981 resultados para multi-mode approximation
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A simple and cost-effective technique for generating a flat, square-shaped multi-wavelength optical comb with 42.6 GHz line spacing and over 0.5 THz of total bandwidth is presented. A detailed theoretical analysis is presented, showing that using two concatenated modulators driven with voltages of 3.5 Vp are necessary to generate 11 comb lines with a flatness below 2dB. This performance is experimentally demonstrated using two cascaded Versawave 40 Gbit/s low drive voltage electro-optic polarisation modulators, where an 11 channel optical comb with a flatness of 1.9 dB and a side-mode-suppression ratio (SMSR) of 12.6 dB was obtained.
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Using three fibre gratings with excessively tilted structures in the cavity, we have experimentally demonstrated a multiwavelength switchable erbium-doped fibre ring laser system. The three tilted gratings act as in-fibre polariser and polarisation dependent loss filters to induce the polarisation hole burning effect in the cavity for the operation of the laser at single, double, triple and quadruple wavelengths. The laser system has demonstrated good stability under room temperature conditions and also achieved a high degree of polarization (~30dB), high optical signal to noise ratio (up to 63dB) and high side mode suppression (~50dB). The system has also been investigated for temperature and strain sensing by subjecting the seeding fibre Bragg gratings (FBG) to temperature and strain variations. Since the loss band of the polarisation dependent loss filter is broader than the bandwidth of the seeding FBG, the laser output shifts in wavelength with the applied temperature and strain. The fibre ring laser has shown good responses to the temperature and strain, providing sensitivities of approximately 11.7 pm/°C and 0.85pm/µe respectively.
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Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.
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We study polarization dynamics of a harmonic mode-locked erbium-doped fiber laser with carbon nanotubes absorber. New types of vector solitons are shown for multi-pulse and harmonic mode-locked operation with locked, switching and precessing polarization states. © 2014 OSA.
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2000 Mathematics Subject Classification: 62G07, 62L20.
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For a fibre Raman amplifier with randomly varying birefringence, we provide insight on the validity of previously explored multi-scale techniques leading to polarisation pulling of the signal state of polarisation to the pump state of polarisation. Unlike previous study, we demonstrate that in addition to polarisation pulling a new random birefringence-mediated phenomenon that goes beyond existing multi-scale techniques can boost resonance-like gain fluctuations similar to the Stochastic Anti-Resonance. For mode locked fibre lasers we report on fast and slow polarisation dynamics of fundamental, bound state, and multipulsing vector solitons along with stretched pulses. We demonstrate that tuning cavity anisotropy and birefringence along with parameters of an injected signal with randomly varying state of polarisation provides access to the variety of vector waveforms previously unexplored.
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Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.
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The aim of this work is to evaluate the SEE sensitivity of a multi-core processor having implemented ECC and parity in their cache memories. Two different application scenarios are studied. The first one configures the multi-core in Asymmetric Multi-Processing mode running a memory-bound application, whereas the second one uses the Symmetric Multi-Processsing mode running a CPU-bound application. The experiments were validated through radiation ground testing performed with 14 MeV neutrons on the Freescale P2041 multi-core manufactured in 45nm SOI technology. A deep analysis of the observed errors in cache memories was carried-out in order to reveal vulnerabilities in the cache protection mechanisms. Critical zones like tag addresses were affected during the experiments. In addition, the results show that the sensitivity strongly depends on the application and the multi-processsing mode used.
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We present the first (to the best of our knowledge) experimental demonstration of a 56 Gb/s multi-band carrierless amplitude and phase modulation (CAP) signal transmission over an 80-km single-mode fiber link with zero overhead pre-FEC signal recovery and enhanced timing jitter tolerance for optical data center interconnects.
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Ticket distribution channels for live music events have been revolutionised through the increased take-up of internet technologies, and the music supply-chain has evolved into a multi-channel value network. The assumption that this creates increased consumer autonomy and improved service quality is explored here through a case-study of the ticket pre-sale for the US leg of the Depeche Mode 2005–06 World Tour, which utilises an innovative virtual channel strategy, promoted as a service to loyal fans. A multi-method analysis, adopting Kozinets' (2002) Kozinets, R. V. 2002. The field behind the screen: using netnography for marketing research in online communities. Journal of Marketing Research, 39: 61–72. [CrossRef], [Web of Science ®] netnography methodology, is employed to map responses of the band's serious fan base on an internet message board (IMB) throughout the tour pre-sale. The analysis focuses on concerns of pricing, ethics, scope of the offer, use of technology, service quality and perceived brand performance fit of channel partners. Findings indicate that fans behaviour is unpredictable in response to channel partners' performance, and that such offers need careful management to avoid alienation of loyal consumers.
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Aluminium cells involve a range of complex physical processes which act simultaneously to provide a narrow satisfactory operating range. These processes involve electromagnetic fields, coupled with heat transfer and phase change, two phase fluid flow with a range of complexities plus the development of stress in the cell structure. All of these phenomena are coupled in some significant sense and so to provide a comprehensive model of these processes involves their representation simultaneously. Conventionally, aspects of the process have been modeled separately using uncoupled estimates of the effects of the other phenomena; this has enabled the use of standard commercial CFD and FEA tools. In this paper we will describe an approach to the modeling of aluminium cells which describes all the physics simultaneously. This approach uses a finite volume approximation for each of the phenomena and facilitates their interactions directly in the modeling-the complex geometries involved are addressed by using unstructured meshes. The very challenging issues to be overcome in this venture will be outlined and some preliminary results will be shown.
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This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.
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Network Virtualization is a key technology for the Future Internet, allowing the deployment of multiple independent virtual networks that use resources of the same basic infrastructure. An important challenge in the dynamic provision of virtual networks resides in the optimal allocation of physical resources (nodes and links) to requirements of virtual networks. This problem is known as Virtual Network Embedding (VNE). For the resolution of this problem, previous research has focused on designing algorithms based on the optimization of a single objective. On the contrary, in this work we present a multi-objective algorithm, called VNE-MO-ILP, for solving dynamic VNE problem, which calculates an approximation of the Pareto Front considering simultaneously resource utilization and load balancing. Experimental results show evidences that the proposed algorithm is better or at least comparable to a state-of-the-art algorithm. Two performance metrics were simultaneously evaluated: (i) Virtual Network Request Acceptance Ratio and (ii) Revenue/Cost Relation. The size of test networks used in the experiments shows that the proposed algorithm scales well in execution times, for networks of 84 nodes
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When designing systems that are complex, dynamic and stochastic in nature, simulation is generally recognised as one of the best design support technologies, and a valuable aid in the strategic and tactical decision making process. A simulation model consists of a set of rules that define how a system changes over time, given its current state. Unlike analytical models, a simulation model is not solved but is run and the changes of system states can be observed at any point in time. This provides an insight into system dynamics rather than just predicting the output of a system based on specific inputs. Simulation is not a decision making tool but a decision support tool, allowing better informed decisions to be made. Due to the complexity of the real world, a simulation model can only be an approximation of the target system. The essence of the art of simulation modelling is abstraction and simplification. Only those characteristics that are important for the study and analysis of the target system should be included in the simulation model. The purpose of simulation is either to better understand the operation of a target system, or to make predictions about a target system’s performance. It can be viewed as an artificial white-room which allows one to gain insight but also to test new theories and practices without disrupting the daily routine of the focal organisation. What you can expect to gain from a simulation study is very well summarised by FIRMA (2000). His idea is that if the theory that has been framed about the target system holds, and if this theory has been adequately translated into a computer model this would allow you to answer some of the following questions: · Which kind of behaviour can be expected under arbitrarily given parameter combinations and initial conditions? · Which kind of behaviour will a given target system display in the future? · Which state will the target system reach in the future? The required accuracy of the simulation model very much depends on the type of question one is trying to answer. In order to be able to respond to the first question the simulation model needs to be an explanatory model. This requires less data accuracy. In comparison, the simulation model required to answer the latter two questions has to be predictive in nature and therefore needs highly accurate input data to achieve credible outputs. These predictions involve showing trends, rather than giving precise and absolute predictions of the target system performance. The numerical results of a simulation experiment on their own are most often not very useful and need to be rigorously analysed with statistical methods. These results then need to be considered in the context of the real system and interpreted in a qualitative way to make meaningful recommendations or compile best practice guidelines. One needs a good working knowledge about the behaviour of the real system to be able to fully exploit the understanding gained from simulation experiments. The goal of this chapter is to brace the newcomer to the topic of what we think is a valuable asset to the toolset of analysts and decision makers. We will give you a summary of information we have gathered from the literature and of the experiences that we have made first hand during the last five years, whilst obtaining a better understanding of this exciting technology. We hope that this will help you to avoid some pitfalls that we have unwittingly encountered. Section 2 is an introduction to the different types of simulation used in Operational Research and Management Science with a clear focus on agent-based simulation. In Section 3 we outline the theoretical background of multi-agent systems and their elements to prepare you for Section 4 where we discuss how to develop a multi-agent simulation model. Section 5 outlines a simple example of a multi-agent system. Section 6 provides a collection of resources for further studies and finally in Section 7 we will conclude the chapter with a short summary.
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Medicinal plants bave gained a special attention in the last years, due to its renowned health benefits, such
as antimicrobial effects [I]. In fact, several natural matrices bave been increasingly studied, namely for its
antifungal activity against opportunistic fungi [2,3]. Candida species, although commensa!
microorganisms, have caused severe organic dysfunctions to the host, once current antifungal agents have
lost their recognized efficiency [2]. So, numerous studies have been carried out focusing the mechanisms
of acquired drug-resistance by Candida species [