951 resultados para Self-organizing networks


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The paper analyses the emergence of group-specific attitudes and beliefs about tax compliance when individuals interact in a social network. It develops a model in which taxpayers possess a range of individual characteristics – including attitude to risk, potential for success in self-employment, and the weight attached to the social custom for honesty – and make an occupational choice based on these characteristics. Occupations differ in the possibility for evading tax. The social network determines which taxpayers are linked, and information about auditing and compliance is transmitted at meetings between linked taxpayers. Using agent-based simulations, the analysis demonstrates how attitudes and beliefs endogenously emerge that differ across sub-groups of the population. Compliance behaviour is different across occupational groups, and this is reinforced by the development of group-specific attitudes and beliefs. Taxpayers self-select into occupations according to the degree of risk aversion, the subjective probability of audit is sustained above the objective probability, and the weight attached to the social custom differs across occupations. These factors combine to lead to compliance levels that differ across occupations.

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Direct electrochemical templating is carried out using a thin layer of a self-assembled diamond phase (QIID) of phytantriol to create a platinum film with a novel nanostructure. Small-angle X-ray scattering shows that the nanostructured platinum films are asymmetrically templated and exhibit “single diamond” morphology with Fd3m symmetry.

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The UK construction industry labour market is characterised by high levels of self-employment, sub-contracting, informality and flexibility. A corollary of this, and a sign of the increasing globalisation of construction, has been an increasing reliance on migrant labour, particularly that from the Eastern European Accession states. Yet, little is known about how their experiences within and outside of work shape their work in the construction sector. In this context better qualitative understandings of the social and communication networks through which migrant workers gain employment, create routes through the sector and develop their role/career are needed. We draw on two examples from a short-term ethnographic study of migrant construction worker employment experiences and practices in the town of Crewe in Cheshire, UK, to demonstrate how informal networks intersect with formal elements of the sector to facilitate both recruitment and up-skilling. Such research knowledge, we argue, offers new evidence of the importance of attending to migrant worker’s own experiences in the development of more transparent recruitment processes.

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This paper seeks to examine the particular operations of gender and cultural politics that both shaped and restrained possible 'networked' interactions between Jamaican women and their British 'motherlands' during the first forty years of the twentieth century. Paying particular attention to the poetry of Albinia Catherine MacKay (a Scots Creole) and the political journalism of Una Marson (a black Jamaica), I shall seek to examine why both writers speak in and of voices out of place. MacKay's poems work against the critical pull of transnational modernism to reveal aesthetic and cultural isolation through a model of strained belonging in relation to both her Jamaica home and an ancestral Scotland. A small number of poems from her 1912 collection that are dedicated to the historical struggle between the English and Scots for the rule of Scotland and cultural self-determination, some of which are written in a Scottish idiom, may help us to read the complex cultural negotiations that silently inform the seemingly in commensurability of location and locution revealed in these works. In contrast, Marson's journalism, although less known even than her creative writings, is both politically and intellectually radical in its arguments concerning the mutual articulation of race and gender empowerment. However, Marson remains aware of her inability to articulate these convictions with force in a British context and thereby of the way in which speaking out of place also silences her.

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This chapter presents selected literature examples to review the development of the use of donor–acceptor π–π stacking interactions as transient cross-links in supramolecular polymer networks. The chapter examines notable examples of these highly specific and directional interactions and illustrates how they can be utilised to reliably produce functional supramolecular, self-assembled systems. Knowledge gained from these fundamental studies has enabled the design, synthesis and application of donor–acceptor stacked supramolecular motifs in non-covalent polymer networks, which is exemplified through detailing the production, physical properties and optimisation of healable materials.

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In this work, we introduce dipeptides containing tryptophan N-capped with the nonsteroidal anti-inflammatory drug naproxen and C-terminal dehydroamino acids, dehydrophenylalanine (ΔPhe), dehydroaminobutyric acid (ΔAbu), and dehydroalanine (ΔAla) as efficacious protease resistant hydrogelators. Optimized conditions for gel formation are reported. Transmission electron microscopy experiments revealed that the hydrogels consist of networks of micro/nanosized fibers formed by peptide self-assembly. Fluorescence and circular dichroism spectroscopy indicate that the self-assembly process is driven by stacking interactions of the aromatic groups. The naphthalene groups of the naproxen moieties are highly organized in the fibers through chiral stacking. Rheological experiments demonstrated that the most hydrophobic peptide (containing C-terminal ΔPhe) formed more elastic gels at lower critical gelation concentrations. This gel revealed irreversible breakup, while the C-terminal ΔAbu and ΔAla gels, although less elastic, exhibited structural recovery and partial healing of the elastic properties. A potential antitumor thieno[3,2-b]pyridine derivative was incorporated (noncovalently) into the gel formed by the hydrogelator containing C-terminal ΔPhe residue. Fluorescence and Förster resonance energy transfer measurements indicate that the drug is located in a hydrophobic environment, near/associated with the peptide fibers, establishing this type of hydrogel as a good drug-nanocarrier candidate.

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Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

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This Letter describes a method for the quantification of the diversity of non-linear dynamics in complex networks as a consequence of self-avoiding random walks. The methodology is analyzed in the context of theoretical models and illustrated with respect to the characterization of the accessibility in urban streets. (C) 2008 Elsevier B.V. All rights reserved.

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Ethylene glycol dimethacrylate (EGDMA) and/or triethylene glycol dimethacrylate (TEGDMA) oligomers formation was catalyzed in aqueous medium by horseradish peroxidase (HRP) in the presence of H(2)O(2) at room temperature. EGDMA and/or TEGDMA oligomers were characterized by means of gel permeation chromatography, infrared vibrational spectroscopy and (1)H NMR spectroscopy. Self-assembling of oligomers led to right-angled crystalline particles, as evidenced by scanning electron microscopy and differential scanning calorimetry. EGDMA, TEGDMA and EGDMA-co-TEGDMA oligomers synthesized in the presence of HRP-H(2)O(2) system presented pendant vinyl groups along the chains. good solubility in chloroform, and well-defined melting point. These features evidenced few cross-linking or cyclization and revealed that the catalytic properties of HRP led to oligomeric materials with new characteristics. (C) 2008 Elsevier B.V. All rights reserved.

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The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

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Sociedades pós-modernas caracterizam-se pela transição de economias baseadas em ativos tangíveis para economias de conhecimento, onde indivíduos vivenciam uma imprescindível conectividade, mas ao mesmo tempo, experimentam um enfraquecimento das estruturas sociais, que tem generado uma crescente necessidade de se criar bases cognitivas e afetivas para a vida (Rheingold, 1992; Wasko & Farah, 2005; Arvidsson, 2008). Nesse cenário se desenvolve o fenômeno das redes sociais virtuais, agregando milhões de pessoas que compartilham mensagens de texto, imagens e vídeos todos os dias (Nielsen, 2012) fazendo com que organizações privadas foquem cada vez mais seus investimentos para acompanhar as novas tendências (McWilliam, 2000; Reichheld & Schefter, 2000; Yoo, Suh & Lee, 2002; Arvidsson, 2008). Consequentemente, uma das mais importantes questões que vem ganhando importância no meio academico e entre profissionais da área é justamente: por que as pessoas compartilham conhecimento online? (Monge, Fulk, Kalman, Flanigan, Parnassa & Rumsey, 1998; Lin, 2001) Por meio de uma metodologia de estudo de caso conduzida no Brasil e na França, este estudo objetiva produzir uma relevante revisão teórica acerca do tema, trazendo novas idéias de diferentes contextos, e propondo um modelo para avaliar as principais motivações que conduzem indivíduos a compartilhar conhecimento em redes sociais virtuais. Essas razões foram estruturadas em cinco dimensões: capital estrutural, cognitivo e relacional, motivações pessoais e razões monetárias (Nahapiet & Ghoshal, 1998; Wasko & Faraj, 2005; Chiu et al, 2006). As evidências sugerem que o processo de participar e compartilhar conhecimento em redes sociais virtuais é resultado de uma complexa combinação de motivações de orientação pessoal e coletiva, que parecem variar pouco de acordo com os diferentes objetivos e contextos dessas comunidades, onde as razões financeiras parecem ser secundárias.

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ABSTRACT: The femtocell concept aims to combine fixed-line broadband access with mobile telephony using the deployment of low-cost, low-power third and fourth generation base stations in the subscribers' homes. While the self-configuration of femtocells is a plus, it can limit the quality of service (QoS) for the users and reduce the efficiency of the network, based on outdated allocation parameters such as signal power level. To this end, this paper presents a proposal for optimized allocation of users on a co-channel macro-femto network, that enable self-configuration and public access, aiming to maximize the quality of service of applications and using more efficiently the available energy, seeking the concept of Green networking. Thus, when the user needs to connect to make a voice or a data call, the mobile phone has to decide which network to connect, using the information of number of connections, the QoS parameters (packet loss and throughput) and the signal power level of each network. For this purpose, the system is modeled as a Markov Decision Process, which is formulated to obtain an optimal policy that can be applied on the mobile phone. The policy created is flexible, allowing different analyzes, and adaptive to the specific characteristics defined by the telephone company. The results show that compared to traditional QoS approaches, the policy proposed here can improve energy efficiency by up to 10%.

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Planar waveguides with controlled refractive index were produced using thin films of sol-gel derived organic-inorganic hybrids, so called di-ureasils. Spectroscopic ellipsometry was used to characterize the films thickness and refractive index. UV-laser direct-writing method was used to produce Y-splitter structures with coupling ratio of 50% without the need of photoinitiators.

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

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In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.