A novel underdetermined source recovery algorithm based on k-sparse component analysis

Sparse component analysis (SCA) is a popular method for addressing underdetermined blind source separation in array signal processing applications. We are motivated by problems that arise in the applications where the sources are densely sparse (i.e. the number of active sources is high and very close to the number of sensors). The separation performance of current underdetermined source recovery (USR) solutions, including the relaxation and greedy families, reduces with decreasing the mixing system dimension and increasing the sparsity level (k). In this paper, we present a k-SCA-based algorithm that is suitable for USR in low-dimensional mixing systems. Assuming the sources is at most (m−1) sparse where m is the number of mixtures; the proposed method is capable of recovering the sources from the mixtures given the mixing matrix using a subspace detection framework. Simulation results show that the proposed algorithm achieves better separation performance in k-SCA conditions compared to state-of-the-art USR algorithms such as basis pursuit, minimizing norm-L1, smoothed L0, focal underdetermined system solver and orthogonal matching pursuit

Carbon dioxide compressibility factor determination using a robust intelligent method

Owing to the demanding applications and wide uses of supercritical carbon dioxide in oil, gas and chemical industries, fast and precise estimation of carbon dioxide compressibility factor is of a vital significance in order to be imported into the relevant industrial simulators. In this study, a data bank covering wide range of temperature and pressure was gathered from open literature. Afterwards, a rigorous novel approach, namely least square support vector machine (LSSVM) optimized with coupled simulated annealing (CSA) was proposed to develop a reliable and robust model for the prediction of compressibility factor of carbon dioxide. Reduced temperature and pressure are the inputs of the model. 80% of the dataset was used for training the model and the remaining 20% was used to evaluate its accuracy and reliability. Statistical and graphical error analyses have been conducted to investigate the performance of the model and the obtained results from the proposed model have been compared with those of six equations of state, REFPROP package and two correlations. It was demonstrated that the proposed CSA–LSSVM model is more efficient and reliable than all of the studied empirical correlations, equations of state and the software package, hence it can be utilized confidently for the prediction of carbon dioxide compressibility factor

Enhanced photocatalytic activity of Fe3O4-WO3-APTES for azo dye removal from aqueous solutions in the presence of visible irradiation

Development of highly active photocatalysts for treatment of dye-laden wastewaters is vital. The photocatalytic removal of azo dye Reactive Black 5 was investigated by Fe3O4-WO3-3-aminopropyltriethoxysilane (APTES) nanoparticles in the presence of visible light. The Fe3O4-WO3-APTES nanoparticles were synthesized via a facile coprecipitation method. The photocatalyst was characterized by XRD, FT-IR, SEM, EDX, VSM, UV�Vis, and pHPZC techniques. The effects of some operational parameters such as solution pH, nanophotocatalyst dosage, initial RB5 concentration, H2O2 concentration, different purging gases, and type of organic compounds on the removal efficiency were studied by the Fe3O4-WO3-APTES nanoparticles as a photocatalyst. Maximum phtocatalytic activity was obtained at pH 3. The photocatalytic removal of RB5 increased with increasing H2O2 concentration up to 5�mM. The removal efficiency declined in the presence of different purging gases and all types of organic compounds. First-order rate constant (kobs) decreased from 0.027 to 0.0022�min�1 and electrical energy per order (EEo) increased from 21.33 to 261.82 (kWh/m3) with increasing RB5 concentration from 10 to 100�mg/L, respectively. The efficiency of LED/Fe3O4-WO3-APTES process for RB5 removal was approximately 89.9, which was more effective than the LED/Fe3O4-WO3 process (60.72). Also, photocatalytic activity decreased after five successive cycles. © 2018 Taylor & Franci

Photocatalytic degradation of a textile dye by illuminated tungsten oxide nanopowder

In this study, photocatalytic degradation of Acid Orange 7 (AO7) by tungsten oxide nanopowder under UV irradiation was investigated with variation of pH, WO3 dosage, initial AO7 concentration, purging gas, type of organic compounds and initial hydrogen peroxide concentration. Removal efficiency was decreased by increasing pH and initial AO7 concentration. The removal efficiency of AO7 was increased by purging of oxygen gas and by addition of hydrogen peroxide. The reaction rate constant (kobs) was decreased from 0.0225 to 0.0006 min-1 with increasing initial AO7 concentration from 5 to 50 mg/L, respectively. © 2015 Science & Technology Network, Inc

Enhanced photocatalytic activity of Fe 3 O 4 -WO 3 -APTES for azo dye removal from aqueous solutions in the presence of visible irradiation

Development of highly active photocatalysts for treatment of dye-laden wastewaters is vital. The photocatalytic removal of azo dye Reactive Black 5 was investigated by Fe 3 O 4 -WO 3 -3-aminopropyltriethoxysilane (APTES) nanoparticles in the presence of visible light. The Fe 3 O 4 -WO 3 -APTES nanoparticles were synthesized via a facile coprecipitation method. The photocatalyst was characterized by XRD, FT-IR, SEM, EDX, VSM, UV�Vis, and pH PZC techniques. The effects of some operational parameters such as solution pH, nanophotocatalyst dosage, initial RB5 concentration, H 2 O 2 concentration, different purging gases, and type of organic compounds on the removal efficiency were studied by the Fe 3 O 4 -WO 3 -APTES nanoparticles as a photocatalyst. Maximum phtocatalytic activity was obtained at pH 3. The photocatalytic removal of RB5 increased with increasing H 2 O 2 concentration up to 5 mM. The removal efficiency declined in the presence of different purging gases and all types of organic compounds. First-order rate constant (k obs ) decreased from 0.027 to 0.0022 min �1 and electrical energy per order (E Eo ) increased from 21.33 to 261.82 (kWh/m 3 ) with increasing RB5 concentration from 10 to 100 mg/L, respectively. The efficiency of LED/Fe 3 O 4 -WO 3 -APTES process for RB5 removal was approximately 89.9, which was more effective than the LED/Fe 3 O 4 -WO 3 process (60.72). Also, photocatalytic activity decreased after five successive cycles. © 2018, © 2018 Taylor & Francis