Free-space communication through turbulence: a comparison of plane-wave and orbital-angular-momentum encodings

Abstract

Free-space communication allows one to use spatial mode encoding, which is susceptible to the effects of diffraction and turbulence. Here, we discuss the optimum communication modes of a system while taking such effects into account. We construct a free-space communication system that encodes information onto the plane-wave (PW) modes of light. We study the performance of this system in the presence of atmospheric turbulence, and compare it with previous results for a system employing orbital-angular-momentum (OAM) encoding. We are able to show that the PW basis is the preferred basis set for communication through atmospheric turbulence for a system with a large Fresnel number product. This study has important implications for high-dimensional quantum key distribution systems.     

Effect of interface on mechanical properties and biodegradation of PCL HAp supramolecular nano-composites

This research explores the correlation between the structural properties of supramolecular biocomposites and their mechanical strength. Hybrid biocomposites composed of surface-modified hydroxyapatite nano-particles and supramolecular polycaprolactone (SP PCL), were prepared at different compositions, and their mechanical, thermal and viscoelastic properties as well as biodegradability, biocompatibility and cytotoxicity were evaluated in vitro. The results were compared with those for SP PCL/naked hydroxyapatite nano-composites. We show that surface modification of hydroxyapatite nanoparticles resulted in outstanding improvement of tensile strength and modulus up to 3.6 and 2.2-fold, respectively. At above 10 wt% HAp and 20 wt% HApUPy, heterogeneous nano-composites with inferior mechanical properties were obtained. Based on rheological (in steady shear mode) and small/wide angle X-ray scattering measurements, unusual improved mechanical properties were ascribed to the formation of supramolecular clusters around nanoparticles. In-vitro degradation of the supramolecular nano-composites was also studied to investigate the overall product biodegradation as well as toxicity of the degradation product(s).     

Probabilistic assessment of torsion in concrete beams externally strengthened with CFRP composites

This paper illustrates an analytical probabilistic study of concrete beams subjected to torsion that are strengthened with carbon fiber reinforced polymer (CFRP). Hii and Al-Mahaidi’s method is one of the best analytical models for evaluating the torsional capacity of CFRP strengthened reinforced concrete beams. The first-order reliability method is carried out to probabilistically assess the capacity of CFRP-strengthened beams. For this aim, the statistical characteristics of design variables and model errors have been considered, followed by the determination of the average reliability indexes of the strengthened beams. The effect of each design variable on the average reliability is also determined. The assessment shows that the Hii and Al-Mahaidi’s analytical model is unconservative. In order to correct the situation, a more relaxed set of resistance factors for use in a load and resistance factor design format are needed. These are then determined for two target reliability levels of $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5. It is found that factors of 0.9200 and 0.8225 are needed for target reliability levels, $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5, respectively. Values of 0.9 and 0.8 are suggested for use in real practice depending on the target reliability sought.     

Optimization of Short Load Forecasting in Electricity Market of Iran Using Artificial Neural Networks

Accurate short-term load forecasting (STLF) is one of the essential requirements for power systems. In this paper, two different seasonal artificial neural networks (ANNs) are designed and compared in terms of model complexity, robustness, and forecasting accuracy. Furthermore, the performance of ANN partitioning is evaluated. The first model is a daily forecasting model which is used for forecasting hourly load of the next day. The second model is composed of 24 sub-networks which are used for forecasting hourly load of the next day. In fact, the second model is partitioning of the first model. Time, temperature, and historical loads are taken as inputs for ANN models. The neural network models are based on feed-forward back propagation which are trained and tested using data from electricity market of Iran during 2003 to 2005. Results show a good correlation between actual data and ANN outcomes. Moreover, it is shown that the first designed model consisting of single ANN is more appropriate than the second model consisting of 24 distinct ANNs. Finally ANN results are compared to conventional regression models. It is observed that in most cases ANN models are superior to regression models in terms of mean absolute percentage error (MAPE).     

Investigation and Simulation of a Two-Channel Drop Filter with Tunable Double Optical Resonators

In this paper, a photonic crystal (PhC) two-channel drop filter based on two 2×2 & 2×3 ring resonators is proposed. This structure is made of Germanium rods in an air background at a two-dimensional (2D) square lattice. Refractive index is chosen in a way in which that device can be easily fabricated. The photonic crystal two-channel drop filter is composed using a horizontal waveguide and two ring resonators, which are placed symmetrically about the horizontal axis. These ring resonators operate as energy coupling and capture the electromagnetic energy propagated in bus waveguide at their resonance frequencies. The filter characteristics are calculated using 2D finite-difference time-domain (FDTD) and plane wave expansion (PWE) methods. We show a two-channel drop filter with two resonators, based on studied basic structures and achieving optimal modes for channel drop filters with one resonator. We have done this through choosing the proper radii for all rods of lattice, setting radii of coupling rods, lattice constant, and studying basic structures having different refractive indexes. Finally, we show 84 % and 100 % dropping efficiencies can be achieved at D and C ports in the communication window and 100 % in direct port. The size of this device is 14.56 μm (length)×11.96 μm (width). This small size makes it possible to use the device in multiplexer applications in future communication systems and in all-optical integrated circuits.     

Using Taguchi method to determine optimum process conditions for flue gas desulfurization through an amine scrubber

This study was done to determine the optimum process conditions for absorption of sulfur dioxide in a mixture of flue gases. Using a selective amine-based absorber; a high amount of SO₂ was absorbed in the scrubbing process. The process was designed to reduce the amount of sulfur dioxide. The pilot plant was designed and set up in the Research Center of Petroleum University of Technology, containing absorption and desorption stages. This paper reports an investigation of the effect and optimization of parameters that improve the efficiency of the whole process. The experiments were conducted under varying levels of desorption temperature, pH of the absorber solution, concentration of SO₂ inlet gas, and flow rate of the absorbing solution. Using Taguchi experimental design method, the optimum conditions were identified for the absorption process. An efficiency of more than 99 % could be obtained by varying the parameters in which all the released SO₂ gas was absorbed from the inlet flue gas; an achievement that is much favorable for industrial purposes.     

Fabrication of capped gold nanoparticles by using various amino acids

The production of gold nanoparticles (GNPs) by amino acid is one of the most attractive and interesting subjects in nanobiotechnology. In this study, amino acids have been utilised as a reducing agent and also an agent for capping GNPs. The GNPs were prepared using a reduction solution containing gold cations with optimum concentration of gold salt (5?mM), and also functionalised by glutamic acid, phenylalanine and tryptophan with optimum concentration of amino acids (25?mM). The optimum condition of gold solution and amino acids were achieved by ultraviolet–visible spectroscopy. The size of nanoparticles was obtained 5–20, 10–20 and 20–30?nm, respectively, by transmission electron microscopy and dynamic light scattering techniques. The results obtained from experimental and quantum calculations confirm that amino acids have strong bond while they have anion binding. Moreover, the free carboxylic groups of capped GNPs are one of the suitable and capable beads for binding biological agents. As a result, the medical applications of amino acids and proteins can be used as a practical method due to the strong interaction of peripheral amine groups with nanoparticles.     

Hybrid Fractal-Wavelet Method for Multi-Channel EEG Signal Compression

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.