a preliminary step to the crop-water monitoring and irrigation scheduling in papaya, using thermal imaging as the main source of information. According to the results, we conclude that thermal imaging is a promising technique to monitor the physiological status of papaya during drought conditions.

Real-Time Engine Diagnostic and Control Based on Acoustic Emissions Analysis

Engine developers are putting more and more emphasis on the research of maximum thermal and mechanical efficiency in the recent years. Research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting exhaust emissions limits. These new technologies require more complex engine control units. The sound emitted from a mechanical system encloses many information related to its operating condition and it can be used for control and diagnostic purposes. The thesis shows how the functions carried out from different and specific sensors usually present on-board, can be executed, at the same time, using only one multifunction sensor based on low-cost microphone technology. A theoretical background about sound and signal processing is provided in chapter 1. In modern turbocharged downsized GDI engines, the achievement of maximum thermal efficiency is precluded by the occurrence of knock. Knock emits an unmistakable sound perceived by the human ear like a clink. In chapter 2, the possibility of using this characteristic sound for knock control propose, starting from first experimental assessment tests, to the implementation in a real, production-type engine control unit will be shown. Chapter 3 focus is on misfire detection. Putting emphasis on the low frequency domain of the engine sound spectrum, features related to each combustion cycle of each cylinder can be identified and isolated. An innovative approach to misfire detection, which presents the advantage of not being affected by the road and driveline conditions is introduced. A preliminary study of air path leak detection techniques based on acoustic emissions analysis has been developed, and the first experimental results are shown in chapter 4. Finally, in chapter 5, an innovative detection methodology, based on engine vibration analysis, that can provide useful information about combustion phase is reported.

Non-Equilibrium Atmospheric Plasma As A Novel Route To Nanomaterial Synthesis And Processing For Biomedical Applications

Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

Evaluating non-price effects of regulatory and competition enforcement interventions

This thesis provides an ex-post evaluation of the effects of regulatory and competition policy enforcement interventions on non-price dimensions of competition. Chapter 1 examines the effects of a merger between two large Dutch supermarket chains on the variety and composition of product assortment. Chapter 2 and Chapter 3 investigate, both theoretically and empirically, the effects of access regulation in fixed telecoms markets on incentives to invest in superior infrastructure technologies. Non-price effects, together with price effects, are crucial to shed light on the extent of competition in a market and assess the effectiveness of regulatory and competition authorities' interventions. When evaluating non-price effects, however, it is harder to draw conclusions on the overall impact on consumers' welfare.

Synthesis of new non-fullerene acceptors based on indacenodithiophene core for organic solar cells

Due to the low cost, lightness and flexibility, Polymer Solar Cell (PSC) technology is considered one of the most promising energy technologies. In the past decades, PSCs using fullerenes or fullerene derivatives as the electron acceptors have made great progress with best power conversion efficiency (PCE) reaching 11%. However, fullerene type electron acceptors have several drawbacks such as complicated synthesis, a low light absorption coefficient and poor tuning in energy levels, which prevent the further development of fullerene-based PSCs. Hence the need to have a new class of electron acceptors as an alternative to conventional fullerene compounds. Non-fullerene acceptors (NFAs) have developed rapidly in the last years and the maximum PCEs have exceeded 14% for single-junction cells and 17% for double-junction tandem cells. By combining an electron-donating backbone, generally with several fused rings with electron-withdrawing units, we can simply construct NFA of the acceptor–donor–acceptor type (A–D–A). Versatile molecular structures have been developed using methods such as acceptor motif engineering and donor motif engineering. However, there are only a few electron-donating backbones that have been proved to be successful. Therefore, it is still necessary to develop promising building blocks to further enrich the structural diversity. An indacenodithiophene (IDT) unit with just five fused rings has a sufficiently rigid coplanar structure, which has been regarded as one of the promising electron-rich units to design high-performance A–D–A NFAs. In this work, performed at the King Abdullah University of Science and Technology in Saudi Arabia, a new nine-cyclic building block (TBIDT) with a two benzothiophene unit was synthesized and used for designing new non-fullerene electron acceptors.

Non-ambient solid-state characterization of crystalline molecular organic semiconductors

The research project is focused on the investigation of the polymorphism of crystalline molecular material for organic semiconductor applications under non-ambient conditions, and the solid-state characterization and crystal structure determination of the different polymorphic forms. In particular, this research project has tackled the investigation and characterization of the polymorphism of perylene diimides (PDIs) derivatives at high temperatures and pressures, in particular N,N’-dialkyl-3,4,9,10-perylendiimide (PDI-Cn, with n = 5, 6, 7, 8). These molecules are characterized by excellent chemical, thermal, and photostability, high electron affinity, strong absorption in the visible region, low LUMO energies, good air stability, and good charge transport properties, which can be tuned via functionalization; these features make them promising n-type organic semiconductor materials for several applications such as OFETs, OPV cells, laser dye, sensors, bioimaging, etc. The thermal characterization of PDI-Cn was carried out by a combination of differential scanning calorimetry, variable temperature X-ray diffraction, hot-stage microscopy, and in the case of PDI-C5 also variable temperature Raman spectroscopy. Whereas crystal structure determination was carried out by both Single Crystal and Powder X-ray diffraction. Moreover, high-pressure polymorphism via pressure-dependent UV-Vis absorption spectroscopy and high-pressure Single Crystal X-ray diffraction was carried out in this project. A data-driven approach based on a combination of self-organizing maps (SOM) and principal component analysis (PCA) is also reported was used to classify different π-stacking arrangements of PDI derivatives into families of similar crystal packing. Besides the main project, in the framework of structure-property analysis under non-ambient conditions, the structural investigation of the water loss in Pt- and Pd- based vapochromic potassium/lithium salts upon temperature, and the investigation of structure-mechanical property relationships in polymorphs of a thienopyrrolyldione endcapped oligothiophene (C4-NT3N) are reported.

Edge and Big Data technologies for Industry 4.0 to create an integrated pre-sale and after-sale environment

The fourth industrial revolution, also known as Industry 4.0, has rapidly gained traction in businesses across Europe and the world, becoming a central theme in small, medium, and large enterprises alike. This new paradigm shifts the focus from locally-based and barely automated firms to a globally interconnected industrial sector, stimulating economic growth and productivity, and supporting the upskilling and reskilling of employees. However, despite the maturity and scalability of information and cloud technologies, the support systems already present in the machine field are often outdated and lack the necessary security, access control, and advanced communication capabilities. This dissertation proposes architectures and technologies designed to bridge the gap between Operational and Information Technology, in a manner that is non-disruptive, efficient, and scalable. The proposal presents cloud-enabled data-gathering architectures that make use of the newest IT and networking technologies to achieve the desired quality of service and non-functional properties. By harnessing industrial and business data, processes can be optimized even before product sale, while the integrated environment enhances data exchange for post-sale support. The architectures have been tested and have shown encouraging performance results, providing a promising solution for companies looking to embrace Industry 4.0, enhance their operational capabilities, and prepare themselves for the upcoming fifth human-centric revolution.

Distributed ledger technologies between anonymity and transparency: AML/CFT regulation of cryptocurrency ecosystems in the EU

The advent of Bitcoin suggested a disintermediated economy in which Internet users can take part directly. The conceptual disruption brought about by this Internet of Money (IoM) mirrors the cross-industry impacts of blockchain and distributed ledger technologies (DLTs). While related instances of non-centralisation thwart regulatory efforts to establish accountability, in the financial domain further challenges arise from the presence in the IoM of two seemingly opposing traits: anonymity and transparency. Indeed, DLTs are often described as architecturally transparent, but the perceived level of anonymity of cryptocurrency transfers fuels fears of illicit exploitation. This is a primary concern for the framework to prevent money laundering and the financing of terrorism and proliferation (AML/CFT/CPF), and a top priority both globally and at the EU level. Nevertheless, the anonymous and transparent features of the IoM are far from clear-cut, and the same is true for its levels of disintermediation and non-centralisation. Almost fifteen years after the first Bitcoin transaction, the IoM today comprises a diverse set of socio-technical ecosystems. Building on an analysis of their phenomenology, this dissertation shows how there is more to their traits of anonymity and transparency than it may seem, and how these features range across a spectrum of combinations and degrees. In this context, trade-offs can be evaluated by referring to techno-legal benchmarks, established through socio-technical assessments grounded on teleological interpretation. Against this backdrop, this work provides framework-level recommendations for the EU to respond to the twofold nature of the IoM legitimately and effectively. The methodology cherishes the mutual interaction between regulation and technology when drafting regulation whose compliance can be eased by design. This approach mitigates the risk of overfitting in a fast-changing environment, while acknowledging specificities in compliance with the risk-based approach that sits at the core of the AML/CFT/CPF regime.

Data-driven and data-oriented methods for materials science and technologies

The discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials. However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process. This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results. Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques. This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns.