Implementação do algoritmo (RTM) para processamento sísmico em arquiteturas não convencionais

With the growth of energy consumption worldwide, conventional reservoirs, the reservoirs called "easy exploration and production" are not meeting the global energy demand. This has led many researchers to develop projects that will address these needs, companies in the oil sector has invested in techniques that helping in locating and drilling wells. One of the techniques employed in oil exploration process is the reverse time migration (RTM), in English, Reverse Time Migration, which is a method of seismic imaging that produces excellent image of the subsurface. It is algorithm based in calculation on the wave equation. RTM is considered one of the most advanced seismic imaging techniques. The economic value of the oil reserves that require RTM to be localized is very high, this means that the development of these algorithms becomes a competitive differentiator for companies seismic processing. But, it requires great computational power, that it still somehow harms its practical success. The objective of this work is to explore the implementation of this algorithm in unconventional architectures, specifically GPUs using the CUDA by making an analysis of the difficulties in developing the same, as well as the performance of the algorithm in the sequential and parallel version

Creative Practices Around the Production of Cork

Cork, as a natural product provided by the bark of the cork oak tree, is an important staple of the Portuguese economy and important to Portuguese culture. It is a sustainable product with a positive ecological footprint, from harvesting to industrial production, with the advantage of creating a local economic model through regional labour activity and distribution. Within the balance between nature-human-economy to create a sustainable system, cork production in Portugal represents a human and social dimension. By focusing on that dimension and by creating an awareness of the cultural and social impact of the activity and by re-appraising the meaning of the material within the culture, the study reframes a consideration of the actual place of labour and production. The human, geophysical, historical, social, economic, ecological and cultural aspects of the place are observed as regards their relation to work or labour in that physical space. A pilot study is being developed in the village of Azaruja in the district of Évora, Portugal. In this small locality, cork is very important in terms of the relationships between the physical subsistence of their residents and the local natural resources, because it structures the place in its cultural, social and economical dimensions. This paper outlines the theoretical foundations, the process and the outcomes of the participatory ecodesign project titled Creative Practices Around the Production of Cork which was initiated by a Portuguese artist/design researcher and developed further through the collaboration with the other two authors, one a Portuguese visual artist/researcher and the other a Turkish fashion designer/theorist. The investigation focuses on questions that expand the notion of place for artists and designers, filtered through the lenses of manual labourers in order to understand their physical, social, cultural and economic relationship with the environment. To create the process of interaction with the place and the people, a creative collaborative dynamic is developed between the authors with their range of artistic sensibilities and the local population. To adopt a holistic notion of sustainability and cultural identity a process of investigation is designated to: (1) analyse, test and interpret - through the dissemination of life stories, visual representation of the place and the creation of cork objects - the importance of culture related to the labour activity of a local natural resource that determines and structures the region; (2) to give public recognition to those involved, taking into account their sense of belonging to the place and in order to show the value of their sustainable labour activities related to local natural resources; (3) to contribute to the knowledge of the place and to its dynamism through an aesthetic approach to labour activities. With reference to fields of knowledge such as anthropology, the social arts and sustainable design, a practice-based research is conducted with collaborative and participatory design methods to create an open model of interaction which involves local people in the realization of the project. Outcomes of this research will be presented in the paper as a survey analysis with theoretical conclusions.

Matlab simulink modeling of photovoltaic cells for understanding shadow effect

Irradiation is the main component for producing the electricity from solar energy. When obstacles come in between the sun and the PV cell then it doesn’t get sufficient irradiance to produce enough electricity. Shadowing has a great impact on photovoltaic cell. The main fuel of PV cell is solar radiation. Using solar radiation, a photovoltaic cell produces electricity. The shadow on a PV cell decreases the output of the photovoltaic cell. It has been already shown in different papers that shadow effect decreases the output of the PV cell. There are different kinds of shadow effects which are observed, some minimize the PV cell output and some reduce the output to zero. There are different types of shadow based on their effects on the photovoltaic cell. The shadow has also effects depending on whether the PV cells are connected in series connection or in parallel connection. In series when one cell is out of order then the whole series of the PV cells will not work but in parallel connection if one cell is damaged, the others will work because they work independently. According to the output requirement the arrangement of the PV cells are made in series or parallel. Simulink modeling is made for series and parallel connection between two PV cells and the shadow effect is analyzed on one of the PV cells. Using SIMULINK, the shadowing is simulated on the two PV cells, where in one system they are in series and in another system they are in parallel. Slowly the irradiance is decreased to simulate the shadow effect. Simulation of the shadow effect gives an idea about the output of the PV cell system when system has shadow on the PV cells. Here the shadow effect on the two PV cells using series and parallel combinations are simulated and analyzed for understanding the effects on output.

A URBANIZAÇÃO NA AMÉRICA LATINA E CARIBE: UM INDICADOR DE ÂMBITO REGIONAL

Na modernidade histórica, o fenômeno da urbanização nas regiões periféricas mundiais – América Latina, Ásia e África, constitui um fenômeno à parte daquele ocorrido nas regiões mais centrais e em época anterior. A urbanização latino-americana apresenta traços bastante particulares de uma modernidade que não são encontrados em nenhuma outra região, fato que acaba se refletindo nas próprias diferenças de urbanização apresentadas pelo conjunto de países que a formam. Considerando, portanto, tal configuração é que se objetiva, nesse estudo, elaborar uma classificação dos países latino-americanos e do Caribe em relação ao seu grau de modernização – variáveis e dimensões relacionadas -, e sua associação com as taxas de crescimento populacional regionais em período recente (2000 - 2004), com base nos dados do Banco Mundial; adicionalmente, objetiva-se, tendo em vista os aportes relacionados, operacionalizar, num sentido lato sensu, uma medida da urbanização regional.

Design of an innovative electric vehicle simulator for Charging Systems' End-of-Line Testing

The trend related to the turnover of internal combustion engine vehicles with EVs goes by the name of electrification. The push electrification experienced in the last decade is linked to the still ongoing evolution in power electronics technology for charging systems. This is the reason why an evolution in testing strategies and testing equipment is crucial too. The project this dissertation is based on concerns the investigation of a new EV simulator design. that optimizes the structure of the testing equipment used by the company who commissioned this work. Project requirements can be summarized in the following two points: space occupation reduction and parallel charging implementation. Some components were completely redesigned, and others were substituted with equivalent ones that could perform the same tasks. In this way it was possible to reduce the space occupation of the simulator, as well as to increase the efficiency of the testing device. Moreover, the possibility of conjugating different charging simulations could be investigated by parallelly launching two testing procedures on a unique machine, properly predisposed for supporting the two charging protocols used. On the back of the results achieved in the body of this dissertation, a new design for the EV simulator was proposed. In this way, space reduction was obtained, and space occupation efficiency was improved with the proposed new design. The testing device thus resulted to be way more compact, enabling to gain in safety and productivity, along with a 25% cost reduction. Furthermore, parallel charging was implemented in the proposed new design since the conducted tests clearly showed the feasibility of parallel charging sessions. The results presented in this work can thus be implemented to build the first prototype of the new EV simulator.

Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

Processi e pratiche di Innovazione Responsabile: il ruolo dell' Advanced Design nella trasformazione collaborativa dei territori

La ricerca indaga il rapporto tra Design e Innovazione Responsabile calandolo all’interno della relazione tra territorio e pratiche collaborative guidate dal design, ma anche legate al patrimonio culturale immateriale e a un sistema di conoscenza a quintupla elica. La necessità emergente di cura del futuro porta a rivedere il contesto del territorio come campo strumentale per la trasformazione degli individui e della comunità e a domandarsi in che modo il design possa supportare questo cambiamento, abilitando la produzione di conoscenza collaborativa. La ricerca parte dal dimostrare come il modello di innovazione recentemente proposto dalla Comunità Europea attraverso il concetto di Responsible Research Innovation (RRI), poi ripreso nella nozione di Responsible Innovation (RI), sia un campo aperto e responsivo: se integrato con altre discipline, in particolare con il design, può supportare lo sviluppo di processi, politiche, prodotti, servizi e comportamenti che rispettino la relazione tra società, ambiente, identità individuale e collettiva e i ritmi ad essi connessi. Partendo dal contesto sopra descritto, ci si chiede come il design e il designer possano integrare le dimensioni RI nei processi di progettazione, per innovare in modo collaborativo i territori. Si individua quindi nell’Advanced Design la metodologia che, grazie alla sua natura anticipatrice, collaborativa, trasformativa, riesce a coniugarsi virtuosamente con l’approccio RI e supportare il cambiamento in atto. L’intersezione di questi elementi porta alla creazione del Modello Advanced Design per/con l’Innovazione Responsabile (ADIR): un sistema multidimensionale per gruppi di innovazione (quintupla elica) che hanno l’obiettivo di rigenerare in modo collaborativo e inclusivo i territori. L’esperienza sul campo ha confermato come la struttura del modello, formata da un corpus di semi-lavorati, permetta di creare un proprio ritmo, una compenetrazione tra azioni e forme progettuali volti a mantenere il senso di comunità e il coinvolgimento degli attori, a creare relazioni, a sviluppare una trasformazione continua.

A machine learning based method to detect genomic imbalances exploiting X chromosome exome reads

Whole Exome Sequencing (WES) is rapidly becoming the first-tier test in clinics, both thanks to its declining costs and the development of new platforms that help clinicians in the analysis and interpretation of SNV and InDels. However, we still know very little on how CNV detection could increase WES diagnostic yield. A plethora of exome CNV callers have been published over the years, all showing good performances towards specific CNV classes and sizes, suggesting that the combination of multiple tools is needed to obtain an overall good detection performance. Here we present TrainX, a ML-based method for calling heterozygous CNVs in WES data using EXCAVATOR2 Normalized Read Counts. We select males and females’ non pseudo-autosomal chromosome X alignments to construct our dataset and train our model, make predictions on autosomes target regions and use HMM to call CNVs. We compared TrainX against a set of CNV tools differing for the detection method (GATK4 gCNV, ExomeDepth, DECoN, CNVkit and EXCAVATOR2) and found that our algorithm outperformed them in terms of stability, as we identified both deletions and duplications with good scores (0.87 and 0.82 F1-scores respectively) and for sizes reaching the minimum resolution of 2 target regions. We also evaluated the method robustness using a set of WES and SNP array data (n=251), part of the Italian cohort of Epi25 collaborative, and were able to retrieve all clinical CNVs previously identified by the SNP array. TrainX showed good accuracy in detecting heterozygous CNVs of different sizes, making it a promising tool to use in a diagnostic setting.

Developing a methodology for co-creation using extended reality technologies.

Amid the remarkable growth of innovative technologies, particularly immersive technologies like Extended Reality (XR) (comprising of Virtual Reality (VR), Augmented Reality (AR) & Mixed Reality (MR)), a transformation is unfolding in the way we collaborate and interact. The current research takes the initiative to explore XR’s potential for co-creation activities and proposes XR as a future co-creation platform. It strives to develop a XR-based co-creation system, actively engage stakeholders in the co-creation process, with the goal of enhancing their creative businesses. The research leverages XR tools to investigate how they can enhance digital co-creation methods and determine if the system facilitates efficient and effective value creation during XR-based co-creation sessions. In specific terms, the research probes into whether the XR-based co-creation method and environment enhances the quality and novelty of ideas, reduce communication challenges by providing better understanding of the product, problem or process and optimize the process in terms of reduction in time and costs. The research introduces a multi-user, multi-sensory collaborative and interactive XR platform that adapts to various use-case scenarios. This thesis also presents the user testing performed to collect both qualitative and quantitative data, which serves to substantiate the hypothesis. What sets this XR system apart is its incorporation of fully functional prototypes into a mixed reality environment, providing users with a unique dimension within an immersive digital landscape. The outcomes derived from the experimental studies demonstrate that XR-based co-creation surpasses conventional desktop co-creation methods and remarkably, the results are even comparable to a full mock-up test. In conclusion, the research underscores that the utilization of XR as a tool for co-creation generates substantial value. It serves as a method that enhances the process, an environment that fosters interaction and collaboration, and a platform that equips stakeholders with the means to engage effectively.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Fuzzy tolerance/equivalence relations from intersection, union and complement operators and their application to a clustering method

This master thesis work introduces the fuzzy tolerance/equivalence relation and its application in cluster analysis. The work presents about the construction of fuzzy equivalence relations using increasing generators. Here, we investigate and research on the role of increasing generators for the creation of intersection, union and complement operators. The objective is to develop different varieties of fuzzy tolerance/equivalence relations using different varieties of increasing generators. At last, we perform a comparative study with these developed varieties of fuzzy tolerance/equivalence relations in their application to a clustering method.

Clustering algorithms and shape factor methods to discriminate among small GTPase phenotypes using DIC image analysis.

Naïvement perçu, le processus d’évolution est une succession d’événements de duplication et de mutations graduelles dans le génome qui mènent à des changements dans les fonctions et les interactions du protéome. La famille des hydrolases de guanosine triphosphate (GTPases) similaire à Ras constitue un bon modèle de travail afin de comprendre ce phénomène fondamental, car cette famille de protéines contient un nombre limité d’éléments qui diffèrent en fonctionnalité et en interactions. Globalement, nous désirons comprendre comment les mutations singulières au niveau des GTPases affectent la morphologie des cellules ainsi que leur degré d’impact sur les populations asynchrones. Mon travail de maîtrise vise à classifier de manière significative différents phénotypes de la levure Saccaromyces cerevisiae via l’analyse de plusieurs critères morphologiques de souches exprimant des GTPases mutées et natives. Notre approche à base de microscopie et d’analyses bioinformatique des images DIC (microscopie d’interférence différentielle de contraste) permet de distinguer les phénotypes propres aux cellules natives et aux mutants. L’emploi de cette méthode a permis une détection automatisée et une caractérisation des phénotypes mutants associés à la sur-expression de GTPases constitutivement actives. Les mutants de GTPases constitutivement actifs Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V ont été analysés avec succès. En effet, l’implémentation de différents algorithmes de partitionnement, permet d’analyser des données qui combinent les mesures morphologiques de population native et mutantes. Nos résultats démontrent que l’algorithme Fuzzy C-Means performe un partitionnement efficace des cellules natives ou mutantes, où les différents types de cellules sont classifiés en fonction de plusieurs facteurs de formes cellulaires obtenus à partir des images DIC. Cette analyse démontre que les mutations Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V induisent respectivement des phénotypes amorphe, allongé, rond et large qui sont représentés par des vecteurs de facteurs de forme distincts. Ces distinctions sont observées avec différentes proportions (morphologie mutante / morphologie native) dans les populations de mutants. Le développement de nouvelles méthodes automatisées d’analyse morphologique des cellules natives et mutantes s’avère extrêmement utile pour l’étude de la famille des GTPases ainsi que des résidus spécifiques qui dictent leurs fonctions et réseau d’interaction. Nous pouvons maintenant envisager de produire des mutants de GTPases qui inversent leur fonction en ciblant des résidus divergents. La substitution fonctionnelle est ensuite détectée au niveau morphologique grâce à notre nouvelle stratégie quantitative. Ce type d’analyse peut également être transposé à d’autres familles de protéines et contribuer de manière significative au domaine de la biologie évolutive.

Two extensions for the ALWABP: Parallel stations and collaborative approach

In this article, we introduce two new variants of the Assembly Line Worker Assignment and Balancing Problem (ALWABP) that allow parallelization of and collaboration between heterogeneous workers. These new approaches suppose an additional level of complexity in the Line Design and Assignment process, but also higher flexibility; which may be particularly useful in practical situations where the aim is to progressively integrate slow or limited workers in conventional assembly lines. We present linear models and heuristic procedures for these two new problems. Computational results show the efficiency of the proposed approaches and the efficacy of the studied layouts in different situations. (C) 2012 Elsevier B.V. All rights reserved.

Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.