Collaborative Adaptive Optical Wireless System in Realistic Indoor Environment

In this paper, we propose and evaluate a collaborative mobile optical wireless (OW) system that employs a collaborative adaptive beam clustering method (CABCM) in conjunction with an imaging receiver. Three cases involving two, three and five receivers are considered. A collaborative maximum ratio combining scheme is used to collaboratively distribute the transmit power among the diffusing spots. Our ultimate goal is to increase the received optical power and improve the signal-to-noise ratio (SNR) at each coexisting receiver when the system operates in a multiuser scenario under the constraints of background noise, multipath dispersion, mobility and shadowing typical in a real indoor environment. Our proposed system (collaborative adaptive beam clustering method) is evaluated at 30 Mbit/s to enable comparison with previous work, and is also assessed at higher bit rates: 2.5 Gbit/s and 5 Gbit/s. Simulation results show that the mobile CABCM system offers a significant performance improvement including a reduction in the background noise (BN) effect, a strong received power, reduction in delay spread, and improvement in the SNR over multiuser line strip multibeam system (LSMS). However, the performance degrades gradually with increase in the number of users

Collaborative Multibeam Transmitter and Imaging Receiver in Realistic Environment

In this paper, we propose a collaborative mobile optical wireless (OW) system that employs a collaborative adaptive beam clustering method (CABCM) in conjunction with an imaging receiver. Collaborative maximum ratio combining (MRCColl) scheme is used to collaboratively distribute the transmit power among diffusing spots. The main goal is to increase the received optical power and improve the signal-to-noise ratio (SNR) at each coexisting receiver when the system operates in a multiuser scenario under the constraints of background noise, multipath dispersion and mobility. Our proposed system (collaborative adaptive beam clustering method) is evaluated at 30 Mbit/s to enable comparison with previous work, and is also assessed at higher bit rates: 2.5 Gbit/s and 5 Gbit/s. Simulation results show that at a bit rate of 30 Mbit/s, a significant SNR improvement of 39 dB is achieved when a CABCM system replaces a multiuser line strip multibeam system (LSMS) at a 6 m transmitter-receiver horizontal separation. The results also show that the proposed system can achieve a 22 dB SNR when the system operates at 2.5 Gbit/s in a two-user scenario

Comparative performance of complex-valued B-spline and polynomial models applied to iterative frequency-domain decision feedback equalization of Hammerstein channels

Complex-valued (CV) B-spline neural network approach offers a highly effective means for identifying and inverting practical Hammerstein systems. Compared with its conventional CV polynomial-based counterpart, a CV B-spline neural network has superior performance in identifying and inverting CV Hammerstein systems, while imposing a similar complexity. This paper reviews the optimality of the CV B-spline neural network approach. Advantages of B-spline neural network approach as compared with the polynomial based modeling approach are extensively discussed, and the effectiveness of the CV neural network-based approach is demonstrated in a real-world application. More specifically, we evaluate the comparative performance of the CV B-spline and polynomial-based approaches for the nonlinear iterative frequency-domain decision feedback equalization (NIFDDFE) of single-carrier Hammerstein channels. Our results confirm the superior performance of the CV B-spline-based NIFDDFE over its CV polynomial-based counterpart

Fractional calculus model of GATA-switching for regulating the differentiation of a hematopoietic stem cell

This paper deals with the fractional order model for GATA-switching for regulating the differentiation of a hematopoietic stem cell. We give a detailed analysis for the asymptotic stability of the model. The Adams-Bashforth-Moulton algorithm has been used to solve and simulate the system of differential equations

Recent Advances on State Estimation for Power Grids with Unconventional Measurements

State estimation problem for power systems has long been a fundamental issue that demands a variety of methodologies depending on the system settings. With the recent introduction of advanced devices of phasor measurement units (PMUs) and dedicated communication networks, the infrastructure of power grids has been greatly improved. Coupled with the infrastructure improvements are three emerging issues for the state estimation problems, namely, the coexistence of both traditional and PMU measurements, the incomplete information resulting from delayed, asynchronous and missing measurements due to communication constraints, and the cyber-attacks on the communication channels. In this study, the authors aim to survey some recent advances on the state estimation methods which tackle the above three issues in power grids. Traditional state estimation methods applied in power grids are first introduced. Latest results on state estimation with mixed measurements and incomplete measurements are then discussed in great detail. In addition, the techniques developed to ensure the cyber-security of the state estimation schemes for power grids are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out

Geochemical composition of dust from Qatar peninsula

Atmospheric dust samples have been collected from different areas in Qatar and analyzed for major and trace element composition. This region of the Arabian Gulf represents an area largely affected by dust from natural and anthropogenic sources. Twenty one samples were collected during 2014 and 2015 from Al-Khor, Katara, Sealine, Al-Waab, and Qatar University by passive and active sampling techniques. Some bulk samples were collected during the massive megastorm that occurred in April 2015. Back trajectories were determined for each sample set using the NOAA HYSPLIT model over a 50 hour time interval. Samples were equally divided between northerly (n=12; northern Saudi Arabia, Kuwait or Iraq) and southerly (n=8; SE Saudi Arabia, United Arab Emirates and Oman) sources. One sample is expected to originate from westward, in Saudi Arabia. There is more variability noticed in source locations throughout the winter months (October to March), with more of them coming from the south (9 times) compared to summer months (April to September) for twice only. Dust samples were microwave-assisted, total acid digested (HF+HCl+HNO3) and oxidized with H2O2 before analyses were conducted by ICP-OES. Only 12 out of 23 elements (Al, Ca, Fe, K, Mg, Na, Ag, As, Ba, Be, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Sr, V, Zn, P) of the Qatari dust samples were enriched relative to Upper Continental Crust (UCC). Calcium was especially enriched to a level of 400% relative to UCC. About 33% of the total sample mass was CaCO3, reflecting the composition of surface rocks in the source areas. Of the elements typically associated with anthropogenic activity, Ag, Ni, and Zn were the most enriched relative to UCC, with enrichment factors of 182%, 233%, and 209%, respectively. Other metals like Pb and V were not significantly enriched, with enrichment factors not exceeding 25% and 3%, respectively. Major elements (Al, Mn and Fe) were depleted relative to UCC due to the strong enrichment of CaCO3, with enrichment factors of -58%, -35% and -5%, respectively. Samples with northern and southern origins were separated to investigate if the elemental composition could be used to identify source/origin. Only three elements were observed to have a statistical difference. Pb and Na were higher in the samples collected from the south while Cr was higher in those from the north. This study aims to investigate present-day geochemistry of dust particles and its effect on the marine environment of the Arabian Gulf. The geochemical composition of dust is essential component for correcting lithogenic input to water column suspended matter samples.qscienc

Robust filtering for a class of nonlinear stochastic systems with probability constraints

This paper is concerned with the probability-constrained filtering problem for a class of time-varying nonlinear stochastic systems with estimation error variance constraint. The stochastic nonlinearity considered is quite general that is capable of describing several well-studied stochastic nonlinear systems. The second-order statistics of the noise sequence are unknown but belong to certain known convex set. The purpose of this paper is to design a filter guaranteeing a minimized upper-bound on the estimation error variance. The existence condition for the desired filter is established, in terms of the feasibility of a set of difference Riccati-like equations, which can be solved forward in time. Then, under the probability constraints, a minimax estimation problem is proposed for determining the suboptimal filter structure that minimizes the worst-case performance on the estimation error variance with respect to the uncertain second-order statistics. Finally, a numerical example is presented to show the effectiveness and applicability of the proposed method

Mechanisms for reducing low back pain: a mediation analysis of a multifaceted intervention in workers in elderly care

Purpose A multifaceted workplace intervention consisting of participatory ergonomics, physical training, and cognitive–behavioural training (CBT) has shown effectiveness for reducing low back pain (LBP). However, the mechanisms of action underlying these intervention components are not well understood. Methods This was a mediation analysis of a cluster-randomised controlled trial of a multifaceted intervention in 420 workers in elderly care. Mediation analysis was carried out via structural equation modelling. Potential mediators investigated were: fear-avoidance beliefs, perceived muscle strength, use of assistive devices at work and perceived physical exertion at work. LBP outcomes assessed were: days with LBP, LBP intensity and days with bothersome LBP. Results There were no significant indirect effects of the intervention on LBP outcomes. There were significant effects of the intervention on both fear-avoidance measures [β = − 0.63, 95% CI (1.23, 0.03); β = − 1.03, 95% CI (− 1.70, − 0.34)] and the use of assistive devices [β = − 0.55, 95% CI (− 1.04, − 0.05)], but not on perceived muscle strength [β = − 0.18, 95% CI (− 0.50, 0.13)] or physical exertion [β = − 0.05, 95% CI (− 0.40, 0.31)]. The only potential mediator with a significant effect on LBP outcomes was physical exertion, which had a significant effect on LBP intensity [β = 0.14, 95% CI (0.04, 0.23)]. Conclusions A multifaceted intervention consisting of participatory ergonomics, physical training, and CBT was able to decrease fear-avoidance beliefs and increase use of assistive devices in the workplace. However, these changes did not explain the effect of any of the intervention components on days with LBP, LBP intensity and days with bothersome LBP