925 resultados para advantages of networking


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The present study focuses on the synthesis of amphiphilic block copolymers containing poly(glycerol monomethacrylate) (PGMMA), showing the advantages of a protection/deprotection strategy based on silyl groups. PGMMA blocks were synthesized via ATRP started by a double functional poly(dimethyl siloxane) (PDMS) macroinitiator of molecular weight ≈7000 g mol-1. The resulting triblock copolymers were characterized by low polydispersity (generally ≤1.1) and their aggregation concentration in water was essentially dominated by the PDMS block length (critical aggregation concentration substantially invariant for GMMA degree of polymerization ≥30). For GMMA blocks with DP > 50, the self-assembly in water produced 35-50 nm spherical micelles, while shorter hydrophilic chains produced larger aggregates apparently displaying worm-like morphologies. Block copolymers with long GMMA chains (DP ≈ 200) produced particularly stable micellar aggregates, which were then selected for a preliminary assessment of the possibility of adsorption of plasma proteins (albumin and fibrinogen); using diffusion NMR as an analytical technique, no significant adsorption was recorded both on micelles and on soluble PGMMA employed as a control, indicating the possibility of a "stealth" behaviour. This journal is © 2013 The Royal Society of Chemistry.

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Advances in statistical physics relating to our understanding of large-scale complex systems have recently been successfully applied in the context of communication networks. Statistical mechanics methods can be used to decompose global system behavior into simple local interactions. Thus, large-scale problems can be solved or approximated in a distributed manner with iterative lightweight local messaging. This survey discusses how statistical physics methodology can provide efficient solutions to hard network problems that are intractable by classical methods. We highlight three typical examples in the realm of networking and communications. In each case we show how a fundamental idea of statistical physics helps solve the problem in an efficient manner. In particular, we discuss how to perform multicast scheduling with message passing methods, how to improve coding using the crystallization process, and how to compute optimal routing by representing routes as interacting polymers.

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The response of single fibres of the human cochlear nerve to electrical stimulation by a cochlear implant has previously been inferred from the response of the cochlear nerve in other mammals. These experiments are hindered by stimulus artefact and the range of stimulus currents used is therefore much less than the perceptual dynamic range (from threshold to discomfort) of human subjects. We have investigated use of the sciatic nerve of the toad Xenopus laevis as a convenient physiological model of the human cochlear nerve. Use of this completely dissected nerve reduces the problems of stimulus artefact whilst maintaining the advantages of a physiological preparation. The validity of the model was assessed by measuring the refractory periods, excitation time-constant, and relative spread of single fibres using microelectrode recording. We have also investigated the response of nerve fibres to sinusoidal stimulation. Based on these measurements, we propose that the sciatic nerve may be a suitable model of the human cochlear nerve if the timescales of stimuli are decreased by a factor of about five to compensate for the slower dynamics of the sciatic nerve and if noise is added to the stimuli to compensate for the lower internal noise of sciatic nerve fibres.

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An important task for a direct mailing company is to detect potential customers in order to avoid unnecessary and unwanted mailing. This paper describes a non-linear method to predict profiles of potential customers using dARTMAP, ARTMAP-IC, and Fuzzy ARTMAP neural networks. The paper discusses advantages of the proposed approaches over similar techniques based on MLP neural networks.

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This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.

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Transition P Systems are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations that are determined by the membrane structure and multisets present inside membranes. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of active evolution rules subset inside each membrane of the P system. But, to establish the active evolution rules subset, it is required the previous calculation of useful and applicable rules. Hence, computation of applicable evolution rules subset is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in every evolution step. The work presented here shows advantages of incorporating decision trees in the evolution rules applicability algorithm. In order to it, necessary formalizations will be presented to consider this as a classification problem, the method to obtain the necessary decision tree automatically generated and the new algorithm for applicability based on it.

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The paper focuses on the rapid development of the digital culture and the challenges it imposes to human creativity. It analyses e-learning, digital entertainment, digital art and the issues of creativity and improvisation. It also presents a classification of the levels in the creative structure including hardware and software tools; product developers; creators and end users. Special attention is paid to the advantages of the new digital culture and the responsibilities of all people who create it or use it. We conclude that more attention should be paid to the threats and to ways of boosting positive creativity in the various fields of application of information and communication technologies.

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The evaluation from experimental data, of physical quantities, which enter into the electromagnetic Maxwell equations, is described as inverse optical problem. The functional relations between the dependent and independent variables are of transcendental character and numeric procedures for evaluation of the unknowns are largely used. Herein, we discuss a direct approach to the solution, illustrated by a specific example of determination of thin films optical constants from spectrophotometric data. New algorithm is proposed for the parameters evaluation, which does not need an initial guess of the unknowns and does not use iterative procedures. Thus we overcome the intrinsic deficiency of minimization techniques, such as gradient search methods, Simplex methods, etc. The price of it is a need of more computing power, but our algorithm is easily implemented in structures such as grid clusters. We show the advantages of this approach and its potential for generalization to other inverse optical problems.

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Summarizing the accumulated experience for a long time in the polyparametric cognitive modeling of different physiological processes (electrocardiogram, electroencephalogram, electroreovasogram and others) and the development on this basis some diagnostics methods give ground for formulating a new methodology of the system analysis in biology. The gist of the methodology consists of parametrization of fractals of electrophysiological processes, matrix description of functional state of an object with a unified set of parameters, construction of the polyparametric cognitive geometric model with artificial intelligence algorithms. The geometry model enables to display the parameter relationships are adequate to requirements of the system approach. The objective character of the elements of the models and high degree of formalization which facilitate the use of the mathematical methods are advantages of these models. At the same time the geometric images are easily interpreted in physiological and clinical terms. The polyparametric modeling is an object oriented tool possessed advances functional facilities and some principal features.

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This article presents the principal results of the doctoral thesis “Direct Operational Methods in the Environment of a Computer Algebra System” by Margarita Spiridonova (Institute of mathematics and Informatics, BAS), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 23 March, 2009.

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The multi-polar world in which we now live and work demands re-examination and refinement of the traditional understanding of the internationalization strategies and competitive advantages of multinational firms by incorporating the characteristics of firms from emerging economies. Based on interviews in four Indian multinationals in different industry segments, we present the "voices" of Indian corporate leaders to provide preliminary evidence on the primary motives behind the internationalization process of emerging multinationals from the perspective of linkage, leverage and learning (LLL). We show how the case study organizations have evolved themselves to become credible global players by leveraging on their learning through targeted acquisitions in developed markets to acquire intangible assets and/or following global clients in search of new markets and competitive advantages.

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Knowledge accessing from external organisations is important to firms, especially entrepreneurial ones which often cannot generate internally all the knowledge necessary for innovation. There is, however, a lack of evidence concerning the association between the evolution of firms and the evolution of their networks. The aim of this paper is to begin to fill this gap by undertaking an exploratory analysis of the relationship between the vintage of firms and their knowledge sourcing networks. Drawing on an analysis of firms in the UK, the paper finds some evidence of a U-shaped relationship existing between firm age and the frequency of accessing knowledge from certain sources. Emerging entrepreneurial firms tend to be highly active with regard to accessing knowledge for a range of sources and geographic locations, with the rate of networking dropping somewhat during the period of peak firm growth. For instance, it is found that firms tend to less frequently access knowledge sources such as universities and research institutes in their own region during a stage of peak turnover growth. Overall, the results suggest a complex relationship between the lifecycle of the firm and its networking patterns. It is concluded that policymakers need to become more aware that network formation and utilisation by firms is likely to vary dependent upon their lifecycle position.

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Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors. All rights reserved.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016