52 research outputs found

    Role of strain reversal in microstructure and texture of pure al during non-monotonic simple shear straining

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    © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Dyestuff is one of the most widely released pollutants into the environment. Many approaches have been considered to deal with the dye removal from polluted water such as adsorption, ultrafiltration, osmosis, solvent extraction and photocatalytic degradation. The photocatalytic degradation process is one of the most beneficial, economical and environmentally friendly ways to degrade the organic pollutants from wastewater. In this study, an efficient ferrite-based photocatalyst, AgFeO2/rGO/TiO2 was successfully developed using simple deposition and reflux method. Physical, chemical and structural properties were analyzed by using XRD, FTIR Raman and PL spectroscopy. The efficiency of photocatalyst was investigated for the decolorization of methyl blue (MB) dye and activity was measured through UV-vis spectroscopy. The effect of parameters like pH, concentrations of MB dye, and loading of silver ferrite (AgFeO2) was investigated. The study depicted that the properties of TiO2 were improved due to addition of silver ferrite and reduced graphene oxide (rGO). The 2.5% AgFeO2/rGO/TiO2 exhibited the highest efficiency and completely degraded the 50 ppm of MB dye in 30 min. The parametric study revealed that dye decolorization is faster in a neutral solution than in basic and acidic medium. The higher performance of the photocatalyst was attributed to the reduced charge recombination and improved optical properties. Thus, AgFeO2/rGO/TiO2 can be a potential composite for photocatalytic dye degradation and other photocatalytic applications under UV-Visible light irradiations

    Multi-dimension Tensor Factorization Collaborative Filtering Recommendation for Academic Profiles

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    The choice of academic itineraries and/or optional subjects to attend is not usually an easy decision since, in most cases, students lack the information, maturity, and knowledge required to make right decisions. This paper evaluates the support of Collaborative Systems for helping and guiding students in this decision-making process, considering the behavior and impact of these systems on the use of data different from the formal information the students usually use. For this purpose, the research applied the clustering based Multi-dimension Tensor Factorization approach to build a recommendation system and confirm that the increment in tensors improves the recommendation accuracy. As a result, this approach permits the user to take advantage of the contextual information to reduce the sparsity issue and increase the recommendation accuracy
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