Transmission performance of adaptively modulated optical OFDM modems using subcarrier modulation over SMF IMDD links for access and metropolitan area networks.

Detailed investigations are undertaken, for the first time, of the transmission performance of recently proposed novel Adaptively Modulated Optical OFDM (AMOOFDM) modems using Subcarrier Modulation (AMOOFDM-SCM) in single-channel, SMF-based IMDD links without optical amplification and chromatic dispersion compensation. The cross-talk effect induced by beatings among subcarriers of various types is a crucial factor limiting the maximum achievable AMOOFDM-SCM performance. By applying single sideband modulation and/or spectral gapping to AMOOFDM-SCM, three AMOOFDM-SCM designs of varying complexity are proposed, which achieve >60Gb/s signal transmission over 20 km, 40 km and 60 km. Such performances are >1.5 times higher than those supported by conventional AMOOFDM modems.

A condition monitoring platform using COTS wireless sensor networks - Lessons and experience

Developments in Micro-Electro-Mechanical Systems (MEMS), wireless communication systems and ad-hoc networking have created new dimensions to improve asset management not only during the operational phase but throughout an asset's lifecycle based on using improved quality of information obtained with respect to two key aspects of an asset: its location and condition. In this paper, we present our experience as well as lessons learnt from building a prototype condition monitoring platform to demonstrate and to evaluate the use of COTS wireless sensor networks to develop a prototype condition monitoring platform with the aim of improving asset management by providing accurate and real-time information. © 2010 IEEE.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Phrase-based statistical language generation using graphical models and active learning

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents BAGEL, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that BAGEL can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data. © 2010 Association for Computational Linguistics.

Free-space optoelectronic switching cores with MPLS for SANs over WDM ring networks

With increasing demands on storage devices in the modern communication environment, the storage area network (SAN) has evolved to provide a direct connection allowing these storage devices to be accessed efficiently. To optimize the performance of a SAN, a three-stage hybrid electronic/optical switching node architecture based on the concept of a MPLS label switching mechanism, aimed at serving as a multi-protocol label switching (MPLS) ingress label edge router (LER) for a SAN-enabled application, has been designed. New shutter-based free-space multi-channel optical switching cores are employed as the core switch fabric to solve the packet contention and switching path conflict problems. The system-level node architecture design constraints are evaluated through self-similar traffic sourced from real gigabit Ethernet network traces and storage systems. The extension performance of a SAN over a proposed WDM ring network, aimed at serving as an MPLS-enabled transport network, is also presented and demonstrated. © 2012 OSA.

Distributed maximum likelihood for simultaneous self-localization and tracking in sensor networks

We show that the sensor self-localization problem can be cast as a static parameter estimation problem for Hidden Markov Models and we implement fully decentralized versions of the Recursive Maximum Likelihood and on-line Expectation-Maximization algorithms to localize the sensor network simultaneously with target tracking. For linear Gaussian models, our algorithms can be implemented exactly using a distributed version of the Kalman filter and a novel message passing algorithm. The latter allows each node to compute the local derivatives of the likelihood or the sufficient statistics needed for Expectation-Maximization. In the non-linear case, a solution based on local linearization in the spirit of the Extended Kalman Filter is proposed. In numerical examples we demonstrate that the developed algorithms are able to learn the localization parameters. © 2012 IEEE.

Polymer waveguide-based backplanes for board-level optical interconnects

Optical interconnects are increasingly considered for use in high-performance electronic systems. Multimode polymer waveguides are a promising technology for the formation of optical backplane as they enable cost-effective integration of optical links onto standard printed circuit boards. In this paper, two different types of polymer waveguide-based optical backplanes are presented. The first one implements a passive shuffle architecture enabling non-blocking on-board optical interconnection between different cards/modules, while the second one deploys a regenerative bus architecture allowing the interconnection of an arbitrary number of electrical cards over a common optical bus. The polymer materials and the multimode waveguide components used to form the optical backplanes are presented, while details of the interconnection architectures and design of the backplanes are described. Proof-of-principle demonstrators fabricated onto low-cost FR4 substrates, including a 10-card 1 Tb/s-capacity passive shuffle router and 4-channel 3-card polymeric bus modules, are reported and their optical performance characteristics are presented. Low-loss, low-crosstalk on-board interconnection is achieved and error-free (BER10 12) 10 Gb/s communication between different card/module interfaces is demonstrated in both polymeric backplane systems. © 2012 IEEE.

Large scale heterogeneous networks, the Davis-Wielandt shell, and graph separation

We consider a large scale network of interconnected heterogeneous dynamical components. Scalable stability conditions are derived that involve the input/output properties of individual subsystems and the interconnection matrix. The analysis is based on the Davis-Wielandt shell, a higher dimensional version of the numerical range with important convexity properties. This can be used to allow heterogeneity in the agent dynamics while relaxing normality and symmetry assumptions on the interconnection matrix. The results include small gain and passivity approaches as special cases, with the three dimensional shell shown to be inherently connected with corresponding graph separation arguments. © 2012 Society for Industrial and Applied Mathematics.

Discriminative spoken language understanding using word confusion networks

Current commercial dialogue systems typically use hand-crafted grammars for Spoken Language Understanding (SLU) operating on the top one or two hypotheses output by the speech recogniser. These systems are expensive to develop and they suffer from significant degradation in performance when faced with recognition errors. This paper presents a robust method for SLU based on features extracted from the full posterior distribution of recognition hypotheses encoded in the form of word confusion networks. Following [1], the system uses SVM classifiers operating on n-gram features, trained on unaligned input/output pairs. Performance is evaluated on both an off-line corpus and on-line in a live user trial. It is shown that a statistical discriminative approach to SLU operating on the full posterior ASR output distribution can substantially improve performance both in terms of accuracy and overall dialogue reward. Furthermore, additional gains can be obtained by incorporating features from the previous system output. © 2012 IEEE.

FEC-free 50 m 1.5 Gb/s plastic optical fibre link using CAP modulation for home networks

LED-based carrierless amplitude and phase modulation is investigated for a multi-gigabit plastic optical fibre link. An FPGA-based 1.5 Gbit/s error free transmission over 50 m standard SI-POF using CAP64 is achieved, providing 2.9 dB power margin without forward error correction. © 2012 OSA.

A polymer waveguide-based 40 Gb/s optical bus backplane for board-level optical interconnects

Optical interconnects are increasingly considered for use in high-performance electronic systems. Multimode polymer waveguides are a promising technology for the formation of optical backplanes as they enable cost-effective integration of optical links onto standard printed circuit boards. In this paper, we present a 40 Gb/s optical backplane demonstrator based on the use of polymer multimode waveguides and a regenerative shared bus architecture. The system allows bus extension by cascading multiple polymeric bus modules through 3R regenerator units enabling the connection of an arbitrary number of electrical cards onto the bus. The proof-ofprinciple demonstrator reported here is formed with low-cost, commercially-available active devices and electronic components mounted on conventional FR4 substrates and achieves error-free 4×10 Gb/s optical interconnection between any two card interfaces on the bus. © 2013 IEEE.

Modelling of free-space optoelectronic switching with MPLS for storage area networks (SANs)

Low-cost optical switches based on SLMs have conventionally been considered unsuitable for packet switching due to slow reconfiguration time. In this paper, we demonstrate that the constraint of SLM reconfiguration time in a hybrid three-stage electronic/optical switching node architecture can be compensated through the utilization of MPLS label switching mechanism to achieve the best performance for SAN applications. © 2012 SEE.

FEC-free 50 m 1.5 Gb/s plastic optical fibre link using CAP modulation for home networks

LED-based carrierless amplitude and phase modulation is investigated for a multi-gigabit plastic optical fibre link. An FPGA-based 1.5 Gbit/s error free transmission over 50 m standard SI-POF using CAP64 is achieved, providing 2.9 dB power margin without forward error correction. © 2012 Optical Society of America.

Characterization and deformation response of orthotropic fibre networks with auxetic out-of-plane behaviour

In the present paper, highly porous fibre networks made of 316L fibres, with different fibre volume fractions, are characterized in terms of network architecture, elastic constants and fracture energies. Elastic constants are measured using quasi-static mechanical and modal vibration testing, yielding local and globally averaged properties, respectively. Differences between quasi-static and dynamic elastic constants are attributed to through-thickness shear effects. Regardless of the method employed, networks show signs of material inhomogeneity at high fibre densities, in agreement with X-ray nanotomography results. Strong auxetic (or negative Poisson's ratio) behaviour is observed in the through-thickness direction, which is attributed to fibre kinking induced during processing. Measured fracture energies are compared with model predictions incorporating information about in-plane fibre orientation distribution, fibre volume fraction and single fibre work of fracture. Experimental values are broadly consistent with model predictions, based on the assumption that this energy is primarily associated with plastic deformation of individual fibres within a process zone of the same order as the inter-joint spacing. © 2013 Published by Elsevier Ltd. on behalf of Acta Materialia Inc. All rights reserved.

Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks

Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.