We present a systematic computational study based on the density functional theory (DFT) aiming to high light the possible effects of one As doping atom on the structural, energetic, and electronic properties of different isomers of Gen + 1 clusters with n = 1–20 atoms. By considering a large number of structures for each cluster size, the lowest-energy isomers are determined. The lowest-energy isomers reveal three-dimensional structures starting from n = 5. Their relative stability versus atomic size is examined based on the calculated binding energy, fragmentation energy, and second-order difference of energy. Doping Gen + 1 clusters with one As atom does not improve their stability. The electronic properties as a function of the atomic size are also discussed from the calculated HOMO–LUMO energy gap, vertical ionization potential, vertical electron affinity, and chemical hardness. The obtained results are significantly affected by the inclusion of one As atom into a Gen cluster.

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Mourad Oussalah, "Face antispoofing based on frame difference and multilevel representation,"Abstract. Due to advances in technology, today's biometric systems become vulnerable to spoof attacks made by fake faces. These attacks occur when an intruder attempts to fool an established face-based recognition system by presenting a fake face (e.g., print photo or replay attacks) in front of the camera instead of the intruder's genuine face. For this purpose, face antispoofing has become a hot topic in face analysis literature, where several applications with antispoofing task have emerged recently. We propose a solution for distinguishing between real faces and fake ones. Our approach is based on extracting features from the difference between successive frames instead of individual frames. We also used a multilevel representation that divides the frame difference into multiple multiblocks. Different texture descriptors (local binary patterns, local phase quantization, and binarized statistical image features) have then been applied to each block. After the feature extraction step, a Fisher score is applied to sort the features in ascending order according to the associated weights. Finally, a support vector machine is used to differentiate between real and fake faces. We tested our approach on three publicly available databases: CASIA Face Antispoofing database, Replay-Attack database, and MSU Mobile Face Spoofing database. The proposed approach outperforms the other state-of-the-art methods in different media and quality metrics.

The structures, relative stability and magnetic properties of pure Ge n+1 , neutral cationic and anionic Sn-Ge n (n = 1-17) clusters have been investigated by using the first principles density functional theory implemented in SIESTA packages. We find that with the increasing of cluster size, the Ge n+1 and SnGe n (0, ±1) clusters tend to adopt compact structures. It has been also found that the Sn atom occupied a peripheral position for SnGe n clusters when n < 12 and occupied a core position for n > 12. The structural and electronic properties such as optimized geometries, fragmentation energy, binding energy per atom, HOMO-LUMO gaps and second-order differences in energy of the pure Ge n+1 and SnGe n clusters in their ground state are calculated and analyzed. All isomers of neutral SnGe n clusters are generally nonmagnetic except for n = 1 and 4, where the total spin magnetic moments is 2μ b . The total (DOS) and partial density of states of these clusters have been calculated to understand the origin of peculiar magnetic properties. The cluster size dependence of vertical ionization potentials, vertical electronic affinities, chemical hardness, adiabatic electron affinities and adiabatic ionization potentials have been calculated and discussed.