869 resultados para Radiality constraints in distribution systems


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We investigate electronic mitigation of linear and non-linear fibre impairments and compare various digital signal processing techniques, including electronic dispersion compensation (EDC), single-channel back-propagation (SC-BP) and back-propagation with multiple channel processing (MC-BP) in a nine-channel 112 Gb/s PM-mQAM (m=4,16) WDM system, for reaches up to 6,320 km. We show that, for a sufficiently high local dispersion, SC-BP is sufficient to provide a significant performance enhancement when compared to EDC, and is adequate to achieve BER below FEC threshold. For these conditions we report that a sampling rate of two samples per symbol is sufficient for practical SC-BP, without significant penalties.

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To investigate investment behaviour the present study applies panel data techniques, in particular the Arellano-Bond (1991) GMM estimator, based on data on Estonian manufacturing firms from the period 1995-1999. We employ the model of optimal capital accumulation in the presence of convex adjustment costs. The main research findings are that domestic companies seem to be financially more constrained than those where foreign investors are present, and also, smaller firms are more constrained than their larger counterparts.

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The behaviour of self adaptive systems can be emergent. The difficulty in predicting the system's behaviour means that there is scope for the system to surprise its customers and its developers. Because its behaviour is emergent, a self-adaptive system needs to garner confidence in its customers and it needs to resolve any surprise on the part of the developer during testing and mainteinance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system's behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, a means needs to be found to explain the current behaviour of the system and the reasons that brought that behaviour about. We propose the use of goal-based models during runtime to offer self-explanation of how a system is meeting its requirements, and why the means of meeting these were chosen. We discuss the results of early experiments in self-explanation, and set out future work. © 2012 C.E.S.A.M.E.S.

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Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

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We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.

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Nonlinear systems with periodic variations of nonlinearity and/or dispersion occur in a variety of physical problems and engineering applications. The mathematical concept of dispersion managed solitons already has made an impact on the development of fibre communications, optical signal processing and laser science. We overview here the field of the dispersion managed solitons starting from mathematical theories of Hamiltonian and dissipative systems and then discuss recent advances in practical implementation of this concept in fibre-optics and lasers.

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In this paper, we present a novel approach to modeling financing constraints of firms. Specifically, we adopt an approach in which firm-level investment is a nonparametric function of some relevant firm characteristics, cash flow in particular. This enables us to generate firm-year specific measures of cash flow sensitivity of investment. We are therefore able to draw conclusions about financing constraints of individual firms as well as cohorts of firms without having to split our sample on an ad hoc basis. This is a significant improvement over the stylized approach that is based on comparison of point estimates of cash flow sensitivity of investment of the average firm of ad hoc sub-samples of firms. We use firm-level data from India to highlight the advantages of our approach. Our results suggest that the estimates generated by this approach are meaningful from an economic point of view and are consistent with the literature. © 2014 © 2014 Taylor & Francis.

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A new generalized sphere decoding algorithm is proposed for underdetermined MIMO systems with fewer receive antennas N than transmit antennas M. The proposed algorithm is significantly faster than the existing generalized sphere decoding algorithms. The basic idea is to partition the transmitted signal vector into two subvectors x and x with N - 1 and M - N + 1 elements respectively. After some simple transformations, an outer layer Sphere Decoder (SD) can be used to choose proper x and then use an inner layer SD to decide x, thus the whole transmitted signal vector is obtained. Simulation results show that Double Layer Sphere Decoding (DLSD) has far less complexity than the existing Generalized Sphere Decoding (GSDs).

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An improved digital backward propagation (DBP) is proposed to compensate inter-nonlinear effects and dispersion jointly in WDM systems based on an advanced perturbation technique (APT). A non-iterative weighted concept is presented to replace the iterative in analytical recursion expression, which can dramatically simplify the complexity and improve accuracy compared to the traditional perturbation technique (TPT). Furthermore, an analytical recursion expression of the output after backward propagation is obtained initially. Numerical simulations are executed for various parameters of the transmission system. The results indicate that the advanced perturbation technique will relax the step size requirements and reduce the oversampling factor when launch power is higher than -2 dBm. We estimate this technique will reduce computational complexity by a factor of around seven with respect to the conventional DBP. © 2013 Optical Society of America.

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The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

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A statistical approach to evaluate numerically transmission distances in optical communication systems was described. The proposed systems were subjected to strong patterning effects and strong intersymbol interference. The dependence of transmission distance on the total number of bits was described. Normal and Gaussian distributions were used to derive the error probability.

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Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.