Robust blind watermarking approach against the compression for fingerprint image using 2D-DCT

This article presents a recent blind and robust fingerprint image watermarking scheme based on a two-dimensional discrete cosine transform (2D-DCT). The main focus is to compress the fingerprint image watermarked data for the purpose of reducing the volume of storage or sending over the network. The fingerprint features might be affected by the embedded watermark, compression of fingerprint images and the sending across network, thereby leading to various sets of features or watermark data. In order to address this goal in a differential way, the watermark sequence bit two sub-vectors were utilized. The two sub-vectors were achieved by the two-dimensional discrete cosine transform of the host image. Throughout the extraction stage, the essential distinction between the corresponding sub-vectors of the watermarked fingerprint image resulted explicitly in an embedded watermark sequence. The advantage of the proposed method is that it can develop a new simple blind and robust watermarking scheme by 2D-DCT frequency domain on the whole image. Accomplished results relative to other reliable compression schemes showed that the proposed scheme has greater or equivalent robustness to common image processing and geometric attacks, such as cropping, resizing, and rotation. To extract watermark data, the initial fingerprint image was not necessary. The proposed study was tested using 80 fingerprint images from 10 persons, for each from CASIA-FingerprintV5 and FVC2002 fingerprint databases. Eight fingerprint images for each individual were set as the format at which the watermark was embedded in each one.

     

Velocity‐free attitude stabilization with inertial vector measurements

This paper deals with the attitude stabilization problem of a rigid body, where neither the angular velocity nor the attitude is used in the feedback; only body‐referenced vector measurements are needed. The proposed control scheme is based on an angular velocity observer‐like system relying solely on vector measurements. The proposed controller ensures almost global asymptotic stability and provides some interesting performance properties through an appropriate tuning of the control gains. The performance and effectiveness of the proposed control scheme are illustrated via simulation results where the control gains are adjusted using a nonlinear optimization. Copyright © 2015 John Wiley & Sons, Ltd.     

Multi-level A Priori Hyper-Reduction of mechanical models involving internal variables

This paper concerns the adaptation of reduced-order models during simulations of series of elastoviscoplastic problems. In continuation with previous works, this paper aimed at extending the A Priori Hyper-Reduction method (APHR method) for nonlinear thermal problems to nonlinear mechanical problems involving internal variables. This method is an a priori approach because full incremental responses of detailed models are not forecasted in order to build reduced-order models. The recent extension of the Hyper-Reduction method to reduction of mechanical models involving internal variables makes possible the reduction of degrees of freedom and the reduction of integration points. A multi-level formulation is introduced to focus on the capability of the method to perform efficient parallel computations to adapt reduced-order models.     

Distinct regulation of T-cell death by CD28 depending on both its aggregation and T-cell receptor triggering: a role for Fas-FasL

CD28 is a major coreceptor that regulates cell proliferation, anergy, and viability of T cells. The negative selection by T-cell receptor (TCR)-induced cell death of immature thymocytes as well as of activated human antigen-specific T-cell clone, requires a costimulatory signal that can be provided by CD28. Conversely, CD28-mediated signals increase expression of Bcl-XL, a survival gene, and promote survival of naive T cells cultured in the absence of antigen or costimulation. Because CD28 appears to both protect from, or induce T-cell death, one important question is to define the activation and cellular parameters that dictate the differential role of CD28 in T-cell apoptosis. Here, we compared different CD28 ligands for their ability to regulate TCR-induced cell death of a murine T-cell hybridoma. In these cells, TCR triggering induced expression of Fas and FasL, and cell death was prevented by anti-Fas blocking monoclonal antibody (MoAb). When provided as a costimulus, both CD28 MoAb and the B7.1 and B7.2 counter receptors downregulated, yet did not completely abolish T-cell receptor-induced apoptosis. This CD28 cosignal resulted in both upregulation of Bcl-XL and prevention of FasL expression. In marked contrast, when given as a single signal, CD28 MoAb or B7.1 and B7.2 induced FasL expression and resulted in T-cell death by apoptosis, which was dependent on the level of CD28 ligation. Furthermore, triggering of CD28 upregulated FasL and induced a marked T-cell death of previously activated normal peripheral T cells. Our results identify Fas and FasL as crucial targets of CD28 in T-cell death regulation and show that within the same cell population, depending on its engagement as a single signal or as a costimulus together with the TCR, CD28 can either induce a dose-dependent death signal or protect from cell death, respectively. These data provide important insights into the role of CD28 in T-cell homeostasis and its possible implication in neoplastic disorders.     

A robust adaptive model reduction method for damage simulations

In our opinion, many of complex numerical models in materials science can be reduced without losing their physical sense. Due to solution bifurcation and strain localization of continuum damage problems, damage predictions are very sensitive to any model modification. Most of the robust numerical algorithms intend to forecast one approximate solution of the continuous model despite there are multiple solutions. Some model perturbations can possibly be added to the finite element model to guide the simulation toward one of the solutions. Doing a model reduction of a finite element damage model is a kind of model perturbation. If no quality control is performed the prediction of the reduced-order model (ROM) can really differ from the prediction of the full finite element model. This can happen using the snapshot Proper Orthogonal Decomposition (POD) model reduction method. Therefore, if the expected purpose of the reduced approximation is to estimate the solution that the finite element simulation should give, an adaptive reduced-order modeling is required when reducing finite element damage models.We propose an adaptive reduced-order modeling method that enables to estimate the effect of loading modifications. The Rousselier continuum damage model is considered. The differences between the finite element prediction and the one provided by the adapted reduced-order model (ROM) remain stable although various loading perturbations are introduced. The adaptive algorithm is based on the APHR (A Priori Hyper Reduction) method. This is an incremental scheme using a ROM to forecast an initial guess solution to the finite element equations. If, at the end of a time increment, this initial prediction is not accurate enough, a finite element correction is added to the ROM prediction. The proposed algorithm can be viewed as a two step Newton–Raphson algorithm. During the first step the prediction belongs to the functional space related to the ROM and during the second step the correction belongs to the classical FE functional space. Moreover the corrections of the ROM predictions enable to expand the basis related to the ROM. Therefore the ROM basis can be improved at each increment of the simulation. The efficiency of the adaptive algorithm is checked comparing the amount of global linear solutions involved in the proposed scheme versus the amount of global linear solutions involved in the classical incremental Newton–Raphson scheme. The quality of the proposed approximation is compared to the one provided by the classical snapshot Proper Orthogonal Decomposition (POD) method.