ADSL transceivers applying DSM and their nonstationary noise robustness

Dynamic spectrum management (DSM) comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL) networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.

Quantum computation using weak nonlinearities: Robustness against decoherence

We investigate decoherence effects in the recently suggested quantum-computation scheme using weak nonlinearities, strong probe coherent fields, detection, and feedforward methods. It is shown that in the weak-nonlinearity-based quantum gates, decoherence in nonlinear media can be made arbitrarily small simply by using arbitrarily strong probe fields, if photon-number-resolving detection is used. On the contrary, we find that homodyne detection with feedforward is not appropriate for this scheme because in this case decoherence rapidly increases as the probe field gets larger.

Robustness of mathematical models for biological systems

The robustness of mathematical models for biological systems is studied by sensitivity analysis and stochastic simulations. Using a neural network model with three genes as the test problem, we study robustness properties of synthesis and degradation processes. For single parameter robustness, sensitivity analysis techniques are applied for studying parameter variations and stochastic simulations are used for investigating the impact of external noise. Results of sensitivity analysis are consistent with those obtained by stochastic simulations. Stochastic models with external noise can be used for studying the robustness not only to external noise but also to parameter variations. For external noise we also use stochastic models to study the robustness of the function of each gene and that of the system.

Issues of robustness and high dimensionality in cluster analysis

Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena. While normal mixture models are often used to cluster data sets of continuous multivariate data, a more robust clustering can be obtained by considering the t mixture model-based approach. Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data where the number of observations n is very large relative to their dimension p. As the approach using the multivariate normal family of distributions is sensitive to outliers, it is more robust to adopt the multivariate t family for the component error and factor distributions. The computational aspects associated with robustness and high dimensionality in these approaches to cluster analysis are discussed and illustrated.

A robustness framework for monitoring real options under uncertainty

This paper presents a problem structuring methodology to assess real option decisions in the face of unpredictability. Based on principles of robustness analysis and scenario planning, we demonstrate how decision-aiding can facilitate participation in projects setting and achieve effective decision making through the use of real options reasoning. We argue that robustness heuristics developed in earlier studies can be practical proxies for real options performance, hence indicators of efficient flexible planning. The developed framework also highlights how to integrate real options solutions in firms’ strategic plans and operating actions. The use of the methodology in a location decision application is provided for illustration.

On the robustness of random Boolean formulae

Random Boolean formulae, generated by a growth process of noisy logical gates are analyzed using the generating functional methodology of statistical physics. We study the type of functions generated for different input distributions, their robustness for a given level of gate error and its dependence on the formulae depth and complexity and the gates used. Bounds on their performance, derived in the information theory literature for specific gates, are straightforwardly retrieved, generalized and identified as the corresponding typical-case phase transitions. Results for error-rates, function-depth and sensitivity of the generated functions are obtained for various gate-type and noise models. © 2010 IOP Publishing Ltd.

Chronic preoperative pain and psychological robustness predict acute postoperative pain outcomes after surgery for breast cancer

Background - Few epidemiological studies have prospectively investigated preoperative and surgical risk factors for acute postoperative pain after surgery for breast cancer. We investigated demographic, psychological, pain-related and surgical risk factors in women undergoing resectional surgery for breast cancer. Methods - Primary outcomes were pain severity, at rest (PAR) and movement-evoked pain (MEP), in the first postoperative week. Results - In 338 women undergoing surgery, those with chronic preoperative pain were three times more likely to report moderate to severe MEP after breast cancer surgery (OR 3.18, 95% CI 1.45–6.99). Increased psychological ‘robustness’, a composite variable representing positive affect and dispositional optimism, was associated with lower intensity acute postoperative PAR (OR 0.63, 95% CI 0.48–0.82) and MEP (OR 0.71, 95% CI 0.54–0.93). Sentinel lymph node biopsy (SLNB) and intraoperative nerve division were associated with reduced postoperative pain. No relationship was found between preoperative neuropathic pain and acute pain outcomes; altered sensations and numbness postoperatively were more common after axillary sample or clearance compared with SLNB. Conclusion - Chronic preoperative pain, axillary surgery and psychological robustness significantly predicted acute pain outcomes after surgery for breast cancer. Preoperative identification and targeted intervention of subgroups at risk could enhance the recovery trajectory in cancer survivors.

Robustness of 40 Gb/s ASK modulation formats in the practical system infrastructure

In this work, we analyzed by means of numerical and laboratory experiments the resilience of 40 Gb/s amplitude shift keying modulation formats to transmission impairments in standard single-mode fiber lines as well as to optical filtering introduced by the optical add/drop multiplexer cascade. Our study is a pre-requisite to assess the implementation of cost-effective 40 Gb/s modulation technology in next generation high bit-rate robust optical transport networks.

Robustness of the OOK modulation formats at 40 Gbit/s in the practical system infrastructure

We experimentally investigate the robustness of OOK modulation formats at 40 Gbit/s versus transmission impairments and optical filtering. This study is a pre-requisite for the implementation of robust transparent networks.

Ensuring efficiency and robustness in MANET

This paper introduces a joint load balancing and hotspot mitigation protocol for mobile ad-hoc network (MANET) termed by us as 'load_energy balance + hotspot mitigation protocol (LEB+HM)'. We argue that although ad-hoc wireless networks have limited network resources - bandwidth and power, prone to frequent link/node failures and have high security risk; existing ad hoc routing protocols do not put emphasis on maintaining robust link/node, efficient use of network resources and on maintaining the security of the network. Typical route selection metrics used by existing ad hoc routing protocols are shortest hop, shortest delay, and loop avoidance. These routing philosophy have the tendency to cause traffic concentration on certain regions or nodes, leading to heavy contention, congestion and resource exhaustion which in turn may result in increased end-to-end delay, packet loss and faster battery power depletion, degrading the overall performance of the network. Also in most existing on-demand ad hoc routing protocols intermediate nodes are allowed to send route reply RREP to source in response to a route request RREQ. In such situation a malicious node can send a false optimal route to the source so that data packets sent will be directed to or through it, and tamper with them as wish. It is therefore desirable to adopt routing schemes which can dynamically disperse traffic load, able to detect and remove any possible bottlenecks and provide some form of security to the network. In this paper we propose a combine adaptive load_energy balancing and hotspot mitigation scheme that aims at evenly distributing network traffic load and energy, mitigate against any possible occurrence of hotspot and provide some form of security to the network. This combine approach is expected to yield high reliability, availability and robustness, that best suits any dynamic and scalable ad hoc network environment. Dynamic source routing (DSR) was use as our underlying protocol for the implementation of our algorithm. Simulation comparison of our protocol to that of original DSR shows that our protocol has reduced node/link failure, even distribution of battery energy, and better network service efficiency.

Improved adaptivity and robustness in decentralised multi-camera networks

In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.

Multibody System Mechanics: Modelling, Stability, Control, and Robustness by V. A. Konoplev and A. Cheremensky

BOOK REVIEWS Multibody System Mechanics: Modelling, Stability, Control, and Ro- bustness, by V. A. Konoplev and A. Cheremensky, Mathematics and its Appli- cations Vol. 1, Union of Bulgarian Mathematicians, Sofia, 2001, XXII + 288 pp., $ 65.00, ISBN 954-8880-09-01

Robustness of 40 Gb/s ASK modulation formats in the practical system infrastructure

In this work, we analyzed by means of numerical and laboratory experiments the resilience of 40 Gb/s amplitude shift keying modulation formats to transmission impairments in standard single-mode fiber lines as well as to optical filtering introduced by the optical add/drop multiplexer cascade. Our study is a pre-requisite to assess the implementation of cost-effective 40 Gb/s modulation technology in next generation high bit-rate robust optical transport networks. © 2006 Optical Society of America.