Z-transform implementation of the perfectly matched layer for truncating FDTD domains

A simple algorithm for implementing the perfectly matched layer (PML) is presented for truncating finite difference time domain (FDTD) computational domains. The algorithm is based on incorporating the Z-transform method into the PML FDTD implementation. The main advantage of the algorithm is its simplicity as it allows direct FDTD implementation of Maxwell's equations in the PML region. In addition, the formulations are independent of the material properties of the FDTD computational domain. Numerical examples are included to demonstrate the effectiveness of these formulations.     

Electrolyte—solvent interaction in the dipolar aprotic solvent dimethyl sulphoxide at 25°C

Conductance measurements are reported for s-alkylisothiouronium bromide, iodide and picrate salts in the dipolar aprotic solvent DMSO at 25°C. The data were analysed by Fuoss's equation (1975–1980) for 1:1 electrolytes, from which the values of Λ₀, the Gurney's cosphere diameter R and K_A are obtained. The results are discussed in the light of the recorded values of the constants K_R and K_S and the free energy term G_s.     

Adiabatic couplers: design rules and optimization

Explicit analytic design rules are derived for both 3 dB and full adiabatic couplers. The design rules are in excellent agreement with numerical calculations using the beam propagation method (BPM). It is shown that the length scaling for 3 dB couplers compared to full couplers makes the former more difficult to design. The design for each case is optimized to obtain the upper limit of performance and a comparison is carried out between two different design geometries for both 3 dB and full adiabatic couplers     

Thickness-dependence of stoichiometry and microstructure characteristics in correlation with conductivity type of CdTe films

CdTe films were prepared by physical vapour deposition on a substrate at room temperature (RT) as well as on a cold (LT) one using low deposition rate. The thickness-dependence of stoichiometry revealed an abrupt decrease in the Cd/Te ratio as the thickness increases. Change of thickness did not affect the type of observed (111) crystallographic texture, only the degree of preferred orientation is enhanced as the film grows. The internal strain was negligible while the crystallite size increased rapidly at small thickness (up to 400 nm), and less thickness dependence was observed with further film growth. However, thickness dependence of lattice parameters showed a minimum and a maximum at approximately 300 nm in the case of RT and LT, respectively. The observed change in conductivity from n- to p-type and its vital correlation with the stoichiometry and structural characteristics were presented. Based on thickness dependence of stoichiometry and lattice parameters as well as the conductivity type, formation and annihilation of lattice defects were considered.     

Age-related response of male melon fliesDacus cucurbitae (Diptera: Tephritidae) to cue-lure

Laboratory-reared and wild adults of the melon fly,Dacus cucurbitae Coquillett, were tested for response to cue-lure at various ages. Virgin laboratory (4, 6, 8, 10, 12, and 14 days old) and wild (10, 12, 14, 16, 18, 20, and 22 days old) flies were released into outdoor field cages and trapped from 0800 until 1600 hr. Response of males to cue-lure increased with age and corresponded with sexual maturity for each strain. Females of both strains were relatively nonresponsive to cue-lure. Failure to eradicate in past male annihilation programs againstD. cucurbitae may be explained in part by the fact that only older males, which may have already mated with gravid females, respond to cue-lure.     

Design and implementation of a new tuned hybrid intelligent model to predict the uniaxial compressive strength of the rock using SFS-ANFIS

This study proposes a novel design to systematically optimize the parameters for the adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) algorithm. To affirm the efficiency of the proposed SFS-ANFIS model, the predicting results were compared with ANFIS and three hybrid methodologies based on ANFIS combined with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Accurate prediction of uniaxial compressive strength (UCS) is of great significance for all geotechnical projects such as tunnels and dams. Hence, this study proposes the use of SFS-ANFIS, GA-ANFIS, DE-ANFIS, PSO-ANFIS, and ANFIS models to predict UCS. In this regard, the fresh water tunnel of Pahang–Selangor located in Malaysia was considered and the requirement data samples were collected. Different statistical metrics such as coefficient of determination (R²) and mean absolute error were used to evaluate the models. Referring to the efficiency results of SFS-ANFIS, it can be found that the SFS-ANFIS (with the R² of 0.981) has higher ability than PSO-ANFIS, DE-ANFIS, GA-ANFIS, and ANFIS models in predicting the UCS.

     

Multi-indicator Active Queue Management Method

A considerable number of applications are running over IP networks. This increased the contention on the network resource, which ultimately results in congestion. Active queue management (AQM) aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance. AQM methods implement different techniques in accordance with congestion indicators, such as queue length and average queue length. The performance of the network is evaluated using delay, loss, and throughput. The gap between congestion indicators and network performance measurements leads to the decline in network performance. In this study, delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM. The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability, which is responsible for managing the router buffer. The experimental results, based on two sets of experiments, have shown that the proposed method outperformed the existing benchmark algorithms including RED, ERED and BLUE algorithms. For instance, in the first experiment, the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms. In addition, the proposed method outperformed the benchmark algorithms in terms of packet loss, packet dropping, and packet retransmission. Overall, the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.     

Customized trapping of magnetic particles

This paper presents an efficient technique for trapping of magnetic particles in confined spatial locations using customized designs of micro-coils (MCs). Large magnetic field gradients of up to 20 T/mm and large magnetic forces in the range of 10⁻⁸ Newton on magnetic particles with diameter of 1 μm have been achieved using MCs with several planar geometrical configurations. A large magnetic field gradient is generated and enhanced by two structural parameters: the small width and high aspect ratio of each single conductor and the ferromagnetic pillars positioned at high-flux density locations. This arrangement creates very steep magnetic potential wells, in particular at the vicinity of the pillars. The system allowed capturing of suspended magnetic particles as far as 1,000 μm from the center of the device. Magnetic particles/cells have been trapped and confined in single and in arrays of deep magnetic potential wells corresponding to the MCs configuration.     

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.