Nonlinear and ROADM induced penalties in 28 Gbaud dynamic optical mesh networks employing electronic signal processing

We report the impact of cascaded reconfigurable optical add-drop multiplexer induced penalties on coherently-detected 28 Gbaud polarization multiplexed m-ary quadrature amplitude modulation (PM m-ary QAM) WDM channels. We investigate the interplay between different higher-order modulation channels and the effect of filter shapes and bandwidth of (de)multiplexers on the transmission performance, in a segment of pan-European optical network with a maximum optical path of 4,560 km (80km x 57 spans). We verify that if the link capacities are assigned assuming that digital back propagation is available, 25% of the network connections fail using electronic dispersion compensation alone. However, majority of such links can indeed be restored by employing single-channel digital back-propagation employing less than 15 steps for the whole link, facilitating practical application of DBP. We report that higher-order channels are most sensitive to nonlinear fiber impairments and filtering effects, however these formats are less prone to ROADM induced penalties due to the reduced maximum number of hops. Furthermore, it has been demonstrated that a minimum filter Gaussian order of 3 and bandwidth of 35 GHz enable negligible excess penalty for any modulation order.

Nonlinear penalties in long-haul optical networks employing dynamic transponders

We report for the first time, the impact of cross phase modulation in WDM optical transport networks employing dynamic 28 Gbaud PM-mQAM transponders (m = 4, 16, 64, 256). We demonstrate that if the order of QAM is adjusted to maximize the capacity of a given route, there may be a significant degradation in the transmission performance of existing traffic for a given dynamic network architecture. We further report that such degradations are correlated to the accumulated peak-to-average power ratio of the added traffic along a given path, and that managing this ratio through pre-distortion reduces the impact of adjusting the constellation size of neighboring channels. (C) 2011 Optical Society of America

Nonlinear penalties in dynamic optical networks employing autonomous transponders

We report for the first time on the limitations in the operational power range of network traffic in the presence of heterogeneous 28-Gbaud polarization-multiplexed quadrature amplitude modulation (PM-mQAM) channels in a nine-channel dynamic optical mesh network. In particular, we demonstrate that transponders which autonomously select a modulation order and launch power to optimize their own performance will have a severe impact on copropagating network traffic. Our results also suggest that altruistic transponder operation may offer even lower penalties than fixed launch power operation.

Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Numerical analysis of artificial neural network and volterra-based nonlinear equalizers for coherent optical OFDM

One major drawback of coherent optical orthogonal frequency-division multiplexing (CO-OFDM) that hitherto remains unsolved is its vulnerability to nonlinear fiber effects due to its high peak-to-average power ratio. Several digital signal processing techniques have been investigated for the compensation of fiber nonlinearities, e.g., digital back-propagation, nonlinear pre- and post-compensation and nonlinear equalizers (NLEs) based on the inverse Volterra-series transfer function (IVSTF). Alternatively, nonlinearities can be mitigated using nonlinear decision classifiers such as artificial neural networks (ANNs) based on a multilayer perceptron. In this paper, ANN-NLE is presented for a 16QAM CO-OFDM system. The capability of the proposed approach to compensate the fiber nonlinearities is numerically demonstrated for up to 100-Gb/s and over 1000km and compared to the benchmark IVSTF-NLE. Results show that in terms of Q-factor, for 100-Gb/s at 1000km of transmission, ANN-NLE outperforms linear equalization and IVSTF-NLE by 3.2dB and 1dB, respectively.

Seasonal dynamic pattern analysis in service of climate change research. A methodical case-study - monitoring and simulation based on an aquatic insect community

Our aim was to approach an important and well-investigable phenomenon – connected to a relatively simple but real field situation – in such a way, that the results of field observations could be directly comparable with the predictions of a simulation model-system which uses a simple mathematical apparatus and to simultaneously gain such a hypothesis-system, which creates the theoretical opportunity for a later experimental series of studies. As a phenomenon of the study, we chose the seasonal coenological changes of aquatic and semiaquatic Heteroptera community. Based on the observed data, we developed such an ecological model-system, which is suitable for generating realistic patterns highly resembling to the observed temporal patterns, and by the help of which predictions can be given to alternative situations of climatic circumstances not experienced before (e.g. climate changes), and furthermore; which can simulate experimental circumstances. The stable coenological state-plane, which was constructed based on the principle of indirect ordination is suitable for unified handling of data series of monitoring and simulation, and also fits for their comparison. On the state-plane, such deviations of empirical and model-generated data can be observed and analysed, which could otherwise remain hidden.

Nonlinear dynamics and chaos simulation system analysis for improved design

Small errors proved catastrophic. Our purpose to remark that a very small cause which escapes our notice determined a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. Small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. When dealing with any kind of electrical device specification, it is important to note that there exists a pair of test conditions that define a test: the forcing function and the limit. Forcing functions define the external operating constraints placed upon the device tested. The actual test defines how well the device responds to these constraints. Forcing inputs to threshold for example, represents the most difficult testing because this put those inputs as close as possible to the actual switching critical points and guarantees that the device will meet the Input-Output specifications. ^ Prediction becomes impossible by classical analytical analysis bounded by Newton and Euclides. We have found that non linear dynamics characteristics is the natural state of being in all circuits and devices. Opportunities exist for effective error detection in a nonlinear dynamics and chaos environment. ^ Nowadays there are a set of linear limits established around every aspect of a digital or analog circuits out of which devices are consider bad after failing the test. Deterministic chaos circuit is a fact not a possibility as it has been revived by our Ph.D. research. In practice for linear standard informational methodologies, this chaotic data product is usually undesirable and we are educated to be interested in obtaining a more regular stream of output data. ^ This Ph.D. research explored the possibilities of taking the foundation of a very well known simulation and modeling methodology, introducing nonlinear dynamics and chaos precepts, to produce a new error detector instrument able to put together streams of data scattered in space and time. Therefore, mastering deterministic chaos and changing the bad reputation of chaotic data as a potential risk for practical system status determination. ^

Dynamic safety analysis of managed pressure drilling operations

The exploration and development of oil and gas reserves located in harsh offshore environments are characterized with high risk. Some of these reserves would be uneconomical if produced using conventional drilling technology due to increased drilling problems and prolonged non-productive time. Seeking new ways to reduce drilling cost and minimize risks has led to the development of Managed Pressure Drilling techniques. Managed pressure drilling methods address the drawbacks of conventional overbalanced and underbalanced drilling techniques. As managed pressure drilling techniques are evolving, there are many unanswered questions related to safety and operating pressure regimes. Quantitative risk assessment techniques are often used to answer these questions. Quantitative risk assessment is conducted for the various stages of drilling operations – drilling ahead, tripping operation, casing and cementing. A diagnostic model for analyzing the rotating control device, the main component of managed pressure drilling techniques, is also studied. The logic concept of Noisy-OR is explored to capture the unique relationship between casing and cementing operations in leading to well integrity failure as well as its usage to model the critical components of constant bottom-hole pressure drilling technique of managed pressure drilling during tripping operation. Relevant safety functions and inherent safety principles are utilized to improve well integrity operations. Loss function modelling approach to enable dynamic consequence analysis is adopted to study blowout risk for real-time decision making. The aggregation of the blowout loss categories, comprising: production, asset, human health, environmental response and reputation losses leads to risk estimation using dynamically determined probability of occurrence. Lastly, various sub-models developed for the stages/sub-operations of drilling operations and the consequence modelling approach are integrated for a holistic risk analysis of drilling operations.

Characterization of dynamic speckle sequences using principal component analysis and image descriptors

Speckle is being used as a characterization tool for the analysis of the dynamic of slow varying phenomena occurring in biological and industrial samples. The retrieved data takes the form of a sequence of speckle images. The analysis of these images should reveal the inner dynamic of the biological or physical process taking place in the sample. Very recently, it has been shown that principal component analysis is able to split the original data set in a collection of classes. These classes can be related with the dynamic of the observed phenomena. At the same time, statistical descriptors of biospeckle images have been used to retrieve information on the characteristics of the sample. These statistical descriptors can be calculated in almost real time and provide a fast monitoring of the sample. On the other hand, principal component analysis requires longer computation time but the results contain more information related with spatial-temporal pattern that can be identified with physical process. This contribution merges both descriptions and uses principal component analysis as a pre-processing tool to obtain a collection of filtered images where a simpler statistical descriptor can be calculated. The method has been applied to slow-varying biological and industrial processes

Bifurcation and dynamic response analysis of a rotating blade excited by upstream vortices

Acknowledgements The authors acknowledge the projects supported by the National Basic Research Program of China (973 Project)(No. 2015CB057405) and the National Natural Science Foundation of China (No. 11372082) and the State Scholarship Fund of CSC. DW thanks for the hospitality of the University of Aberdeen.

Dynamic method of stiffness identification in impacting systems for percussive drilling applications

Peer reviewed

Outer rotor mechanical and dynamic performance analysis for high-speed machine

Due to high-speed rotation, the problems about rotor mechanics and dynamics for outer rotor high-speed machine are more serious than conventional ones, in view of above problems the mechanical and dynamics analysis for an outer rotor high-speed permanent magnet claw pole motor are carried out. The rotor stress analytical calculation model was derived, then the stress distribution is calculated by finite element method also, which is coincided with that calculated by analytical model. In addition, the stress distribution of outer rotor yoke and PMs considering centrifugal force and temperature effect has been calculated, some influence factors on rotor stress distribution have been analyzed such as pole-arc coefficient and speed. The rotor natural frequency and critical speed were calculated by vibration mode analysis, and its dynamics characteristics influenced by gyroscope effect were analyzed based on Campbell diagram. Based on the analysis results above an outer rotor permanent magnet high-speed claw pole motor is design and verified.

When static meets dynamic: Comparing cone-beam computed tomography and acoustic reflection for upper airway analysis

INTRODUCTION: Upper airway measurement can be important for the diagnosis of breathing disorders. Acoustic reflection (AR) is an accepted tool for studying the airway. Our objective was to investigate the differences between cone-beam computed tomography (CBCT) and AR in calculating airway volumes and areas. METHODS: Subjects with prescribed CBCT images as part of their records were also asked to have AR performed. A total of 59 subjects (mean age, 15 ± 3.8 years) had their upper airway (5 areas) measured from CBCT images, acoustic rhinometry, and acoustic pharyngometry. Volumes and minimal cross-sectional areas were extracted and compared with software. RESULTS: Intraclass correlation on 20 randomly selected subjects, remeasured 2 weeks apart, showed high reliability (r >0.77). Means of total nasal volume were significantly different between the 2 methods (P = 0.035), but anterior nasal volume and minimal cross-sectional area showed no differences (P = 0.532 and P = 0.066, respectively). Pharyngeal volume showed significant differences (P = 0.01) with high correlation (r = 0.755), whereas pharyngeal minimal cross-sectional area showed no differences (P = 0.109). The pharyngeal volume difference may not be considered clinically significant, since it is 758 mm3 for measurements showing means of 11,000 ± 4000 mm3. CONCLUSIONS: CBCT is an accurate method for measuring anterior nasal volume, nasal minimal cross-sectional area, pharyngeal volume, and pharyngeal minimal cross-sectional area.