Outage Constrained Design in NOMA-Based D2D Offloading Systems

Non-orthogonal multiple access (NOMA) is a new multiple access method that has been considered in 5G cellular communications in recent years, and can provide better throughput than traditional orthogonal multiple access (OMA) to save communication bandwidth. Device-to-device (D2D) communication, as a key technology of 5G, can reuse network resources to improve the spectrum utilization of the entire communication network. Combining NOMA technology with D2D is an effective solution to improve mobile edge computing (MEC) communication throughput and user access density. Considering the estimation error of channel, we investigate the power of the transmit nodes optimization problem of NOMA-based D2D networks under the rates outage probability (OP) constraints of all single users. Specifically, under the channel statistical error model, the total system transmit power is minimized with the rate OP constraint of a single device. Unfortunately, the problem presented is thorny and non-convex. After equivalent transformation of the rate OP constraints by the Bernstein inequality, an algorithm based on semi-definite relaxation (SDR) can efficiently solve this challenging non-convex problem. Numerical results show that the channel estimation error increases the power consumption of the system. We also compare NOMA with the OMA mode, and the numerical results show that the D2D offloading systems based on NOMA are superior to OMA.

Performance of Digital Drone Signage System Based on DUET

In this letter, we study a scenario based on degenerate unmixing estimation technique (DUET) that separates original signals from mixture of FHSS signals with two antennas. We have shown that the assumptions for separating mixed signals in DUET can be applied to drone based digital signage recognition signals and proposed the DUET-based separation scheme (DBSS) to classify the mixed recognition drone signals by extracting the delay and attenuation components of the mixture signal through the likelihood function and the short-term Fourier transform (STFT). In addition, we propose an iterative algorithm for signal separation with the conventional DUET scheme. Numerical results showed that the proposed algorithm is more separation-efficient compared to baseline schemes. DBSS can separate all signals within about 0.56 seconds when there are fewer than nine signage signals.

On wave propagation and free vibration of piezoelectric sandwich plates with perfect and porous functionally graded substrates

This paper aims to develop analytical solutions for wave propagation and free vibration of perfect and porous functionally graded (FG) plate structures integrated with piezoelectric layers. The effect of porosities, which occur in FG materials, is rarely reported in the literature of smart FG plates but included in the present modeling. The modified rule of mixture is therefore considered for variation of effective material properties within the FG substrate. Based on a four-variable higher-order theory, the electromechanical model of the system is established through the use of Hamilton’s principle, and Maxwell’s equation. This theory drops the need of any shear correction factor, and results in less governing equations compared to the conventional higher-order theories. Analytical solutions are applied to the obtained equations to extract the results for two investigations: (I) the plane wave propagation of infinite smart plates and (II) the free vibration of smart rectangular plates with different boundary conditions. After verifying the model, extensive numerical results are presented. Numerical results demonstrate that the wave characteristics of the system, including wave frequency and phase velocity along with the natural frequencies of its bounded counterpart, are highly influenced by the plate parameters such as power-law index, porosity, and piezoelectric characteristics.

Predicting the airborne microbial transmission via human breath particles using a gated recurrent units neural network

Purpose The purpose of this paper is to devise a tool based on computational fluid dynamics (CFD) and machine learning (ML), for the assessment of potential airborne microbial transmission in enclosed spaces. A gated recurrent units neural network (GRU-NN) is presented to learn and predict the behaviour of droplets expelled through breaths via particle tracking data sets. Design/methodology/approach A computational methodology is used for investigating how infectious particles that originated in one location are transported by air and spread throughout a room. High-fidelity prediction of indoor airflow is obtained by means of an in-house parallel CFD solver, which uses a one equation Spalart–Allmaras turbulence model. Several flow scenarios are considered by varying different ventilation conditions and source locations. The CFD model is used for computing the trajectories of the particles emitted by human breath. The numerical results are used for the ML training. Findings In this work, it is shown that the developed ML model, based on the GRU-NN, can accurately predict the airborne particle movement across an indoor environment for different vent operation conditions and source locations. The numerical results in this paper prove that the presented methodology is able to provide accurate predictions of the time evolution of particle distribution at different locations of the enclosed space. Originality/value This study paves the way for the development of efficient and reliable tools for predicting virus airborne movement under different ventilation conditions and different human positions within an indoor environment, potentially leading to the new design. A parametric study is carried out to evaluate the impact of system settings on time variation particles emitted by human breath within the space considered.

D3 Dihedral Logistic Map of Fractional Order

In this paper, the D3 dihedral logistic map of fractional order is introduced. The map presents a dihedral symmetry D3. It is numerically shown that the construction and interpretation of the bifurcation diagram versus the fractional order requires special attention. The system stability is determined and the problem of hidden attractors is analyzed. Furthermore, analytical and numerical results show that the chaotic attractor of integer order, with D3 symmetries, looses its symmetry in the fractional-order variant.

Fiber element modeling of circular double-skin concrete-filled stainless-carbon steel tubular columns under axial load and bending

Circular concrete-filled double-skin steel tubular (CFDST) columns with external stainless-steel are high-performance composite columns that have potential applications in civil construction including the construction of offshore structures, bridge piers, and transmission towers. Reflecting the limited research performed on investigating their mechanical performance, this study develops a computationally efficient fiber model to simulate the responses of short and slender beam-columns accounting for the influences of material and geometric nonlinearities. Accurate material laws of stainless steel, carbon steel, and confined concrete are implemented in the mathematical modeling scheme developed. A new solution algorithm based on the Regula-Falsi method is developed to maintain the equilibrium condition. The independent test results of short and slender CFDST beam-column are utilized to validate the accuracy of the theoretical solutions. The influences of various column parameters are studied on the load-axial strain [Formula: see text] curves, load-lateral deflection [Formula: see text] curves, column strength curves, and interaction curves of CFDST columns. Design formulas are suggested for designing short and beam-columns and validated against the numerical results. The computational model is found to be capable of simulating the responses of CFDST short and slender columns reasonably well. Parametric studies show that the consideration of the concrete confinement is important for the accuracy of the prediction of their mechanical responses. Furthermore, high-strength concrete can be utilized to enhance their load-carrying capacity particularly for short and intermediate slender beam-columns. The strengths of CFDST columns computed by the suggested design model are in good agreement with the test and numerical results.

Effect of quartz aperture covers on the fluid dynamics and thermal efficiency of falling particle receivers

Falling particle receivers are an emerging technology for use in concentrating solar power systems. In this work, quartz half-shells are investigated for use as full or partial aperture covers to reduce receiver thermal losses. A receiver subdomain and surrounding air are modeled using ANSYS® Fluent®. The model is used to simulate fluid dynamics and heat transfer for the following cases: (1) open aperture, (2), aperture fully covered by quartz half-shells, and (3) aperture partially covered by quartz half-shells. We compare the percentage of total incident solar power lost due to conduction through the receiver walls, advective losses through the aperture, and radiation exiting the aperture. Contrary to expected outcomes, results show that quartz aperture covers can increase radiative losses and result in modest to nonexistent reductions in advective losses. The increased radiative losses are driven by elevated quartz half-shell temperatures and have the potential to be mitigated by active cooling and/or material selection. Quartz half-shell total transmissivity was measured experimentally using a radiometer and the National Solar Thermal Test Facility heliostat field. Average measured total transmissivities are 0.97±0.01 and 0.94±0.02 for concave and convex side toward the heliostat field, respectively. Quartz half-shell aperture covers did not yield expected efficiency gains in numerical results due to increased radiative losses, but efficiency improvement in some numerical results and the performance of quartz half-shells subject to concentrated solar radiation suggest quartz half-shell aperture covers should be investigated further.

Molecular Dynamics Investigation on Thermal Conductivity and Photon Behaviors of Graphene With Sierpinski Carpet Fractal Defects

The thermal conductivity (TC) of graphene with Sierpinski carpet fractal (SCF) and regular carpet (RC) defects is numerically studied by the non-equilibrium molecular dynamics (NEMD) method. The influences of porosity, fractal levels, and types of defects on the TC of graphene are clarified, and the underlying mechanisms of phonon behaviors are uncovered. The numerical results indicate that the defects in graphene induce the atoms that have the heat transfer blockage effect, and thus, the TC of defective graphene decreases with increasing porosity. With the increase in fractal levels, more atoms have the heat transfer blockage effect, which induces the TC of graphene with SCF defects to sharply decrease. Moreover, compared with the graphene with RC defects, more atoms participate in the heat transfer blockage under the graphene with SCF defects, which leads to the lower TC of graphene with SCF defects.

Numerical Simulation of Cubic-Quartic Optical Solitons with Perturbed Fokas–Lenells Equation Using Improved Adomian Decomposition Algorithm

The current manuscript displays elegant numerical results for cubic-quartic optical solitons associated with the perturbed Fokas–Lenells equations. To do so, we devise a generalized iterative method for the model using the improved Adomian decomposition method (ADM) and further seek validation from certain well-known results in the literature. As proven, the proposed scheme is efficient and possess a high level of accuracy.

𝑯𝑵- Entropy: A New Measureof Information And Its Properties

Entropy measures the amount of uncertainty and dispersion of an unknown or random quantity, this concept introduced at first by Shannon (1948), it is important for studies in many areas. Like, information theory: entropy measures the amount of information in each message received, physics: entropy is the basic concept that measures the disorder of the thermodynamical system, and others. Then, in this paper, we introduce an alternative measure of entropy, called 𝐻𝑁- entropy, unlike Shannon entropy, this proposed measure of order α and β is more flexible than Shannon. Then, the cumulative residual 𝐻𝑁- entropy, cumulative 𝐻𝑁- entropy, and weighted version have been introduced. Finally, comparison between Shannon entropy and 𝐻𝑁- entropy and numerical results have been introduced.