3D FDTD Implementation for Scattering of Electric Anisotropic Dispersive Medium Using Recursive Convolution Method

The finite-difference time-domain method based on recursive convoltion method (RC-FDTD) for the electric anisotropic dispersive medium is discussed in detail. To exemplify the availability of the three-dimensional RC-FDTD algorithm, the backscattering Radar-Cross-Section(RCS) of a non-magnetized plasma sphere is computed, and the numerical results are the same as the one of the Shift Operater-FDTD method, and show that the RC-FDTD method is correct and efficient. In addition, the co-polarized and cross-polarized backscattering time-domain of a magnetized plasma sphere are obtained by the RC-FDTD algorithm. The results show that when the external magnetic field is implemented, the cross-polarized component appear, evidently.     

A novel all-optical label processing based on multiple optical orthogonal codes sequences for optical packet switching networks

This paper proposes an all-optical label processing scheme that uses the multiple optical orthogonal codes sequences (MOOCS)-based optical label for optical packet switching (OPS) (MOOCS-OPS) networks. In this scheme, each MOOCS is a permutation or combination of the multiple optical orthogonal codes (MOOC) selected from the multiple-groups optical orthogonal codes (MGOOC). Following a comparison of different optical label processing (OLP) schemes, the principles of MOOCS-OPS network are given and analyzed. Firstly, theoretical analyses are used to prove that MOOCS is able to greatly enlarge the number of available optical labels when compared to the previous single optical orthogonal code (SOOC) for OPS (SOOC-OPS) network. Then, the key units of the MOOCS-based optical label packets, including optical packet generation, optical label erasing, optical label extraction and optical label rewriting etc., are given and studied. These results are used to verify that the proposed MOOCS-OPS scheme is feasible.     

Central limit theorem and weak law of large numbers with rates for martingales in Banach spaces

This paper is concerned with large-$\text{O}$ error estimates concerning convergence in distribution as well as norm convergence for Banach space-valued martingale difference sequences. Indeed, two general limit theorems equipped with rates of convergence for such difference sequences are established. Applications of these lead to the central limit theorem and the weak law of large numbers with rates for Banach space-valued martingales.     

T1 and T2 effects during radio-frequency pulses in spoiled gradient echo sequences

Finite pulse durations in diverse pulse schemes lead to the reduction of the magnitude of the magnetization vector due to T₁ and T₂ effects during the radio-frequency pulses. This paper presents an analysis of the steady state signal in the presence of relaxation effects during radio-frequency pulses in MRI spoiled gradient echo sequences. It is shown that minor attenuations of the magnetization vector can have dramatic consequences on the measured signal, and may thus entail a loss in SNR benefits at high static magnetic fields if a careful analysis is not performed. It is emphasized that it is the time-integrated magnetization vector trajectory that matters for these effects and not only the pulse duration. Some experimental results obtained on a phantom at 3 T verify this analysis.     

Traffic flow monitoring in software-defined network using modified recursive learning

The recursive network design used in this paper to monitor traffic flow ensures accurate anomaly identification. The suggested method enhances the effectiveness of cyber attacks in SDN. The suggested model achieves a remarkable attack detection performance in the case of distributed denial-of-service (DDoS) attacks by preventing network forwarding performance degradation. The suggested methodology is designed to teach users how to match traffic flows in ways that increase granularity while proactively protecting the SDN data plane from overload. The application of a learnt traffic flow matching control policy makes it possible to obtain the best traffic data for detecting abnormalities obtained during runtime, improving the performance of cyber-attack detection. The accuracy of the suggested model is superior to the MMOS, FMS, DATA, Q-DATA, and DEEP-MC by 19.23%, 16.25%, 47.61%, 16.25%, and 12.04%.     

Determination of the gas chromatographic elution sequences of the (+)- and (−)-enantiomers of stable atropisomeric PCBs on Chirasil-dex

Pure enantiomers of chiral (atropisomeric) polychlorinated biphenyls (PCBs) obtained by high-performance liquid chromatography were used to establish the gas chromatographic elution sequences of the (+)- and (−)-enantiomers of six PCB atropisomers on Chirasil-Dex. The elution order was found to be (−/+) for PCBs 84, 132, 136, and 176 and (+/−) for PCBs 135 and 174. The retention characteristics of all 19 tri- and tetra-ortho atropisomeric PCBs were also investigated. Nine of the atropisomers could be separated using this chiral selector. PCBs 95, 132, and 149 were completely resovled and PCBs 84, 91, 135, 136, 174, and 176 were partially separated (R = 0.7–0.9). All of the separated congeners are 2,3,6-substituted in at least one ring, and conversely – none of the congeners that lacks 2,3,6-substitution could be separated. Thus, chiral recognition and enantiomer separation seems to be strongly governed by 2,3,6-substitution.     

Improvement of the recursive projection method for linear iterative scheme stabilization based on an approximate eigenvalue problem

An algorithm for stabilizing linear iterative schemes is developed in this study. The recursive projection method is applied in order to stabilize divergent numerical algorithms. A criterion for selecting the divergent subspace of the iteration matrix with an approximate eigenvalue problem is introduced. The performance of the present algorithm is investigated in terms of storage requirements and CPU costs and is compared to the original Krylov criterion. Theoretical results on the divergent subspace selection accuracy are established. The method is then applied to the resolution of the linear advection–diffusion equation and to a sensitivity analysis for a turbulent transonic flow in the context of aerodynamic shape optimization. Numerical experiments demonstrate better robustness and faster convergence properties of the stabilization algorithm with the new criterion based on the approximate eigenvalue problem. This criterion requires only slight additional operations and memory which vanish in the limit of large linear systems.     

On a new class of multiplicative pseudo-random number generators

In the computing literature, there are few detailed analytical studies of the global statistical characteristics of a class of multiplicative pseudo-random number generators.We comment briefly on normal numbers and study analytically the approximately uniform discrete distribution or (j,)-normality in the sense of Besicovitch for complete periods of fractional parts {x _{0 1} ⁱ /p} on [0, 1] fori=0, 1,..., (p–1)p^–1–1, i.e. in current terminology, generators given byx _{n+1 1} x _n mod p wheren=0, 1,..., (p–1)p ^–1–1,p is any odd prime, (x ₀,p)=1, ₁ is a primitive root modp ², and 1 is any positive integer.We derive the expectationsE(X, ),E(X ², ),E(X _nX_n+k); the varianceV(X, ), and the serial correlation coefficient k. By means of Dedekind sums and some results of H. Rademacher, we investigate the asymptotic properties of k for various lagsk and integers 1 and give numerical illustrations. For the frequently used case =1, we find comparable results to estimates of Coveyou and Jansson as well as a mathematical demonstration of a so-called rule of thumb related to the choice of ₁ for small k.Due to the number of parameters in this class of generators, it may be possible to obtain increased control over the statistical behavior of these pseudo-random sequences both analytically as well as computationally.