Voice spoofing detection based on acoustic and glottal flow features using conventional machine learning techniques

Multimedia Tools and Applications - Automatic Speaker Verification (ASV) systems are vulnerable to spoofing attacks. Most existing spoofing detection systems rely on two main points; the feature...     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

H∞ control for uncertain one‐sided Lipschitz nonlinear systems in finite frequency domain

The current article discusses the H_∞ disturbance attenuation control design problem for one‐sided Lipschitz systems in finite frequency domain. Models containing norm‐bounded parameter uncertainties, disturbances, and input nonlinearities are considered. By contrast to existing full frequency methods, the H_∞ controller is computed depending on the frequency ranges of disturbances. The finite frequency disturbance attenuation index is initially defined. Thanks to Finsler's lemma, sufficient and less conservative analysis conditions are also derived for the closed‐loop system. Then, synthesis conditions in the low, middle, and high frequency ranges as well as the whole frequency range, are formulated in terms of linear matrix inequalities. At last, to prove the effectiveness and the superiority of the proposed approach, a physical example is used and a comparative study is done.     

Production of Synthesis Gas via Dry Reforming of Methane over Co‐Based Catalysts: Effect on H2/CO Ratio and Carbon Deposition

The effect of support type on synthesis gas production using Co‐based catalysts supported over TiO₂‐P25, Al₂O₃, SiO₂, and CeO₂ was investigated. The catalysts were prepared by the incipient wet impregnation method and characterized by various techniques for comparison. Experiments were performed in a micro tubular reactor. The results revealed that all Co‐supported catalysts produced synthesis gas ratios of 1 and below and, thus, proved to be well‐suited for methanol and Fischer‐Tropsch syntheses. Co catalysts supported over TiO₂‐P25 and Al₂O₃ provided better synthesis gas ratios and stability performances. The promotion of a Co/TiO₂‐P25 catalyst with Ce had a substantial influence on its catalytic activity and the amount of carbon deposit. A Ce‐promoted catalyst diminished markedly the extent of carbon deposition and thus boosted the performance towards better activity and stability.     

Validation and improvement of gamma heating calculation methods for the G.A. Siwabessy multipurpose reactor

Nuclear Science and Techniques - This study presents the RF design of a linear accelerator (linac) operated in single-bunch mode. The accelerator is powered by a compressed RF pulse produced from a...     

Removal of lead(Pb(Ⅱ))and zinc(Zn(Ⅱ))from aqueous solution using coal fly ash(CFA)as a dual-sites adsorbent

Coal fly ash(CFA)is composed of minerals containing some oxides in crystalline phase(i.e.,quartz and mullite),as well as unburned carbon as mesoporous material,thus enabling CFA to act as a dual-sites adsorbent with unique properties.This work focused on the adsorption of Pb(Ⅱ)and Zn(Ⅱ)from binary system,a mixture containing two metal ion solutions present simultaneously,onto NaOH-modified CFA(MCFA).Several adsorption tests were conducted to evaluate the effect of several parameters,includ-ing pH and contact times.The experiment results indicated that chemical treatment of CFA with NaOH increased pore volume from 0.021 to 0.223 cm3 g-1.In addition,it could also enhance the availability of functional groups on both minerals and unburned carbon,resulting in almost 100％Pb(Ⅱ)and 97％Zn(Ⅱ)adsorbed.The optimum pH for adsorption system was pH=3 and quasi-equilibrium occurred in 240 minutes.Equilibrium data from the experimental results were analyzed using Modified Extended Langmuir(MEL)and Competitive Adsorption Langmuir-Langmuir(CALL)isotherm models.The analysis results showed that the CALL isotherm model could better describe the Pb(Ⅱ)and Zn(Ⅱ)adsorption pro-cess onto MCFA in binary system compared with MEL isotherm model.     

Experimental and numerical investigation of intermittent drying of timber

Intermittent drying may be of interest in the future to address energy issues. Such drying conditions are also likely to help stress relaxation through mechanosorptive creep. The influence of applying oscillations of temperature and relative humidity during the drying of beech timber on time and drying stresses is discussed in the paper by means of nonsymmetrical and loaded drying. Experimental data were used to validate a numerical model in the case of intermittent drying. The model was then used to perform a numerical investigation of the possibility of using an intermittent energy source to dry wood.     

Noise estimation for speech enhancement algorithms with post-smoothness processor incorporating global posterior SNR

Multimedia Tools and Applications - Performances of speech enhancement algorithms depend greatly on the accuracy of the estimated noise. In this paper, we explain in details the relationship...     

Extracting TSK-type Neuro-Fuzzy model using the Hunting search algorithm

This paper proposes a Takagi-Sugeno-Kang (TSK) type Neuro-Fuzzy model tuned by a novel metaheuristic optimization algorithm called Hunting Search (HuS). The HuS algorithm is derived based on a model of group hunting of animals such as lions, wolves, and dolphins when looking for a prey. In this study, the structure and parameters of the fuzzy model are encoded into a particle. Thus, the optimal structure and parameters are achieved simultaneously. The proposed method was demonstrated through modeling and control problems, and the results have been compared with other optimization techniques. The comparisons indicate that the proposed method represents a powerful search approach and an effective optimization technique as it can extract the accurate TSK fuzzy model with an appropriate number of rules.     

Microstructural,hydraulic conductivity and geochemical changes of drying mature fine oil sand tailings in column experiments

This study offers new insights into two-lift deposition of mature fine tailings under atmospheric drying. The interaction of newly added lift and former lift(s) was evaluated using column experiments in terms of volumetric water content, electrical conductivity (EC), hydraulic conductivity, geochemistry and microstructure. Water content and EC followed the same trend and decreasing of water content appears to be responsible for significant reduction in EC. Evaporation on top of the column reduced the water content to almost zero. The obtained results support the coupling between the hydraulic and chemical processes that should be considered by active operators.