952 resultados para Network pattern language
Resumo:
Background: Developing the knowledge base on the impact of aphasia on people's social lives has become increasingly important in recent times to further our understanding of the broad consequences of communication disability and thus provide appropriate services. Past research clearly indicates that relationships and social activities with family members and others undergo change with the onset of aphasia in an individual, however more evidence of a quantitative nature would be beneficial. Aims: The current research furthers our knowledge by quantifying chronically aphasic older people's regular social contacts and social activities, and places them in context by comparing them with healthy older people of similar age and education. Methods & Procedures: A total of 30 aphasic participants aged 57 to 88 years, and 71 non-aphasic controls aged 62 to 98 years were interviewed by a speech and language therapist using self-report measures of Social Network Analysis (Antonucci & Akiyama, 1987) and Social Activities Checklist (Cruice, 2001, in Worrall & Hickson, 2003). Demographic information was also collected. Descriptive statistics are presented and independent samples t tests were used to examine differences between the groups. Outcomes & Results: Participants with primarily mild to moderate aphasic impairment reported a considerable range of social contacts (5-51) and social activities (8-18). Many significant differences were evident between the two groups' social contacts and activities. On average, aphasic participants had nine fewer social contacts (mainly friend'' relationships) and three fewer social activities (mainly leisure'' activities) than their non-aphasic peers. The majority of controls were satisfied with their social activities, whereas the majority of aphasic participants were not and wanted to be doing more. There were some general similarities between the groups, in terms of range of social contacts, overall pattern of social relationships, and core social activities. Conclusions: Older people with chronic aphasia had significantly fewer social contacts and social activities than their peers. People with aphasia expressed a desire to increase the social activity of their lives. Given the importance of leisure activity and relationships with friends as well as family for positive well-being, speech and language therapists may direct their rehabilitation efforts towards two areas: (1) conversational partner programmes training friends to maintain these relationships; and (2) encouraging and supporting aphasic clients in leisure activities of their choice.
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This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.
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Retrieving large amounts of information over wide area networks, including the Internet, is problematic due to issues arising from latency of response, lack of direct memory access to data serving resources, and fault tolerance. This paper describes a design pattern for solving the issues of handling results from queries that return large amounts of data. Typically these queries would be made by a client process across a wide area network (or Internet), with one or more middle-tiers, to a relational database residing on a remote server. The solution involves implementing a combination of data retrieval strategies, including the use of iterators for traversing data sets and providing an appropriate level of abstraction to the client, double-buffering of data subsets, multi-threaded data retrieval, and query slicing. This design has recently been implemented and incorporated into the framework of a commercial software product developed at Oracle Corporation.
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Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.
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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 reports the initial results of a joint research project carried out by Aston University and Lloyd's Register to develop a practical method of assessing neural network applications. A set of assessment guidelines for neural network applications were developed and tested on two applications. These case studies showed that it is practical to assess neural networks in a statistical pattern recognition framework. However there is need for more standardisation in neural network technology and a wider takeup of good development practice amongst the neural network community.
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In the last decade we have seen an exponential growth of functional imaging studies investigating multiple aspects of language processing. These studies have sparked an interest in applying some of the paradigms to various clinically relevant questions, such as the identification of the cortical regions mediating language function in surgical candidates for refractory epilepsy. Here we present data from a group of adult control participants in order to investigate the potential of using frequency specific spectral power changes in MEG activation patterns to establish lateralisation of language function using expressive language tasks. In addition, we report on a paediatric patient whose language function was assessed before and after a left hemisphere amygdalo-hippocampectomy. Our verb generation task produced left hemisphere decreases in beta-band power accompanied by right hemisphere increases in low beta-band power in the majority of the control group, a previously unreported phenomenon. This pattern of spectral power was also found in the patient's post-surgery data, though not her pre-surgery data. Comparison of pre and post-operative results also provided some evidence of reorganisation in language related cortex both inter- and intra-hemispherically following surgery. The differences were not limited to changes in localisation of language specific cortex but also changes in the spectral and temporal profile of frontal brain regions during verb generation. While further investigation is required to establish concordance with invasive measures, our data suggest that the methods described may serve as a reliable lateralisation marker for clinical assessment. Furthermore, our findings highlight the potential utility of MEG for the investigation of cortical language functioning in both healthy development and pathology.
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The loss of dopamine in idiopathic or animal models of Parkinson's disease induces synchronized low-frequency oscillatory burst-firing in subthalamic nucleus neurones. We sought to establish whether these firing patterns observed in vivo were preserved in slices taken from dopamine-depleted animals, thus establishing a role for the isolated subthalamic-globus pallidus complex in generating the pathological activity. Mice treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) showed significant reductions of over 90% in levels of dopamine as measured in striatum by high pressure liquid chromatography. Likewise, significant reductions in tyrosine hydroxylase immunostaining within the striatum (>90%) and tyrosine hydroxylase positive cell numbers (65%) in substantia nigra were observed. Compared with slices from intact mice, neurones in slices from MPTP-lesioned mice fired significantly more slowly (mean rate of 4.2 Hz, cf. 7.2 Hz in control) and more irregularly (mean coefficient of variation of inter-spike interval of 94.4%, cf. 37.9% in control). Application of ionotropic glutamate receptor antagonists 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) and 2-amino-5-phosphonopentanoic acid (AP5) and the GABAA receptor antagonist picrotoxin caused no change in firing pattern. Bath application of dopamine significantly increased cell firing rate and regularized the pattern of activity in cells from slices from both MPTP-treated and control animals. Although the absolute change was more modest in control slices, the maximum dopamine effect in the two groups was comparable. Indeed, when taking into account the basal firing rate, no differences in the sensitivity to dopamine were observed between these two cohorts. Furthermore, pairs of subthalamic nucleus cells showed no correlated activity in slices from either control (21 pairs) or MPTP-treated animals (20 pairs). These results indicate that the isolated but interconnected subthalamic-globus pallidus network is not itself sufficient to generate the aberrant firing patterns in dopamine-depleted animals. More likely, inputs from other regions, such as the cortex, are needed to generate pathological oscillatory activity. © 2006 IBRO.
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Although reading ability has been related to the processing of simple pitch features such as isolated transitions or continuous modulation spoken language also contains complex patterns of pitch changes that are important for establishing stress location and for segmenting the speech stream. These aspects of spoken language processing depend critically on pitch pattern (global structure) rather than on absolute pitch values (local structure). Here we show that the detection of global structure, and not local structure, is predictive of performance on measures of phonological skill and reading ability, which supports a critical importance of pitch contour processing in the acquisition of literacy.
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EV is a child with a talent for learning language combined with Asperger syndrome. EV’s talent is evident in the unusual circumstances of her acquisition of both her first (Bulgarian) and second (German) languages and the unique patterns of both receptive and expressive language (in both the L1 and L2), in which she shows subtle dissociations in competence and performance consistent with an uneven cognitive profile of skills and abilities. We argue that this case provides support for theories of language learning and usage that require more general underlying cognitive mechanisms and skills. One such account, the Weak Central Coherence (WCC) hypothesis of autism, provides a plausible framework for the interpretation of the simultaneous co-occurrence of EV’s particular pattern of cognitive strengths and weaknesses. Furthermore, we show that specific features of the uneven cognitive profile of Asperger syndrome can help explain the observed language talent displayed by EV. Thus, rather than demonstrating a case where language learning takes place despite the presence of deficits, EV’s case illustrates how a pattern of strengths within this profile can specifically promote language learning.
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The fast spread of the Internet and the increasing demands of the service are leading to radical changes in the structure and management of underlying telecommunications systems. Active networks (ANs) offer the ability to program the network on a per-router, per-user, or even per-packet basis, thus promise greater flexibility than current networks. To make this new network paradigm of active network being widely accepted, a lot of issues need to be solved. Management of the active network is one of the challenges. This thesis investigates an adaptive management solution based on genetic algorithm (GA). The solution uses a distributed GA inspired by bacterium on the active nodes within an active network, to provide adaptive management for the network, especially the service provision problems associated with future network. The thesis also reviews the concepts, theories and technologies associated with the management solution. By exploring the implementation of these active nodes in hardware, this thesis demonstrates the possibility of implementing a GA based adaptive management in the real network that being used today. The concurrent programming language, Handel-C, is used for the description of the design system and a re-configurable computer platform based on a FPGA process element is used for the hardware implementation. The experiment results demonstrate both the availability of the hardware implementation and the efficiency of the proposed management solution.
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Changes in the pattern of activity of neurones within the basal ganglia are relevant in the pathophysiology and symptoms of Parkinson’s disease. The globus pallidus (GP) – subthalamic nucleus (STN) network has been proposed to form a pacemaker driving regenerative synchronous bursting activity. In order to test whether this activity can be sustained in vitro a 20o parasagittal slice of mouse midbrain was developed which preserved functional connectivity between the STN and GP. Mouse STN and GP cells were characterised electrophysiologically by the presence or absence of a voltage sag in response to hyperpolarising current steps indicative of Ih and the presence of rebound depolarisations. The presence of evoked and spontaneous post-synaptic GABA and glutamatergic currents indicated functional connectivity between the STN and GP. In control slices, STN cells fired action potentials at a regular rate, activity which was unaffected by bath application of the GABAA receptor antagonist picrotoxin (50 μM) or the glutamate receptor antagonist CNQX (10 μM). Paired extracellular recordings of STN cells showed uncorrelated firing. Oscillatory burst activity was induced pharmacologically using the glutamate receptor agonist, NMDA (20 μM), in combination with the potassium channel blocker apamin (50 -100 nM). The burst activity was unaffected by bath application of picrotoxin or CNQX while paired STN recordings showed uncorrelated activity indicating that the activity is not produced by the neuronal network. Thus, no regenerative activity is evident in this mouse brain preparation, either in control slices or when bursting is pharmacologically induced, suggesting the requirement of other afferent inputs that are not present in the slice. Using single-unit extracellular recording, dopamine (30 μM) produced an excitation of STN cells. This excitation was independent of synaptic transmission and was mimicked by both the Dl-like receptor agonist SKF38393 (10 μM) and the D2-like receptor agonist quinpirole (10 μM). However, the excitation was partially reduced by the D1-like antagonist SCH23390 (2 μM) but not by the D2-like antagonists sulpiride (10 μM) and eticlopride (10 μM). Using whole-recordings, dopamine was shown to induce membrane depolarisation. This depolarisation was caused either by a D1-like receptor mediated increase in a conductance which reversed at -34 mV, consistent with a non-specific cation conductance, or a D2-like receptor mediated decrease in conductance which reversed around -100 mV, consistent with a potassium conductance. Bath application of dopamine altered the pattern of the burst-firing produced by NMDA an apamin towards a more regular pattern. This effect was associated with a decrease in amplitude and ll1crease in frequency of TTX-resistant plateau potentials which underlie the burst activity.
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Image segmentation is one of the most computationally intensive operations in image processing and computer vision. This is because a large volume of data is involved and many different features have to be extracted from the image data. This thesis is concerned with the investigation of practical issues related to the implementation of several classes of image segmentation algorithms on parallel architectures. The Transputer is used as the basic building block of hardware architectures and Occam is used as the programming language. The segmentation methods chosen for implementation are convolution, for edge-based segmentation; the Split and Merge algorithm for segmenting non-textured regions; and the Granlund method for segmentation of textured images. Three different convolution methods have been implemented. The direct method of convolution, carried out in the spatial domain, uses the array architecture. The other two methods, based on convolution in the frequency domain, require the use of the two-dimensional Fourier transform. Parallel implementations of two different Fast Fourier Transform algorithms have been developed, incorporating original solutions. For the Row-Column method the array architecture has been adopted, and for the Vector-Radix method, the pyramid architecture. The texture segmentation algorithm, for which a system-level design is given, demonstrates a further application of the Vector-Radix Fourier transform. A novel concurrent version of the quad-tree based Split and Merge algorithm has been implemented on the pyramid architecture. The performance of the developed parallel implementations is analysed. Many of the obtained speed-up and efficiency measures show values close to their respective theoretical maxima. Where appropriate comparisons are drawn between different implementations. The thesis concludes with comments on general issues related to the use of the Transputer system as a development tool for image processing applications; and on the issues related to the engineering of concurrent image processing applications.
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The study examines factors influencing language planning decisions in contemporary France. It focuses upon the period 1992-1994, which witnessed the introduction of two major language policy measures, the first an amendment to the French Constitution, in 1992, proclaiming the language of the Republic as French, the second, in 1994, legislation to extend the ambit of the loi Bas-Lauriol, governing the use of the French language in France. The thesis posits a significant role for the pro-reform movement led by the French language association Avenir de la Langue Francaise (ALF) in the introduction and formulation of the policy measures concerned. The movement is depicted as continuing the traditional pattern of intellectual involvement in language planning, whilst also marking the beginning of a highly proactive, and increasingly political approach. Detailed examination of the movement's activities reveals that contextual factors and strategic strength combined to facilitate access to the levers of power, and enabled those involved to exert an impact on policy initiation, formulation, and ultimately implementation. However, ALF's decision to pursue the legislative route led to the expansion of the network of actors involved in language policymaking, and the development of counter-pressure from sectoral groups. It is suggested that this more interventionist approach destabilised the traditionally consensual language policy community, and called into question the quasi-monopoly of the intelligentsia in respect of language policymaking. It raised broader questions relating to freedom of expression and the permissible limits of language regulation in a democracy such as France. It also exposed ongoing ambiguities and inconsistencies in the interpretation of the tenets of language planning.
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This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.