993 resultados para Growing Pyramidal Networks
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Collaborative Work plays an important role in today’s organizations, especially in areas where decisions must be made. However, any decision that involves a collective or group of decision makers is, by itself complex, but is becoming recurrent in recent years. In this work we present the VirtualECare project, an intelligent multi-agent system able to monitor, interact and serve its customers, which are, normally, in need of care services. In last year’s there has been a substantially increase on the number of people needed of intensive care, especially among the elderly, a phenomenon that is related to population ageing. However, this is becoming not exclusive of the elderly, as diseases like obesity, diabetes and blood pressure have been increasing among young adults. This is a new reality that needs to be dealt by the health sector, particularly by the public one. Given this scenarios, the importance of finding new and cost effective ways for health care delivery are of particular importance, especially when we believe they should not to be removed from their natural “habitat”. Following this line of thinking, the VirtualECare project will be presented, like similar ones that preceded it. Recently we have also assisted to a growing interest in combining the advances in information society - computing, telecommunications and presentation – in order to create Group Decision Support Systems (GDSS). Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the above presented GDSS to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This achievement is vital, regarding the explosion of knowledge and skills, together with the need to use limited resources and get better results.
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Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
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The complexity associated with fast growing of B2B and the lack of a (complete) suite of open standards makes difficulty to maintain the underlying collaborative processes. Aligned to this challenge, this paper aims to be a contribution to an open architecture of logistics and transport processes management system. A model of an open integrated system is being defined as an open computational responsibility from the embedded systems (on-board) as well as a reference implementation (prototype) of a host system to validate the proposed open interfaces. Embedded subsystem can, natively, be prepared to cooperate with other on-board units and with IT-systems in an infrastructure commonly referred to as a center information system or back-office. In interaction with a central system the proposal is to adopt an open framework for cooperation where the embedded unit or the unit placed somewhere (land/sea) interacts in response to a set of implemented capabilities.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.
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It is now possible to perform resections of slow-growing tumors in awake patients. Using direct electrical stimulation, real-time functional mapping of the brain can be used to prevent the resection of essential areas near the tumor. Simple clinical observations of patients with a resection of slow-growing tumors have demonstrated substantial recovery within a few days of such 'awake surgery'. The aim of this study was to investigate the kinetics of recovery following the resection of slow-growing tumors invading the left parietal area and to focus mainly on its rapidity. Two patients were assessed by standard line bisection tests and compared with eight healthy individuals. Independently of the pure nature of the symptoms, we report that the patients rapidly and substantially recovered from pronounced right neglect. They were tested 48 hours after the surgery and the recovery was significant for both patients after less than 4 hours. Strikingly, for one patient, recovery was ultra fast and substantial in the first practice session within less than 7 minutes: it occurred without verbal feedback and was substantially retained during the following testing session. Its rapidity suggests a process of unmasking redundant networks. With the slow growth of the lesion, the contralesional hemisphere is probably progressively prepared for rapid unmasking of homologue networks. These results have major clinical implications. For patients with an invading left-side tumor, it is now clear that line bisections are required before, during, and after awake surgery to: plan the surgery, control the quality of the resection, and also optimize the rehabilitation of the patient
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This PhD thesis addresses the issue of scalable media streaming in large-scale networking environments. Multimedia streaming is one of the largest sink of network resources and this trend is still growing as testified by the success of services like Skype, Netflix, Spotify and Popcorn Time (BitTorrent-based). In traditional client-server solutions, when the number of consumers increases, the server becomes the bottleneck. To overcome this problem, the Content-Delivery Network (CDN) model was invented. In CDN model, the server copies the media content to some CDN servers, which are located in different strategic locations on the network. However, they require heavy infrastructure investment around the world, which is too expensive. Peer-to-peer (P2P) solutions are another way to achieve the same result. These solutions are naturally scalable, since each peer can act as both a receiver and a forwarder. Most of the proposed streaming solutions in P2P networks focus on routing scenarios to achieve scalability. However, these solutions cannot work properly in video-on-demand (VoD) streaming, when resources of the media server are not sufficient. Replication is a solution that can be used in these situations. This thesis specifically provides a family of replication-based media streaming protocols, which are scalable, efficient and reliable in P2P networks. First, it provides SCALESTREAM, a replication-based streaming protocol that adaptively replicates media content in different peers to increase the number of consumers that can be served in parallel. The adaptiveness aspect of this solution relies on the fact that it takes into account different constraints like bandwidth capacity of peers to decide when to add or remove replicas. SCALESTREAM routes media blocks to consumers over a tree topology, assuming a reliable network composed of homogenous peers in terms of bandwidth. Second, this thesis proposes RESTREAM, an extended version of SCALESTREAM that addresses the issues raised by unreliable networks composed of heterogeneous peers. Third, this thesis proposes EAGLEMACAW, a multiple-tree replication streaming protocol in which two distinct trees, named EAGLETREE and MACAWTREE, are built in a decentralized manner on top of an underlying mesh network. These two trees collaborate to serve consumers in an efficient and reliable manner. The EAGLETREE is in charge of improving efficiency, while the MACAWTREE guarantees reliability. Finally, this thesis provides TURBOSTREAM, a hybrid replication-based streaming protocol in which a tree overlay is built on top of a mesh overlay network. Both these overlays cover all peers of the system and collaborate to improve efficiency and low-latency in streaming media to consumers. This protocol is implemented and tested in a real networking environment using PlanetLab Europe testbed composed of peers distributed in different places in Europe.
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We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.
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Networks famously epitomize the shift from 'government' to 'governance' as governing structures for exercising control and coordination besides hierarchies and markets. Their distinctive features are their horizontality, the interdependence among member actors and an interactive decision-making style. Networks are expected to increase the problem-solving capacity of political systems in a context of growing social complexity, where political authority is increasingly fragmented across territorial and functional levels. However, very little attention has been given so far to another crucial implication of network governance - that is, the effects of networks on their members. To explore this important question, this article examines the effects of membership in European regulatory networks on two crucial attributes of member agencies, which are in charge of regulating finance, energy, telecommunications and competition: organisational growth and their regulatory powers. Panel analysis applied to data on 118 agencies during a ten-year period and semi-structured interviews provide mixed support regarding the expectation of organisational growth while strongly confirming the positive effect of networks on the increase of the regulatory powers attributed to member agencies.
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The α(1)-adrenergic receptor (AR) subtypes (α(1a), α(1b), and α(1d)) mediate several physiological effects of epinephrine and norepinephrine. Despite several studies in recombinant systems and insight from genetically modified mice, our understanding of the physiological relevance and specificity of the α(1)-AR subtypes is still limited. Constitutive activity and receptor oligomerization have emerged as potential features regulating receptor function. Another recent paradigm is that β arrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effects. The aim of this review is to summarize our current knowledge on some recently identified functional paradigms and signaling networks that might help to elucidate the functional diversity of the α(1)-AR subtypes in various organs.
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Autism is a neurodevelopmental disorder characterized by deficits in social interaction and social communication, as well as by the presence of repetitive and stereotyped behaviors and interests. Brodmann areas 44 and 45 in the inferior frontal cortex, which are involved in language processing, imitation function, and sociality processing networks, have been implicated in this complex disorder. Using a stereologic approach, this study aims to explore the presence of neuropathological differences in areas 44 and 45 in patients with autism compared to age- and hemisphere-matched controls. Based on previous evidence in the fusiform gyrus, we expected to find a decrease in the number and size of pyramidal neurons as well as an increase in volume of layers III, V, and VI in patients with autism. We observed significantly smaller pyramidal neurons in patients with autism compared to controls, although there was no difference in pyramidal neuron numbers or layer volumes. The reduced pyramidal neuron size suggests that a certain degree of dysfunction of areas 44 and 45 plays a role in the pathology of autism. Our results also support previous studies that have shown specific cellular neuropathology in autism with regionally specific reduction in neuron size, and provide further evidence for the possible involvement of the mirror neuron system, as well as impairment of neuronal networks relevant to communication and social behaviors, in this disorder.
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Erilaisten IP-pohjaisten palvelujen käyttö lisääntyy jatkuvasti samalla, kun käyttäjistä tulee yhä liikkuvaisempia. Tästä syystä IP- protokolla tulee väistämättä myös mobiiliverkkoihin. Tässä diplomityössä tutkitaan mobiliteetin IP multcastingiin tuomia ongelmia ja simuloidaan niitä Network Simulatoria käyttäen. Pääpaino on ongelmalla, joka aiheutuu multicast- ryhmänmuodostusviiveestä. Tätä ongelmaa simuloidaan, jotta viiveen, mobiilikäyttäjien palveluunsaapumistaajuuden ja Scalable Reliable Multicast (SRM) protokollan ajastinarvojen asetusten vaikutus repair request- pakettien määrään ja sitä kautta suoritettavien uudelleenlähetysten määrään selviäisi. Eri parametrien vaikutuksen tutkimiseksi esitetään simulaatiotuloksia varioiduilla parametreillä käyttäen CDF- käyriä. Tulosten perusteella merkittävin tekijä uudelleenlähetyspyyntöjen kannalta on protokollan ajastimien arvot ja haluttu palvelun taso, viiveen merkityksen jäädessä vähäiseksi. Työn lopuksi tutkitaan SRM- protokollan soveltuvuutta mobiiliverkkoihin ja pohditaan vaihtoehtoja toiminnan parantamiseksi.