A hybrid Laplace transform/finite difference boundary element method for diffusion problems

The solution process for diffusion problems usually involves the time development separately from the space solution. A finite difference algorithm in time requires a sequential time development in which all previous values must be determined prior to the current value. The Stehfest Laplace transform algorithm, however, allows time solutions without the knowledge of prior values. It is of interest to be able to develop a time-domain decomposition suitable for implementation in a parallel environment. One such possibility is to use the Laplace transform to develop coarse-grained solutions which act as the initial values for a set of fine-grained solutions. The independence of the Laplace transform solutions means that we do indeed have a time-domain decomposition process. Any suitable time solver can be used for the fine-grained solution. To illustrate the technique we shall use an Euler solver in time together with the dual reciprocity boundary element method for the space solution

Solving the advection-dispersion equation using the discrete puff particle method

A flexible, mass-conservative numerical technique for solving the advection-dispersion equation for miscible contaminant transport is presented. The method combines features of puff transport models from air pollution studies with features from the random walk particle method used in water resources studies, providing a deterministic time-marching algorithm which is independent of the grid Peclet number and scales from one to higher dimensions simply. The concentration field is discretised into a number of particles, each of which is treated as a point release which advects and disperses over the time interval. The dispersed puff is itself discretised into a spatial distribution of particles whose masses can be pre-calculated. Concentration within the simulation domain is then calculated from the mass distribution as an average over some small volume. Comparison with analytical solutions for a one-dimensional fixed-duration concentration pulse and for two-dimensional transport in an axisymmetric flow field indicate that the algorithm performs well. For a given level of accuracy the new method has lower computation times than the random walk particle method.

A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

A Low Complexity Video Watermarking in H.264 Compressed Domain

In this paper, a new blind and readable H.264 compressed domain watermarking scheme is proposed in which the embedding/extracting is performed using the syntactic elements of the compressed bit stream. As a result, it is not necessary to fully decode a compressed video stream both in the embedding and extracting processes. The method also presents an inexpensive spatiotemporal analysis that selects the appropriate submacroblocks for embedding, increasing watermark robustness while reducing its impact on visual quality. Meanwhile, the proposed method prevents bit-rate increase and restricts it within an acceptable limit by selecting appropriate quantized residuals for watermark insertion. Regarding watermarking demands such as imperceptibility, bit-rate control, and appropriate level of security, a priority matrix is defined which can be adjusted based on the application requirements. The resulted flexibility expands the usability of the proposed method.

SVD-Based Universal Spatial Domain Image Steganalysis

This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain steganographic methods. The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs content independency provided by a Wiener filtering process. Experimental results show that the novel method has superior performance when compared with its counterparts in terms of spatial domain steganography. Experiments also demonstrate the reasonable ability of the method to detect discrete cosine transform-based steganography as well as the perturbation quantization method.

Low-complexity iterative method of equalization for single carrier with cyclic prefix in doubly selective channels

Orthogonal frequency division multiplexing (OFDM) requires an expensive linear amplifier at the transmitter due to its high peak-to-average power ratio (PAPR). Single carrier with cyclic prefix (SC-CP) is a closely related transmission scheme that possesses most of the benefits of OFDM but does not have the PAPR problem. Although in a multipath environment, SC-CP is very robust to frequency-selective fading, it is sensitive to the time-selective fading characteristics of the wireless channel that disturbs the orthogonality of the channel matrix (CM) and increases the computational complexity of the receiver. In this paper, we propose a time-domain low-complexity iterative algorithm to compensate for the effects of time selectivity of the channel that exploits the sparsity present in the channel convolution matrix. Simulation results show the superior performance of the proposed algorithm over the standard linear minimum mean-square error (L-MMSE) equalizer for SC-CP.

Finite difference time domain modeling of phase grating diffusion

In this paper, a method for modeling diffusion caused by non-smooth boundary surfaces in simulations of room acoustics using finite difference time domain (FDTD) technique is investigated. The proposed approach adopts the well-known theory of phase grating diffusers to efficiently model sound scattering from rough surfaces. The variation of diffuser well-depths is attained by nesting allpass filters within the reflection filters from which the digital impedance filters used in the boundary implementation are obtained. The presented technique is appropriate for modeling diffusion at high frequencies caused by small surface roughness and generally diffusers that have narrow wells and infinitely thin separators. The diffusion coefficient was measured with numerical experiments for a range of fractional Brownian diffusers.

Prediction of Transonic LCOs using an Aeroelastic Harmonic Balance Method

This work proposes a novel approach to compute transonic Lim
it Cycle Oscillations using high fidelity analysis. CFD based Harmonic Balance methods have proven to be efficient tools to predict periodic phenomena. This paper’s contribution is to present a new methodology to determine the unknown frequency of oscillations, enabling HB methods to accurately capture Limit Cycle Oscillations (LCOs); this is achieved by defining a frequency updating procedure based on a coupled CFD/CSD Harmonic Balance formulation to find the LCO condition. A pitch/plunge aerofoil and delta wing aerodynamic and respective linear structural models are used to validate the new method against conventional time-domain simulations. Results show consistent agreement between the proposed and time-marching methods for both LCO amplitude and frequency, while producing at least one order of magnitude reduction in computational time.

Prediction of limit cycle oscillations under uncertainty using a Harmonic Balance method

The Harmonic Balance method is an attractive solution for computing periodic responses and can be an alternative to time domain methods, at a reduced computational cost. The current paper investigates using a Harmonic Balance method for simulating limit cycle oscillations under uncertainty. The Harmonic Balance method is used in conjunction with a non-intrusive polynomial-chaos approach to propagate variability and is validated against Monte Carlo analysis. Results show the potential of the approach for a range of nonlinear dynamical systems, including a full wing configuration exhibiting supercritical and subcritical bifurcations, at a fraction of the cost of performing time domain simulations.

Prediction of Transonic Limit-Cycle Oscillations Using an Aeroelastic Harmonic Balance Method

This work proposes a novel approach to compute transonic limit-cycle oscillations using high-fidelity analysis. Computational-Fluid-Dynamics based harmonic balance methods have proven to be efficient tools to predict periodic phenomena. This paper’s contribution is to present a new methodology to determine the unknown frequency of oscillations, enabling harmonic balance methods to accurately capture limit-cycle oscillations; this is achieved by defining a frequency-updating procedure based on a coupled computational-fluid-dynamics/computational-structural-dynamics harmonic balance formulation to find the limit-cycle oscillation condition. A pitch/plunge airfoil and delta wing aerodynamic and respective linear structural models are used to validate the new method against conventional time-domain simulations. Results show consistent agreement between the proposed and time-marching methods for both limit-cycle oscillation amplitude and frequency while producing at least a one-order-of-magnitude reduction in computational time.

A mixed cost-function adaptive algorithm for ADSL time-domain equalization

We propose a mixed cost-function adaptive initialization algorithm for the time domain equalizer in a discrete multitone (DMT)-based asymmetric digital subscriber line. Using our approach, a higher convergence rate than that of the commonly used least-mean square algorithm is obtained, whilst attaining bit rates close to the optimum maximum shortening SNR and the upper bound SNR. Furthermore, our proposed method outperforms the minimum mean-squared error design for a range of time domain equalizer (TEQ) filter lengths. The improved performance outweighs the small increase in computational complexity required. A block variant of our proposed algorithm is also presented to overcome the increased latency imposed on the feedback path of the adaptive system.

Investigation of tanpura string vibrations using a two-dimensional time-domain model incorporating coupling and bridge friction

Tanpura string vibrations have been investigated previously using numerical models based on energy conserving schemes derived from a Hamiltonian description in one-dimensional form. Such time-domain models have the property that, for the lossless case, the numerical Hamiltonian (representing total energy of the system) can be proven to be constant from one time step
to the next, irrespective of any of the system parameters; in practice the Hamiltonian can be shown to be conserved within machine precision. Models of this kind can reproduce a jvari effect, which results from the bridge-string interaction. However the one-dimensional formulation has recently been shown to fail to replicate the jvaris strong dependence on the thread placement. As a first step towards simulations which accurately emulate this sensitivity to the thread placement, a twodimensional model is proposed, incorporating coupling of controllable level between the two string polarisations at the string termination opposite from the barrier. In addition, a friction force acting when the string slides across the bridge in horizontal direction is introduced, thus effecting a further damping mechanism. In this preliminary study, the string is terminated at the position of the thread. As in the one-dimensional model, an implicit scheme has to be used to solve the system, employing Newton's method to calculate the updated positions and momentums of each string segment. The two-dimensional model is proven to be energy conserving when the loss parameters are set to zero, irrespective of the coupling constant. Both frequency-dependent and independent losses are then added to the string, so that the model can be compared to analogous instruments. The influence of coupling and the bridge friction are investigated.

Method for rapid extraction of pectic substances from plant materials

A method is described for the rapid extraction of pectic substances from alcohol insoluble solids (AIS) from material of plant origin, especially fruit. Samples of AIS can be prepared for galacturonic acid assay within 60 min using extraction with 0·5m HCl in a Fibertec-1 system (Tecator) for 30 min. The extraction conditions are carefully standardised and operator error is reduced by the elimination of transfer steps, particularly during filtration. The results obtained for plant-derived alcohol insoluble solids containing from 10% to 33% pectic substances were in close agreement with those obtained by enzymic hydrolysis using a commercially available enzyme preparation (Ultrazyme). The method will have application in the rapid, routine estimation of pectic substances in plant materials. © 1987.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Power Spectral Density Side-Channel Attack Overlapping Window Method

Cryptographic algorithms have been designed to be computationally secure, however it has been shown that when they are implemented in hardware, that these devices leak side channel information that can be used to mount an attack that recovers the secret encryption key. In this paper an overlapping window power spectral density (PSD) side channel attack, targeting an FPGA device running the Advanced Encryption Standard is proposed. This improves upon previous research into PSD attacks by reducing the amount of pre-processing (effort) required. It is shown that the proposed overlapping window method requires less processing effort than that of using a sliding window approach, whilst overcoming the issues of sampling boundaries. The method is shown to be effective for both aligned and misaligned data sets and is therefore recommended as an improved approach in comparison with existing time domain based correlation attacks.