NLSE-based model of a random distributed feedback fiber laser

In this work we propose a NLSE-based model of power and spectral properties of the random distributed feedback (DFB) fiber laser. The model is based on coupled set of non-linear Schrödinger equations for pump and Stokes waves with the distributed feedback due to Rayleigh scattering. The model considers random backscattering via its average strength, i.e. we assume that the feedback is incoherent. In addition, this allows us to speed up simulations sufficiently (up to several orders of magnitude). We found that the model of the incoherent feedback predicts the smooth and narrow (comparing with the gain spectral profile) generation spectrum in the random DFB fiber laser. The model allows one to optimize the random laser generation spectrum width varying the dispersion and nonlinearity values: we found, that the high dispersion and low nonlinearity results in narrower spectrum that could be interpreted as four-wave mixing between different spectral components in the quasi-mode-less spectrum of the random laser under study could play an important role in the spectrum formation. Note that the physical mechanism of the random DFB fiber laser formation and broadening is not identified yet. We investigate temporal and statistical properties of the random DFB fiber laser dynamics. Interestingly, we found that the intensity statistics is not Gaussian. The intensity auto-correlation function also reveals that correlations do exist. The possibility to optimize the system parameters to enhance the observed intrinsic spectral correlations to further potentially achieved pulsed (mode-locked) operation of the mode-less random distributed feedback fiber laser is discussed.

Development of Database for Distributed Information Measurement and Control System

The purpose of this work is the development of database of the distributed information measurement and control system that implements methods of optical spectroscopy for plasma physics research and atomic collisions and provides remote access to information and hardware resources within the Intranet/Internet networks. The database is based on database management system Oracle9i. Client software was realized in Java language. The software was developed using Model View Controller architecture, which separates application data from graphical presentation components and input processing logic. The following graphical presentations were implemented: measurement of radiation spectra of beam and plasma objects, excitation function for non-elastic collisions of heavy particles and analysis of data acquired in preceding experiments. The graphical clients have the following functionality of the interaction with the database: browsing information on experiments of a certain type, searching for data with various criteria, and inserting the information about preceding experiments.

Modeling of the spectrum in a random distributed feedback fiber laser within the power balance modes

The simplest model for a description of the random distributed feedback (RDFB) Raman fiber laser is a power balance model describing the evolution of the intensities of the waves over the fiber length. The model predicts well the power performances of the RDFB fiber laser including the generation threshold, the output power and pump and generation wave intensity distributions along the fiber. In the present work, we extend the power balance model and modify equations in such a way that they describe now frequency dependent spectral power density instead of integral over the spectrum intensities. We calculate the generation spectrum by using the depleted pump wave longitudinal distribution derived from the conventional power balance model. We found the spectral balance model to be sufficient to account for the spectral narrowing in the RDFB laser above the threshold of the generation. © 2014 SPIE.

Random distributed feedback fiber laser of ultimate efficiency

We demonstrate a random fiber laser of ultimate efficiency. More than 2 Watts are generated from 0.5W of pump excess over the generation threshold. At higher power, an optical efficiency corresponds to the quantum limit.

SNR enhanced distributed vibration fiber sensing system employing polarization OTDR and ultraweak FBGs

A distributed fiber sensing system based on ultraweak FBGs (UWFBGs) assisted polarization optical time-domain reflectometry (POTDR) is proposed for load and vibration sensing with improved signal-to-noise ratio (SNR) and sensitivity. UWFBGs with reflectivity higher than Rayleigh scattering coefficient per pulse are induced into a POTDR system to increase the intensity of the back signal. The performance improvement of the system has been studied. The numerical analysis has shown that the SNR and sensitivity of the system can be effectively improved by integrating UWFBGs along the whole sensing fiber, which has been clearly proven by the experiment. The experimental results have shown that by using UWFBGs with 1.1 x 10-5 reflectivity and 10-m interval distance, the SNR is improved by 11 dB, and the load and vibration sensitivities of the POTDR are improved by about 10.7 and 9 dB, respectively.

Random distributed feedback Raman fiber laser with polarized pumping

In this letter, the polarization properties of a random fiber laser operating via Raman gain and random distributed feedback owing to Rayleigh scattering are investigated for the first time. Using polarized pump, the partially polarized generation is obtained with a generation spectrum exhibiting discrete narrow spectral features contrary to the smooth spectrum observed for the depolarized pump. The threshold, output power, degree of polarization and the state of polarization (SOP) of the lasing can be significantly influenced by the SOP of the pump. Fine narrow spectral components are also sensitive to the SOP of the pump wave. Furthermore, we found that random lasing's longitudinal power distributions are different in the case of polarized and depolarized pumping that results in considerable reduction of the generation slope efficiency for the polarized radiation. Our results indicate that polarization effects play an important role on the performance of the random fiber laser. This work improves the understanding of the physics of random lasing in fibers and makes a step forward towards the establishment of the vector model of random fiber lasers.

HW Implementation of a Optimized Algorithm for the Application of Active Rules in a Transition P-system

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. They are inspired in the way cells process chemical compounds, energy and information. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This work is part of an exhaustive investigation line. The final objective is to implement a HW system that evolves as it makes a transition P-system. To achieve this objective, it has been carried out a division of this generic system in several stages, each of them with concrete matters. In this paper the stage is developed by obtaining the part of the system that is in charge of the application of the active rules. To count the number of times that the active rules is applied exist different algorithms. Here, it is presents an algorithm with improved aspects: the number of necessary iterations to reach the final values is smaller than the case of applying step to step each rule. Hence, the whole process requires a minor number of steps and, therefore, the end of the process will be reached in a shorter length of time.

Application of long-period-grating sensors to respiratory plethysmography

A series of in-line curvature sensors on a garment are used to monitor the thoracic and abdominal movements of a human during respiration. These results are used to obtain volumetric tidal changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The curvature sensors are based on long-period gratings (LPGs) written in a progressive three-layered fiber to render the LPGs insensitive to the refractive index external to the fiber. A curvature sensor consists of the fiber long-period grating laid on a carbon fiber ribbon, which is then encapsulated in a low-temperature curing silicone rubber. The sensors have a spectral sensitivity to curvature, dλ/dR from ∼7-nm m to ∼9-nm m. The interrogation technique is borrowed from derivative spectroscopy and monitors the changes in the transmission spectral profile of the LPG's attenuation band due to curvature. The multiplexing of the sensors is achieved by spectrally matching a series of distributed feedback (DFB) lasers to the LPGs. The versatility of this sensing garment is confirmed by it being used on six other human subjects covering a wide range of body mass indices. Just six fully functional sensors are required to obtain a volumetric error of around 6%. © 2007 Society of Photo-Optical Instrumentation Engineers.

Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses

We show theoretically and experimentally a mechanismbehind the emergence of wide or bimodal protein distributions in biochemical networks with nonlinear input-output characteristics (the dose-response curve) and variability in protein abundance. Large cell-to-cell variation in the nonlinear dose-response characteristics can be beneficial to facilitate two distinct groups of response levels as opposed to a graded response. Under the circumstances that we quantify mathematically, the two distinct responses can coexist within a cellular population, leading to the emergence of a bimodal protein distribution. Using flow cytometry, we demonstrate the appearance of wide distributions in the hypoxia-inducible factor-mediated response network in HCT116 cells. With help of our theoretical framework, we perform a novel calculation of the magnitude of cell-to-cell heterogeneity in the dose-response obtained experimentally. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Static, dynamic, and adaptive heterogeneity in distributed smart camera networks

We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

Maximum Principle and Its Application for the Time-Fractional Diffusion Equations

MSC 2010: 26A33, 33E12, 35B45, 35B50, 35K99, 45K05 Dedicated to Professor Rudolf Gorenflo on the occasion of his 80th anniversary

A gloss composition and context clustering based distributed word sense representation model

In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

Impacts of distributed generation on low-voltage distribution network protection

This paper reports work of a MEng student final year project, which looks in detail at the impacts that distributed generation can have on existing low-voltage distribution network protection systems. After a review of up-to-date protection issues, this paper will investigate several key issues that face distributed generation connections when it comes to network protection systems. These issues include, the blinding of protection systems, failure to automatically reclose, unintentional islanding, loss of mains power and the false tripping of feeders. Each of these problems impacts on protection systems in its own way. This study aims to review and investigate these problems via simulation demonstrations on one representative network to recommend solutions to practices.

Effect of Rayleigh-scattering distributed feedback on multiwavelength Raman fiber laser generation

We experimentally demonstrate a Raman fiber laser based on multiple point-action fiber Bragg grating (FBG) reflectors and distributed feedback via Rayleigh scattering in a ∼22 km long optical fiber. Twenty two lasing lines with spacing of ∼100 GHz (close to ITU grid) in C-band are generated at Watts power level. In contrast to the normal cavity with competition between laser lines, the random distributed feedback cavity exhibits highly stable multiwavelength generation with a power-equalized uniform distribution which is almost independent on power. The current set up showing the capability of generating Raman gain of about 100-nm wide giving the possibility of multiwavelength generation at different bands. © 2011 SPIE.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.