933 resultados para non-trivial data structures


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En esta tesis se aborda el problema de la externalización segura de servicios de datos y computación. El escenario de interés es aquel en el que el usuario posee datos y quiere subcontratar un servidor en la nube (“Cloud”). Además, el usuario puede querer también delegar el cálculo de un subconjunto de sus datos al servidor. Se presentan dos aspectos de seguridad relacionados con este escenario, en concreto, la integridad y la privacidad y se analizan las posibles soluciones a dichas cuestiones, aprovechando herramientas criptográficas avanzadas, como el Autentificador de Mensajes Homomórfico (“Homomorphic Message Authenticators”) y el Cifrado Totalmente Homomórfico (“Fully Homomorphic Encryption”). La contribución de este trabajo es tanto teórica como práctica. Desde el punto de vista de la contribución teórica, se define un nuevo esquema de externalización (en lo siguiente, denominado con su término inglés Outsourcing), usando como punto de partida los artículos de [3] y [12], con el objetivo de realizar un modelo muy genérico y flexible que podría emplearse para representar varios esquemas de ”outsourcing” seguro. Dicho modelo puede utilizarse para representar esquemas de “outsourcing” seguro proporcionando únicamente integridad, únicamente privacidad o, curiosamente, integridad con privacidad. Utilizando este nuevo modelo también se redefine un esquema altamente eficiente, construido en [12] y que se ha denominado Outsourcinglin. Este esquema permite calcular polinomios multivariados de grado 1 sobre el anillo Z2k . Desde el punto de vista de la contribución práctica, se ha construido una infraestructura marco (“Framework”) para aplicar el esquema de “outsourcing”. Seguidamente, se ha testado dicho “Framework” con varias implementaciones, en concreto la implementación del criptosistema Joye-Libert ([18]) y la implementación del esquema propio Outsourcinglin. En el contexto de este trabajo práctico, la tesis también ha dado lugar a algunas contribuciones innovadoras: el diseño y la implementación de un nuevo algoritmo de descifrado para el esquema de cifrado Joye-Libert, en colaboración con Darío Fiore. Presenta un mejor comportamiento frente a los algoritmos propuestos por los autores de [18];la implementación de la función eficiente pseudo-aleatoria de forma amortizada cerrada (“amortized-closed-form efficient pseudorandom function”) de [12]. Esta función no se había implementado con anterioridad y no supone un problema trivial, por lo que este trabajo puede llegar a ser útil en otros contextos. Finalmente se han usado las implementaciones durante varias pruebas para medir tiempos de ejecución de los principales algoritmos.---ABSTRACT---In this thesis we tackle the problem of secure outsourcing of data and computation. The scenario we are interested in is that in which a user owns some data and wants to “outsource” it to a Cloud server. Furthermore, the user may want also to delegate the computation over a subset of its data to the server. We present the security issues related to this scenario, namely integrity and privacy and we analyse some possible solutions to these two issues, exploiting advanced cryptographic tools, such as Homomorphic Message Authenticators and Fully Homomorphic Encryption. Our contribution is both theoretical and practical. Considering our theoretical contribution, using as starting points the articles of [3] and [12], we introduce a new cryptographic primitive, called Outsourcing with the aim of realizing a very generic and flexible model that might be employed to represent several secure outsourcing schemes. Such model can be used to represent secure outsourcing schemes that provide only integrity, only privacy or, interestingly, integrity with privacy. Using our new model we also re-define an highly efficient scheme constructed in [12], that we called Outsourcinglin and that is a scheme for computing multi-variate polynomials of degree 1 over the ring Z2k. Considering our practical contribution, we build a Framework to implement the Outsourcing scheme. Then, we test such Framework to realize several implementations, specifically the implementation of the Joye-Libert cryptosystem ([18]) and the implementation of our Outsourcinglin scheme. In the context of this practical work, the thesis also led to some novel contributions: the design and the implementation, in collaboration with Dario Fiore, of a new decryption algorithm for the Joye-Libert encryption scheme, that performs better than the algorithms proposed by the authors in [18]; the implementation of the amortized-closed-form efficient pseudorandom function of [12]. There was no prior implementation of this function and it represented a non trivial work, which can become useful in other contexts. Finally we test the implementations to execute several experiments for measuring the timing performances of the main algorithms.

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The design of a prestressed concrete roof is described. A special linear elastic analysis of non-prismatic folded structures has been applied. The obtained results have been compared to the results deducted from a small scale model test. Conclusions about the efficiency of these type of structures are shown.

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A necessidade de obter solução de grandes sistemas lineares resultantes de processos de discretização de equações diferenciais parciais provenientes da modelagem de diferentes fenômenos físicos conduz à busca de técnicas numéricas escaláveis. Métodos multigrid são classificados como algoritmos escaláveis.Um estimador de erros deve estar associado à solução numérica do problema discreto de modo a propiciar a adequada avaliação da solução obtida pelo processo de aproximação. Nesse contexto, a presente tese caracteriza-se pela proposta de reutilização das estruturas matriciais hierárquicas de operadores de transferência e restrição dos métodos multigrid algébricos para acelerar o tempo de solução dos sistemas lineares associados à equação do transporte de contaminantes em meio poroso saturado. Adicionalmente, caracteriza-se pela implementação das estimativas residuais para os problemas que envolvem dados constantes ou não constantes, os regimes de pequena ou grande advecção e pela proposta de utilização das estimativas residuais associadas ao termo de fonte e à condição inicial para construir procedimentos adaptativos para os dados do problema. O desenvolvimento dos códigos do método de elementos finitos, do estimador residual e dos procedimentos adaptativos foram baseados no projeto FEniCS, utilizando a linguagem de programação PYTHONR e desenvolvidos na plataforma Eclipse. A implementação dos métodos multigrid algébricos com reutilização considera a biblioteca PyAMG. Baseado na reutilização das estruturas hierárquicas, os métodos multigrid com reutilização com parâmetro fixo e automática são propostos, e esses conceitos são estendidos para os métodos iterativos não-estacionários tais como GMRES e BICGSTAB. Os resultados numéricos mostraram que o estimador residual captura o comportamento do erro real da solução numérica, e fornece algoritmos adaptativos para os dados cuja malha retornada produz uma solução numérica similar à uma malha uniforme com mais elementos. Adicionalmente, os métodos com reutilização são mais rápidos que os métodos que não empregam o processo de reutilização de estruturas. Além disso, a eficiência dos métodos com reutilização também pode ser observada na solução do problema auxiliar, o qual é necessário para obtenção das estimativas residuais para o regime de grande advecção. Esses resultados englobam tanto os métodos multigrid algébricos do tipo SA quanto os métodos pré-condicionados por métodos multigrid algébrico SA, e envolvem o transporte de contaminantes em regime de pequena e grande advecção, malhas estruturadas e não estruturadas, problemas bidimensionais, problemas tridimensionais e domínios com diferentes escalas.

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In this paper we describe Fénix, a data model for exchanging information between Natural Language Processing applications. The format proposed is intended to be flexible enough to cover both current and future data structures employed in the field of Computational Linguistics. The Fénix architecture is divided into four separate layers: conceptual, logical, persistence and physical. This division provides a simple interface to abstract the users from low-level implementation details, such as programming languages and data storage employed, allowing them to focus in the concepts and processes to be modelled. The Fénix architecture is accompanied by a set of programming libraries to facilitate the access and manipulation of the structures created in this framework. We will also show how this architecture has been already successfully applied in different research projects.

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In this paper a utilization of the high data-rates channels by threading of sending and receiving is studied. As a communication technology evolves the higher speeds are used more and more in various applications. But generating traffic with Gbps data-rates also brings some complications. Especially if UDP protocol is used and it is necessary to avoid packet fragmentation, for example for high-speed reliable transport protocols based on UDP. For such situation the Ethernet network packet size has to correspond to standard 1500 bytes MTU[1], which is widely used in the Internet. System may not has enough capacity to send messages with necessary rate in a single-threaded mode. A possible solution is to use more threads. It can be efficient on widespread multicore systems. Also the fact that in real network non-constant data flow can be expected brings another object of study –- an automatic adaptation to the traffic which is changing during runtime. Cases investigated in this paper include adjusting number of threads to a given speed and keeping speed on a given rate when CPU gets heavily loaded by other processes while sending data.

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Thesis--University of Illinois at Urbana-Champaign.

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"UIUCDCS-R-74-615"

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A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

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Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.

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In this paper, we present a formal hardware verification framework linking ASM with MDG. ASM (Abstract State Machine) is a state based language for describing transition systems. MDG (Multiway Decision Graphs) provides symbolic representation of transition systems with support of abstract sorts and functions. We implemented a transformation tool that automatically generates MDG models from ASM specifications, then formal verification techniques provided by the MDG tool, such as model checking or equivalence checking, can be applied on the generated models. We support this work with a case study of an Island Tunnel Controller, which behavior and structure were specified in ASM then using our ASM-MDG tool successfully verified within the MDG tool.

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Data refinements are refinement steps in which a program’s local data structures are changed. Data refinement proof obligations require the software designer to find an abstraction relation that relates the states of the original and new program. In this paper we describe an algorithm that helps a designer find an abstraction relation for a proposed refinement. Given sufficient time and space, the algorithm can find a minimal abstraction relation, and thus show that the refinement holds. As it executes, the algorithm displays mappings that cannot be in any abstraction relation. When the algorithm is not given sufficient resources to terminate, these mappings can help the designer find a suitable abstraction relation. The same algorithm can be used to test an abstraction relation supplied by the designer.

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In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

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This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

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Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.

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Recently, there has been a considerable research activity in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, the representational capabilities and internal representations of the models are not well understood. We rigorously analyze a generalization of the Self-Organizing Map (SOM) for processing sequential data, Recursive SOM (RecSOM [1]), as a non-autonomous dynamical system consisting off a set of fixed input maps. We show that contractive fixed input maps are likely to produce Markovian organizations of receptive fields o the RecSOM map. We derive bounds on parameter $\beta$ (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed input maps is guaranteed.