A new approach in solving illumination and facial expression problems for face recognition

In this paper, a novel dual optimal multiband features (DOMF) method is presented to increase the robustness of face recognition system to illumination and facial expression variations.The wavelet packet transform first decomposes image into low-, mid- and high-frequency subbands and the multiband feature fusion technique is incorporated to select the subbands that are invariant to illumination and expression variation separately.These subbands form the optimal feature sets.Parallel radial basis function neural networks are employed to classify these feature sets.The scores generated by the neural networks are combined by an adaptive fusion mechanism where the level of illumination variations of the testing image is estimated and the weights are assigned to the scores accordingly.The experimental results show that DOMF outperforms other algorithms and also achieves promising performance on illumination and facial expression variation conditions

Synergized Mechanistic and Solar Photocatalysis Features of N-TiO2 Functionalised Activated Carbon

A TiO2 photocatalysts was successfully functionalised by employing nitrogen (N) as a dopant on activated carbon (AC) support as synergist. Two different types of activated carbon adopting namely Garcinia mangostana and palm shell as precursor were chosen as an activated carbon support. Thus the synthesized samples were examined for its physical and chemistry properties through advanced microscopic and spectroscopic techniques. The results revealed the contribution of adsorbent support through the rich surface area while doping of nitrogen contributed for effectively utilizing the incident photons by narrowing the band gap energy. The synergetic adsorption-photocatalytic activity was investigated by adopting batik dye, Remazol Brilliant Blue Dye (RBB) as model pollutant. Thus the N-TiO2 functionalised activated carbon demonstrated excellent adsorption-photocatalytic activity with 80% removal efficiency in 6 h. The synergism of adsorption photocatalysis portrayed the alternative for treating recalcitrant RBB a predominant dye found in batik textile industry wastewate

Carba-Cyclophellitols are Neutral Retaining Glucosidase Inhibitors

The conformational analysis of glycosidases affords a route to their specific inhibition through transition-state mimicry. Inspired by the rapid reaction rates of cyclophellitol and cyclophellitol aziridineboth covalent retaining β-glucosidase inhibitorswe postulated that the corresponding carba “cyclopropyl” analogue would be a potent retaining β-glucosidase inhibitor for those enzymes reacting through the ⁴H₃ transition-state conformation. <i>Ab initio</i> metadynamics simulations of the conformational free energy landscape for the cyclopropyl inhibitors show a strong bias for the ⁴H₃ conformation, and carba-cyclophellitol, with an <i>N</i>-(4-azidobutyl)­carboxamide moiety, proved to be a potent inhibitor (<i>K</i>_i = 8.2 nM) of the <i>Thermotoga maritima</i> <i>Tm</i>GH1 β-glucosidase. 3-D structural analysis and comparison with unreacted epoxides show that this compound indeed binds in the ⁴H₃ conformation, suggesting that conformational strain induced through a cyclopropyl unit may add to the armory of tight-binding inhibitor designs

Gluco-1 H-imidazole : A New Class of Azole-Type β-Glucosidase Inhibitor

Gluco-azoles competitively inhibit glucosidases by transition-state mimicry and their ability to interact with catalytic acid residues in glucosidase active sites. We noted that no azole-type inhibitors described, to date, possess a protic nitrogen characteristic for 1 H-imidazoles. Here, we present gluco-1 H-imidazole, a gluco-azole bearing a 1 H-imidazole fused to a glucopyranose-configured cyclitol core, and three close analogues as new glucosidase inhibitors. All compounds inhibit human retaining β-glucosidase, GBA1, with the most potent ones inhibiting this enzyme (deficient in Gaucher disease) on a par with glucoimidazole. None inhibit glucosylceramide synthase, cytosolic β-glucosidase GBA2 or α-glucosidase GAA. Structural, physical and computational studies provide first insights into the binding mode of this conceptually new class of retaining β-glucosidase inhibitors

Audio-visual recognition system in compression domain

This paper presents a highly efficient audio-visual recognition system in compression domain. For face recognition systems, the multiband feature fusion method selects the wavelet subbands that are invariant to illumination and facial expression variations. These subbands will be extracted directly from the inverse quantization in the compression system. By taking the inverse quantized wavelet coefficient of the video as the input, the inverse wavelet transform which corresponds to image reconstruction is omitted. As a result, the computational complexity of the conventional video-based face recognition system is reduced. We also present a set of new face localization methods to localize the facial wavelet coefficients from the wavelet subband image. The dual optimal multiband feature fusion method is then used to fuse the two set of wavelet coefficients and generate the visual scores. Experimental results show that with low computational complexity, the proposed system achieves high recognition accuracy in UNMC-VIER, CUAVE, and XM2VTS audio-visual database.</p

Radial basis function neural network with incremental learning for face recognition

Conventional face recognition suffers from problems such as extending the classifier for newly added people and learning updated information about the existing people. The way to address these problems is to retrain the system which will require expensive computational complexity. In this paper, a radial basis function (RBF) neural network with a new incremental learning method based on the regularized orthogonal least square (ROLS) algorithm is proposed for face recognition. It is designed to accommodate new information without retraining the initial network. In our proposed method, the selection of the regressors for the new data is done locally, hence avoiding the expensive reselecting process. In addition, it accumulates previous experience and learns updated new knowledge of the existing groups to increase the robustness of the system. The experimental results show that the proposed method gives higher average recognition accuracy compared to the conventional ROLS-algorithm-based RBF neural network with much lower computational complexity. Furthermore, the proposed method achieves higher recognition accuracy as compared to other incremental learning algorithms such as incremental principal component analysis and incremental linear discriminant analysis in face recognition.</p

Interface-Modulated Resistive Switching in Mo-Irradiated ReS2 for Neuromorphic Computing

https://doi-org.libproxy1.nus.edu.sg/10.1002/adma.202202722Advanced Materials3430220272