900 resultados para Multi-modal information processing


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All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. Under this context distributed generators, owned by different decentralized players can provide a significant amount of the electricity generation. To get negotiation power and advantages of scale economy, these players can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multi-technology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the integration of Virtual Power Producers into an electricity market simulator –MASCEM – as a coalition of distributed producers.

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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Doutor em Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of such datasets. However, for change detection existing methods are often unable to deal with heterogeneous image sources and very few consider possible nonlinearities in the data. Additionally, the availability of labeled information is very limited in change detection applications. For these reasons, we present the use of a semi-supervised kernel-based feature extraction technique. It incorporates a manifold regularization accounting for the geometric distribution and jointly addressing the small sample problem. An exhaustive example using Landsat 5 data illustrates the potential of the method for multi-sensor change detection.

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Traditionally, the ventral occipito-temporal (vOT) area, but not the superior parietal lobules (SPLs), is thought as belonging to the neural system of visual word recognition. However, some dyslexic children who exhibit a visual attention span disorder - i.e. poor multi-element parallel processing - further show reduced SPLs activation when engaged in visual multi-element categorization tasks. We investigated whether these parietal regions further contribute to letter-identity processing within strings. Adult skilled readers and dyslexic participants with a visual attention span disorder were administered a letter-string comparison task under fMRI. Dyslexic adults were less accurate than skilled readers to detect letter identity substitutions within strings. In skilled readers, letter identity differs related to enhanced activation of the left vOT. However, specific neural responses were further found in the superior and inferior parietal regions, including the SPLs bilaterally. Two brain regions that are specifically related to substituted letter detection, the left SPL and the left vOT, were less activated in dyslexic participants. These findings suggest that the left SPL, like the left vOT, may contribute to letter string processing.

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Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.

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Forensic science is generally defined as the application of science to address questions related to the law. Too often, this view restricts the contribution of science to one single process which eventually aims at bringing individuals to court while minimising risk of miscarriage of justice. In order to go beyond this paradigm, we propose to refocus the attention towards traces themselves, as remnants of a criminal activity, and their information content. We postulate that traces contribute effectively to a wide variety of other informational processes that support decision making inmany situations. In particular, they inform actors of new policing strategies who place the treatment of information and intelligence at the centre of their systems. This contribution of forensic science to these security oriented models is still not well identified and captured. In order to create the best condition for the development of forensic intelligence, we suggest a framework that connects forensic science to intelligence-led policing (part I). Crime scene attendance and processing can be envisaged within this view. This approach gives indications abouthowto structure knowledge used by crime scene examiners in their effective practice (part II).

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Recent multisensory research has emphasized the occurrence of early, low-level interactions in humans. As such, it is proving increasingly necessary to also consider the kinds of information likely extracted from the unisensory signals that are available at the time and location of these interaction effects. This review addresses current evidence regarding how the spatio-temporal brain dynamics of auditory information processing likely curtails the information content of multisensory interactions observable in humans at a given latency and within a given brain region. First, we consider the time course of signal propagation as a limitation on when auditory information (of any kind) can impact the responsiveness of a given brain region. Next, we overview the dual pathway model for the treatment of auditory spatial and object information ranging from rudimentary to complex environmental stimuli. These dual pathways are considered an intrinsic feature of auditory information processing, which are not only partially distinct in their associated brain networks, but also (and perhaps more importantly) manifest only after several tens of milliseconds of cortical signal processing. This architecture of auditory functioning would thus pose a constraint on when and in which brain regions specific spatial and object information are available for multisensory interactions. We then separately consider evidence regarding mechanisms and dynamics of spatial and object processing with a particular emphasis on when discriminations along either dimension are likely performed by specific brain regions. We conclude by discussing open issues and directions for future research.

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We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

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Thisthesis supplements the systematic approach to competitive intelligence and competitor analysis by introducing an information-processing perspective on management of the competitive environment and competitors therein. The cognitive questions connected to the intelligence process and also the means that organizational actors use in sharing information are discussed. The ultimate aim has been to deepen knowledge of the different intraorganizational processes that are used in acorporate organization to manage and exploit the vast amount of competitor information that is received from the environment. Competitor information and competitive knowledge management is examined as a process, where organizational actorsidentify and perceive the competitive environment by using cognitive simplification, make interpretations resulting in learning and finally utilize competitor information and competitive knowledge in their work processes. The sharing of competitive information and competitive knowledge is facilitated by intraorganizational networks that evolve as a means of developing a shared, organizational level knowledge structure and ensuring that the right information is in the right place at the right time. This thesis approaches competitor information and competitive knowledge management both theoretically and empirically. Based on the conceptual framework developed by theoretical elaboration, further understanding of the studied phenomena is sought by an empirical study. The empirical research was carried out in a multinationally operating forest industry company. This thesis makes some preliminary suggestions of improving the competitive intelligence process. It is concluded that managing competitor information and competitive knowledge is not simply a question of managing information flow or improving sophistication of competitor analysis, but the crucial question to be solved is rather, how to improve the cognitive capabilities connected to identifying and making interpretations of the competitive environment and how to increase learning. It is claimed that competitive intelligence can not be treated like an organizational function or assigned solely to a specialized intelligence unit.

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Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

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Tavoitteena diplomityössä oli kuvata projektiliiketoimintaa harjoittavan yrityksen informaatio- ja materiaalivirrat toimitusprojekteissa. Selvitys haluttiin tehdä tulevia kehitysprojekteja varten. Diplomityö toteutettiin kahessa osassa: laatimalla aiheeseen liittyvä teoriakatsaus ja kartoittamalla todellinen tilanne yrityksen sisällä.Teoriaosassa kuvattiin tarkastelualue ja projektiliiketoiminnan erityispiirteitä sekä käsiteltiin tietojärjestelmiä ja materiaalivirran hallintaan liittyviä asioita. Yrityksen informaatio- ja materiaalivirtojen nykytila kartoitettiin laatimalla vuokaaviot kolmen esimerkkituotteen toimitusprojekteista. Kaaviot laadittiin yrityksen sisäisten dokumenttien ja kvalitatiivisten haastattelujen pohjalta. Kaavioiden sisältöä täydennettiin taulukoimalla kaavioissa esiintyvien dokumettien sisältöä. Työn tuloksena muodostui kuva tiedonkäsittelyn nykytilasta myynti- ja toimitusprojekteissa, pelkistetty visio tulevaisuuden tietojärjestelmien rooleista sekä ehdotuksia tulevia kehitysprojekteja varten.

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The key information processing units within gene regulatory networks are enhancers. Enhancer activity is associated with the production of tissue-specific noncoding RNAs, yet the existence of such transcripts during cardiac development has not been established. Using an integrated genomic approach, we demonstrate that fetal cardiac enhancers generate long noncoding RNAs (lncRNAs) during cardiac differentiation and morphogenesis. Enhancer expression correlates with the emergence of active enhancer chromatin states, the initiation of RNA polymerase II at enhancer loci and expression of target genes. Orthologous human sequences are also transcribed in fetal human hearts and cardiac progenitor cells. Through a systematic bioinformatic analysis, we identified and characterized, for the first time, a catalog of lncRNAs that are expressed during embryonic stem cell differentiation into cardiomyocytes and associated with active cardiac enhancer sequences. RNA-sequencing demonstrates that many of these transcripts are polyadenylated, multi-exonic long noncoding RNAs. Moreover, knockdown of two enhancer-associated lncRNAs resulted in the specific downregulation of their predicted target genes. Interestingly, the reactivation of the fetal gene program, a hallmark of the stress response in the adult heart, is accompanied by increased expression of fetal cardiac enhancer transcripts. Altogether, these findings demonstrate that the activity of cardiac enhancers and expression of their target genes are associated with the production of enhancer-derived lncRNAs.

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Information processing in groups has long been seen as a cooperative process. In contrast with this assumption, group members were rarely found to behave cooperatively: They withhold unshared information and stick to initial incorrect decisions. In the present article, we examined how group members' cooperative and competitivemotives impact on group information processing and propose that information sharing and use in groups could be seen as strategic behavior. We reviewed the latest developments in the literature investigating different forms of strategic information processing and their underlying mechanisms. This review suggests that explicit cooperative goals are needed for effective group decision-making.

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We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.