958 resultados para iaas, anonymous cloud, p2p, anonymizing network, gossip
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This paper describes a Computer-Supported Collaborative Learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on Free- and Open-Source Software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. First, the Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates onhow Collage and Gridcole were employed, describes the applied evaluation methodology, anddiscusses the most significant findings derived from the case study.
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ADSL is becoming the standard form of residential and small-business broadband Internet access due to, primarily, its low deployment cost. These ADSL residential lines are often deployed with 802.11 Access Points (AP) that providewireless connectivity. Given the density of ADSL deployment, it is often possible for a residential wireless client to be in range of several other APs, belonging to neighbors, with ADSL connectivity. While the ADSL technology has showed evident limits in terms of capacity (with speeds ranging 1-10 Mbps), the short-range wireless communication can guarantee a muchhigher capacity (up to 20 Mbps). Furthermore, the ADSL links in the neighborhood are generally under-utilized, since ADSL subscribers do not connect 100% of the time. Therefore, it is possible for a wireless client to simultaneously connect to several APs in range and effectively aggregate their available ADSL bandwidth.In this paper, we introduce ClubADSL, a wireless client that can simultaneously connect to several APs in range on different frequencies and aggregate both their downlink and uplink capacity. ClubADSL is a software that runs locally on the client-side, and it requires neither modification to the existing Internet infrastructure, nor any hardware/protocol upgradesto the 802.11 local area network. We show the feasibility of ClubADSL in seamlessly transmitting TCP traffic, and validate its implementation both in controlled scenarios and with current applications over real ADSL lines. In particular we show that a ClubADSL client can greatly benefit from the aggregated download bandwidth in the case of server-client applications such as video streaming, but can also take advantage of the increased upload bandwidth greatly reducing download times with incentive-based P2P applications such as BitTorrent.
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This is the Annual Report for Fiscal Year 2005 (July 1, 2004-June 30, 2005) for the Iowa Communications Network.
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Agency Performance Report
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Agency Performance Report
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Iowa DOT savings through use of Iowa Communications Network (ICN) videoconferencing
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This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.
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Abstract Consideration of consumers’ demand for food quality entails several aspects. Quality itself is a complex and dynamic concept, and constantly evolving technical progress may cause changes in consumers’ judgment of quality. To improve our understanding of the factors influencing the demand for quality, food quality must be defined and measured from the consumer’s perspective (Cardello, 1995). The present analysis addresses the issue of food quality, focusing on pork—the food that respondents were concerned about. To gain insight into consumers’ demand, we analyzed their perception and evaluation and focused on their cognitive structures concerning pork quality. In order to more fully account for consumers’ concerns about the origin of pork, in 2004 we conducted a consumer survey of private households. The qualitative approach of concept mapping was used to uncover the cognitive structures. Network analysis was applied to interpret the results. In order to make recommendations to enterprises, we needed to know what kind of demand emerges from the given food quality schema. By establishing the importance and relative positions of the attributes, we find that the country of origin and butcher may be the two factors that have the biggest influence on consumers’ decisions about the purchase of pork.
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Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.
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[Acte. 1719-08-21. Paris]
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[Acte. 1726-08-27. aux Tuileries]
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The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.
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The goal of this paper is to study the e¤ects of globalization on the workings of financial markets. We adopt a "technological" view of globalization, which consists of an exogenous reduction in the cost of shipping goods across di¤erent regions of the world. We model financial markets where agents anonymously trade securities issued by every other agent in the world. In the absence of frictions, we show how globalization creates trade opportunities among residents of different regions of the world, thereby raising welfare. In the presence of sovereign risk, however, there emerge two crucial interactions between trade among residents within a region and trade among residents of di¤erent regions. First, the more residents within a region trade with each other, the more they can trade with residents of other regions. Second, the possibility of trade with residents of other regions sometimes leads a government to not enforce payments by its residents, destroying trade opportunities among residents within the region. The net effect on welfare of this process of creation and destruction of trade opportunities is ambiguous. We argue that there are no policies governments can take to avoid the negative effects of globalization on trade among domestic residents. In a dynamic extension, we analyze how our results are a¤ected by reputational considerations.