Dimensioning BCH codes for coherent DQPSK systems with laser phase noise and cycle slips

Forward error correction (FEC) plays a vital role in coherent optical systems employing multi-level modulation. However, much of coding theory assumes that additive white Gaussian noise (AWGN) is dominant, whereas coherent optical systems have significant phase noise (PN) in addition to AWGN. This changes the error statistics and impacts FEC performance. In this paper, we propose a novel semianalytical method for dimensioning binary Bose-Chaudhuri-Hocquenghem (BCH) codes for systems with PN. Our method involves extracting statistics from pre-FEC bit error rate (BER) simulations. We use these statistics to parameterize a bivariate binomial model that describes the distribution of bit errors. In this way, we relate pre-FEC statistics to post-FEC BER and BCH codes. Our method is applicable to pre-FEC BER around 10-3 and any post-FEC BER. Using numerical simulations, we evaluate the accuracy of our approach for a target post-FEC BER of 10-5. Codes dimensioned with our bivariate binomial model meet the target within 0.2-dB signal-to-noise ratio.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

Duality in multi-channel Luttinger Liquid with local scatterer

We have devised a general scheme that reveals multiple duality relations valid for all multi-channel Luttinger Liquids. The relations are universal and should be used for establishing phase diagrams and searching for new non-trivial phases in low-dimensional strongly correlated systems. The technique developed provides universal correspondence between scaling dimensions of local perturbations in different phases. These multiple relations between scaling dimensions lead to a connection between different inter-phase boundaries on the phase diagram. The dualities, in particular, constrain phase diagram and allow predictions of emergence and observation of new phases without explicit model-dependent calculations. As an example, we demonstrate the impossibility of non-trivial phase existence for fermions coupled to phonons in one dimension. © 2013 EPLA.

Analysis and modelling of muscles motion during whole body vibration

The aim of the study is to characterize the local muscles motion in individuals undergoing whole body mechanical stimulation. In this study we aim also to evaluate how subject positioning modifies vibration dumping, altering local mechanical stimulus. Vibrations were delivered to subjects by the use of a vibrating platform, while stimulation frequency was increased linearly from 15 to 60Hz. Two different subject postures were here analysed. Platform and muscles motion were monitored using tiny MEMS accelerometers; a contra lateral analysis was also presented. Muscle motion analysis revealed typical displacement trajectories: motion components were found not to be purely sinusoidal neither in phase to each other. Results also revealed a mechanical resonant-like behaviour at some muscles, similar to a second-order system response. Resonance frequencies and dumping factors depended on subject and his positioning. Proper mechanical stimulation can maximize muscle spindle solicitation, which may produce a more effective muscle activation. © 2010 M. Cesarelli et al.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

A methodological evaluation and predictive in silico investigation into the multi-functionality of arginine in directly compressed tablets

The acceleration of solid dosage form product development can be facilitated by the inclusion of excipients that exhibit poly-/multi-functionality with reduction of the time invested in multiple excipient optimisations. Because active pharmaceutical ingredients (APIs) and tablet excipients present diverse densification behaviours upon compaction, the involvement of these different powders during compaction makes the compaction process very complicated. The aim of this study was to assess the macrometric characteristics and distribution of surface charges of two powders: indomethacin (IND) and arginine (ARG); and evaluate their impact on the densification properties of the two powders. Response surface modelling (RSM) was employed to predict the effect of two independent variables; Compression pressure (F) and ARG percentage (R) in binary mixtures on the properties of resultant tablets. The study looked at three responses namely; porosity (P), tensile strength (S) and disintegration time (T). Micrometric studies showed that IND had a higher charge density (net charge to mass ratio) when compared to ARG; nonetheless, ARG demonstrated good compaction properties with high plasticity (Y=28.01MPa). Therefore, ARG as filler to IND tablets was associated with better mechanical properties of the tablets (tablet tensile strength (σ) increased from 0.2±0.05N/mm2 to 2.85±0.36N/mm2 upon adding ARG at molar ratio of 8:1 to IND). Moreover, tablets' disintegration time was shortened to reach few seconds in some of the formulations. RSM revealed tablet porosity to be affected by both compression pressure and ARG ratio for IND/ARG physical mixtures (PMs). Conversely, the tensile strength (σ) and disintegration time (T) for the PMs were influenced by the compression pressure, ARG ratio and their interactive term (FR); and a strong correlation was observed between the experimental results and the predicted data for tablet porosity. This work provides clear evidence of the multi-functionality of ARG as filler, binder and disintegrant for directly compressed tablets.

A simulation conceptual modelling procedure for SCM applications

Purpose – The purpose of this paper is to outline a seven-phase simulation conceptual modelling procedure that incorporates existing practice and embeds a process reference model (i.e. SCOR). Design/methodology/approach – An extensive review of the simulation and SCM literature identifies a set of requirements for a domain-specific conceptual modelling procedure. The associated design issues for each requirement are discussed and the utility of SCOR in the process of conceptual modelling is demonstrated using two development cases. Ten key concepts are synthesised and aligned to a general process for conceptual modelling. Further work is outlined to detail, refine and test the procedure with different process reference models in different industrial contexts. Findings - Simulation conceptual modelling is often regarded as the most important yet least understood aspect of a simulation project (Robinson, 2008a). Even today, there has been little research development into guidelines to aid in the creation of a conceptual model. Design issues are discussed for building an ‘effective’ conceptual model and the domain-specific requirements for modelling supply chains are addressed. The ten key concepts are incorporated to aid in describing the supply chain problem (i.e. components and relationships that need to be included in the model), model content (i.e. rules for determining the simplest model boundary and level of detail to implement the model) and model validation. Originality/value – Paper addresses Robinson (2008a) call for research in defining and developing new approaches for conceptual modelling and Manuj et al., (2009) discussion on improving the rigour of simulation studies in SCM. It is expected that more detailed guidelines will yield benefits to both expert (i.e. avert typical modelling failures) and novice modellers (i.e. guided practice; less reliance on hopeful intuition)

Multi-threaded parallel simulation of non-local non-linear problems in ultrashort laser pulse propagation in the presence of plasma

We describe a parallel multi-threaded approach for high performance modelling of wide class of phenomena in ultrafast nonlinear optics. Specific implementation has been performed using the highly parallel capabilities of a programmable graphics processor. © 2011 SPIE.

Winding-centre-tapped switched reluctance motor drive for multi-source charging in electric vehicle applications

Switched reluctance motors (SRMs) can provide an attractive traction drive for electric vehicle applications. To lower the investment in the off-board charging station facilities, a multi-functional switched reluctance motor topology is proposed on the basis of the traditional asymmetrical half-bridge converter. The SRM phase windings are employed as input filter inductors and centre-tapped windings are also developed to form symmetrical inductors for three-phase grid supply. Owing to the varying rotor position, phase inductors are unequal between one another. A hysteresis control scheme is therefore developed for grid-connection operation. In addition to AC supplies, the proposed topology can also supports the DC-source charging. A new current sharing strategy is employed to diminish the influence of the unequal winding inductances. The simulation and experimental tests are carried out to verify the proposed topology and control methods. Since this work eliminates the need for building charging station infrastructure, its potential economic impact on the automotive market can be significant.

Cooperative and adaptive medium access control in multi-hop wireless networks

Due to low cost and easy deployment, multi-hop wireless networks become a very attractive communication paradigm. However, IEEE 802.11 medium access control (MAC) protocol widely used in wireless LANs was not designed for multi-hop wireless networks. Although it can support some kinds of ad hoc network architecture, it does not function efficiently in those wireless networks with multi-hop connectivity. Therefore, our research is focused on studying the medium access control in multi-hop wireless networks. The objective is to design practical MAC layer protocols for supporting multihop wireless networks. Particularly, we try to prolong the network lifetime without degrading performances with small battery-powered devices and improve the system throughput with poor quality channels. ^ In this dissertation, we design two MAC protocols. The first one is aimed at minimizing energy-consumption without deteriorating communication activities, which provides energy efficiency, latency guarantee, adaptability and scalability in one type of multi-hop wireless networks (i.e. wireless sensor network). Methodologically, inspired by the phase transition phenomena in distributed networks, we define the wake-up probability, which maintained by each node. By using this probability, we can control the number of wireless connectivity within a local area. More specifically, we can adaptively adjust the wake-up probability based on the local network conditions to reduce energy consumption without increasing transmission latency. The second one is a cooperative MAC layer protocol for multi-hop wireless networks, which leverages multi-rate capability by cooperative transmission among multiple neighboring nodes. Moreover, for bidirectional traffic, the network throughput can be further increased by using the network coding technique. It is a very helpful complement for current rate-adaptive MAC protocols under the poor channel conditions of direct link. Finally, we give an analytical model to analyze impacts of cooperative node on the system throughput. ^

Plasma and cold sprayed aluminum carbon nanotube composites: Quantification of nanotube distribution and multi-scale mechanical properties

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si prealloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al 4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)

Interferometric synthetic aperture radar (InSAR) techniques can successfully detect phase variations related to the water level changes in wetlands and produce spatially detailed high-resolution maps of water level changes. Despite the vast details, the usefulness of the wetland InSAR observations is rather limited, because hydrologists and water resources managers need information on absolute water level values and not on relative water level changes. We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water level time series using radar interferograms acquired successively over wetlands. The method uses stage (water level) observation for calibrating the relative InSAR observations and tying them to the stage's vertical datum. We tested the STBAS technique with two-year long Radarsat-1 data acquired during 2006–2008 over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The InSAR-derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 m pixel resolution) of absolute water levels. We evaluate the quality of the STBAS technique using a root mean square error (RMSE) criterion of the difference between InSAR observations and stage measurements. The average RMSE is 6.6 cm, which provides an uncertainty estimation of the STBAS technique to monitor absolute water levels. About half of the uncertainties are attributed to the accuracy of the InSAR technique to detect relative water levels. The other half reflects uncertainties derived from tying the relative levels to the stage stations' datum.

Plasma And Cold Sprayed Aluminum Carbon Nanotube Composites: Quantification Of Nanotube Distribution And Multi-Scale Mechanical Properties

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si pre-alloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

Multi-media filtration for removal of petroleum contamination

A pilot scale multi-media filtration system was used to evaluate the effectiveness of filtration in removing petroleum hydrocarbons from a source water contaminated with diesel fuel. Source water was artificially prepared by mixing bentonite clay and tap water to produce a turbidity range of 10-15 NTU. Diesel fuel concentrations of 150 ppm or 750 ppm were used to contaminate the source water. The coagulants used included Cat Floc K-10 and Cat Floc T-2. The experimental phase was conducted under direct filtration conditions at constant head and constant rate filtration at 8.0 gpm. Filtration experiments were run until the filter reached its clogging point as noted by a measured peak pressure loss of 10 psi. The experimental variables include type of coagulant, oil concentration and source water. Filtration results were evaluated based on turbidity removal and petroleum hydrocarbon (PHC) removal efficiency as measured by gas chromatography. Experiments indicated that clogging was controlled by the clay loading on the filter and that inadequate destabilization of the contaminated water by the coagulant limited the PHC removal. ^