839 resultados para Class-based isolation vs. sharing


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This study helps develop an overall understanding as to why some students achieve where others don't. Debate on the effects of class on educational attainment is well documented and typically centres on the reproductive nature of class whilst studies of the effect of class on educational aspirations also predict outcomes that see education reinforcing and reproducing a student's class background.Despite a number of government initiatives to help raise higher education participation to 50 per cent by 2010, for the working class numbers have altered little. Using data from an ethnographic case study of a low-achieving girls school, the author explores aspirations and argues that whilst class is very powerful in explaining educational attainment, understanding educational aspirations is somewhat more complex. The purpose of this book, therefore, is to question and challenge popular assumptions surrounding class-based theory in making sense of girls' aspirations and to question the usefulness of the continued over reliance of such broad categorisations by both academics and policy makers

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An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.

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The popularity of wireless local area networks (WLANs) has resulted in their dense deployments around the world. While this increases capacity and coverage, the problem of increased interference can severely degrade the performance of WLANs. However, the impact of interference on throughput in dense WLANs with multiple access points (APs) has had very limited prior research. This is believed to be due to 1) the inaccurate assumption that throughput is always a monotonically decreasing function of interference and 2) the prohibitively high complexity of an accurate analytical model. In this work, firstly we provide a useful classification of commonly found interference scenarios. Secondly, we investigate the impact of interference on throughput for each class based on an approach that determines the possibility of parallel transmissions. Extensive packet-level simulations using OPNET have been performed to support the observations made. Interestingly, results have shown that in some topologies, increased interference can lead to higher throughput and vice versa.

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It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

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The use of economic incentives for biodiversity (mostly Compensation and Reward for Environmental Services including Payment for ES) has been widely supported in the past decades and became the main innovative policy tools for biodiversity conservation worldwide. These policy tools are often based on the insight that rational actors perfectly weigh the costs and benefits of adopting certain behaviors and well-crafted economic incentives and disincentives will lead to socially desirable development scenarios. This rationalist mode of thought has provided interesting insights and results, but it also misestimates the context by which ‘real individuals’ come to decisions, and the multitude of factors influencing development sequences. In this study, our goal is to examine how these policies can take advantage of some unintended behavioral reactions that might in return impact, either positively or negatively, general policy performances. We test the effect of income's origin (‘Low effort’ based money vs. ‘High effort’ based money) on spending decisions (Necessity vs. Superior goods) and subsequent pro social preferences (Future pro-environmental behavior) within Madagascar rural areas, using a natural field experiment. Our results show that money obtained under low effort leads to different consumption patterns than money obtained under high efforts: superior goods are more salient in the case of low effort money. In parallel, money obtained under low effort leads to subsequent higher pro social behavior. Compensation and rewards policies for ecosystem services may mobilize knowledge on behavioral biases to improve their design and foster positive spillovers on their development goals.

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IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.

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This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciência da Computação - IBILCE

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[ES] Los web frameworks son herramientas para mejorar el desarrollo y mantenimiento de sitios web. Aprender a utilizar un framework requiere varios meses y existen más de 100 web frameworks. Por ello es interesante que haya estudios que muestren sus diferencias. En este proyecto se realizó una comparativa de web frameworks para valorar sus diferencias, debilidades y fortalezas. Para seleccionar los web frameworks se utilizaron variables como las estadísticas de uso, popularidad y resultados en otras omparativas. Además, se decidió que los web frameworks seleccionados estuviesen basados en distintos lenguajes de programación. En base a esto se seleccionaron los web frameworks : Rails, Grails, Django y Codelgniter. Para compararlos se implementó una aplicación muy sencilla, MyBlog, con cada uno de ellos, un sistema de usuarios con blogs, posts y comentarios. La preparación para esta implementación consistió en : leer documentación sobre el lenguaje de programación, realizar un conjunto de ejercicios muy sencillos y leer la documentación del web framework. Todas estas tareas, incluida la implementación de MyBlog se tuvieron que realizar en un tiempo límite asignado. En base a este desarrollo se concluyó que Rails, Grails y Django son frameworks que requieren mucho tiempo en su aprendizaje, mientras que Codelgniter es mucho más sencillo de aprender. Sin embargo, los primeros producen un código más conciso y menos repetitivo, mientras que el último resulta en un código repetitivo y extenso. Por otro lado, la documentación de Grails era de baja calidad e incrementaba la dificultad en su aprendizaje. Rails y Django presentan una buena documentación. Rails es el único framework con un gran soporte para migraciones y Javascript. Django es el único que soporta las class-based views. Grails es el único que soporta internacionalización desde la generación de código.

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In computer systems, specifically in multithread, parallel and distributed systems, a deadlock is both a very subtle problem - because difficult to pre- vent during the system coding - and a very dangerous one: a deadlocked system is easily completely stuck, with consequences ranging from simple annoyances to life-threatening circumstances, being also in between the not negligible scenario of economical losses. Then, how to avoid this problem? A lot of possible solutions has been studied, proposed and implemented. In this thesis we focus on detection of deadlocks with a static program analysis technique, i.e. an analysis per- formed without actually executing the program. To begin, we briefly present the static Deadlock Analysis Model devel- oped for coreABS−− in chapter 1, then we proceed by detailing the Class- based coreABS−− language in chapter 2. Then, in Chapter 3 we lay the foundation for further discussions by ana- lyzing the differences between coreABS−− and ASP, an untyped Object-based calculi, so as to show how it can be possible to extend the Deadlock Analysis to Object-based languages in general. In this regard, we explicit some hypotheses in chapter 4 first by present- ing a possible, unproven type system for ASP, modeled after the Deadlock Analysis Model developed for coreABS−−. Then, we conclude our discussion by presenting a simpler hypothesis, which may allow to circumvent the difficulties that arises from the definition of the ”ad-hoc” type system discussed in the aforegoing chapter.

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The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only applications must evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time to changing contexts. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.