958 resultados para iaas, anonymous cloud, p2p, anonymizing network, gossip


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Aquest projecte consisteix en definir i desenvolupar un servei per JXTA que permeti l'anonimat en comunicacions P2P. Aquest servei s'ha desenvolupat fent servir els mecanismes que ofereix JXTA de forma que estigui el màxim d'integrat al sistema i disponible per qualsevol aplicació JXTA que requereix d'aquesta funcionalitat. Aquest servei està basat en un protocol existent d'anonimat descrit al paper Hordes: A Multicast Based Protocol for Anonymity (Brian Neil Levine & Clay Shields) triat després de fer-ne un estudi dels protocols existents actualment.

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In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

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Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

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Glial cells are active partners of neurons in processing information and synaptic integration. They receive coded signals from synapses and elaborate modulatory responses. The active properties of glia, including long-range signalling and regulated transmitter release, are beginning to be elucidated. Recent insights suggest that the active brain should no longer be regarded as a circuitry of neuronal contacts, but as an integrated network of interactive neurons and glia.

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HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

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BACKGROUND Combination antiretroviral therapy (cART) has produced significant changes in mortality of HIV-infected persons. Our objective was to estimate mortality rates, standardized mortality ratios and excess mortality rates of cohorts of the AIDS Research Network (RIS) (CoRIS-MD and CoRIS) compared to the general population. METHODS We analysed data of CoRIS-MD and CoRIS cohorts from 1997 to 2010. We calculated: (i) all-cause mortality rates, (ii) standardized mortality ratio (SMR) and (iii) excess mortality rates for both cohort for 100 person-years (py) of follow-up, comparing all-cause mortality with that of the general population of similar age and gender. RESULTS Between 1997 and 2010, 8,214 HIV positive subjects were included, 2,453 (29.9%) in CoRIS-MD and 5,761 (70.1%) in CoRIS and 294 deaths were registered. All-cause mortality rate was 1.02 (95% CI 0.91-1.15) per 100 py, SMR was 6.8 (95% CI 5.9-7.9) and excess mortality rate was 0.8 (95% CI 0.7-0.9) per 100 py. Mortality was higher in patients with AIDS, hepatitis C virus (HCV) co-infection, and those from CoRIS-MD cohort (1997-2003). CONCLUSION Mortality among HIV-positive persons remains higher than that of the general population of similar age and sex, with significant differences depending on the history of AIDS or HCV coinfection.