1000 resultados para Vector computers


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Modelling the level of demand for construction is vital in policy formulation and implementation as the construction industry plays an important role in a country’s economic development process. In construction economics, research efforts on construction demand modelling and forecasting are various, but few researchers have considered the impact of global economy events in construction demand modelling. An advanced multivariate modelling technique, namely the vector error correction (VEC) model with dummy variables, was adopted to predict demand in the Australian construction market. The results of prediction accuracy tests suggest that the general VEC model and the VEC model with dummy variables are both acceptable for forecasting construction economic indicators. However, the VEC model that considers external impacts achieves higher prediction accuracy than the general VEC model. The model estimates indicate that the growth in population, changes in national income, fluctuations in interest rates and changes in householder expenditure all play significant roles when explaining variations in construction demand. The VEC model with disturbances developed can serve as an experimentation using an advanced econometrical method which can be used to analyse the effect of specific events or factors on the construction market growth.

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This paper addresses the problem of privacy-preserving data publishing for social network. Research on protecting the privacy of individuals and the confidentiality of data in social network has recently been receiving increasing attention. Privacy is an important issue when one wants to make use of data that involves individuals' sensitive information, especially in a time when data collection is becoming easier and sophisticated data mining techniques are becoming more efficient. In this paper, we discuss various privacy attack vectors on social networks. We present algorithms that sanitize data to make it safe for release while preserving useful information, and discuss ways of analyzing the sanitized data. This study provides a summary of the current state-of-the-art, based on which we expect to see advances in social networks data publishing for years to come.

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A key traditional question the client learns in the conventional psychotherapies is ‘Am I getting what I want?’. But can this question incite a mindset that does not align with the ‘give and take’ essence of sustainable everyday relations? Is it possible that the psychotherapies—if these practices can be bundled together—might teach clients to become more self-centred and relationally illiterate? MARK FURLONG suggests that well-intentioned practitioners can inadvertently de-empathise, ignore or even disrupt their clients’ intimate networks. Findings from his research support the proposition that the action of the mainstream therapies tends to undermine the service users’ prospects for sustainable personal relationships. Exceptions were found in the specialist settings of paediatric and aged care, and in narrative and family therapy practice.

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Least square problem with l1 regularization has been proposed as a promising method for sparse signal reconstruction (e.g., basis pursuit de-noising and compressed sensing) and feature selection (e.g., the Lasso algorithm) in signal processing, statistics, and related fields. These problems can be cast as l1-regularized least-square program (LSP). In this paper, we propose a novel monotonic fixed point method to solve large-scale l1-regularized LSP. And we also prove the stability and convergence of the proposed method. Furthermore we generalize this method to least square matrix problem and apply it in nonnegative matrix factorization (NMF). The method is illustrated on sparse signal reconstruction, partner recognition and blind source separation problems, and the method tends to convergent faster and sparser than other l1-regularized algorithms.

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This paper presents some of the findings of a pilot study concerning gender differences in behaviour in a Year 10 co- educational secondary mathematics classroom that used computers. Analysis of interactions between students and the teacher and engagement with the task, the computer and the mathematics suggest some evidence of gender difference. A number of factors were hypothesised as relating to behaviour and this paper discusses the preliminary findings in relation to students' experience with computers and their style of interaction with computers.

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Secondary students who participated in a computer enhanced mathematics program expressed positive attitudes about the use of computers. They viewed computers as a source of pleasure, success, relevance and/or power in mathematics. Girls were more likely than boys to qualify their support for the use of computers and more likely to view computers as a source of success in mathematics. Boys were more likely to claim that computers brought pleasure or relevance to mathematics learning.

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In this paper, we discuss the design aspects of a dynamic distributed directory scheme (DDS) to facilitate efficient and transparent access to information files in mobile environments. The proposed directory interface enables users of mobile computers to view a distributed file system on a network of computers as a globally shared file system. In order to counter some of the limitations of wireless communications, we propose improvised invalidation schemes that avoid false sharing and ensure uninterrupted usage under disconnected and low bandwidth conditions.

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In this paper, a two-stage algorithm for vector quantization is proposed based on a self-organizing map (SOM) neural network. First, a conventional self-organizing map is modified to deal with dead codebooks in the learning process and is then used to obtain the codebook distribution structure for a given set of input data. Next, subblocks are classified based on the previous structure distribution with a prior criteria. Then, the conventional LBG algorithm is applied to these sub-blocks for data classification with initial values obtained via the SOM. Finally, extensive simulations illustrate that the proposed two-stage algorithm is very effective.

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Many small organisms in various life stages can be transported in the digestive system of larger vertebrates, a process known as endozoochory. Potential dispersal distances of these “propagules” are generally calculated after monitoring retrieval in experiments with resting vector animals. We argue that vectors in natural situations will be actively moving during effective transport rather than resting. We here test for the first time how physical activity of a vector animal might affect its dispersal efficiency. We compared digestive characteristics between swimming, wading (i.e. resting in water) and isolation (i.e. resting in a cage) mallards (Anas platyrhynchos). We fed plastic markers and aquatic gastropods, and monitored retrieval and survival of these propagules in the droppings over 24 h. Over a period of 5 h of swimming, mallards excreted 1.5 times more markers than when wading and 2.3 times more markers than isolation birds, the pattern being reversed over the subsequent period of monitoring where all birds were resting. Retention times of markers were shortened for approximately 1 h for swimming, and 0.5 h for wading birds. Shorter retention times imply higher survival of propagules at increased vector activity. However, digestive intensity measured directly by retrieval of snail shells was not a straightforward function of level of activity. Increased marker size had a negative effect on discharge rate. Our experiment indicates that previous estimates of propagule dispersal distances based on resting animals are overestimated, while propagule survival seems underestimated. These findings have implications for the dispersal of invasive species, meta-population structures and long distance colonization events.