Advanced SOM & K Mean Method for Load Curve Clustering

From the load curve classification for one customer, the main features such as the seasonal factors, the weekday factors influencing on the electricity consumption may be extracted. By this way some utilities can make decision on the tariff by seasons or by day in week. The popular clustering techniques are the SOM & K-mean or Fuzzy K-mean. SOM &Kmean is a prominent approach for clustering with a two-level approach: first, the data set will be clustered using the SOM and in the second level, the SOM will be clustered by K-mean. In the first level, two training algorithms were examined: sequential and batch training. For the second level, the K-mean has the results that are strongly depended on the initial values of the centers. To overcome this, this paper used the subtractive clustering approach proposed by Chiu in 1994 to determine the centers. Because the effective radius in Chiu’s method has some influence on the number of centers, the paper applied the PSO technique to find the optimum radius. To valid the proposed approach, the test on well-known data samples is carried out. The applications for daily load curves of one Southern utility are presented

One-pot preparation of alumina-modified polysulfone-graphene oxide nanocomposite membrane for separation of emulsion-oil from wastewater

In recent years, polysulfone-based nanocomposite membranes have been widely used for contaminated water treatment because they comprise properties such as high thermal stability and chemical resistance. In this study, a polysulfone (PSf) nanocomposite membrane was fabricated using the wet-phase inversion method with the fusion of graphene oxide (GO) and alumina (Al2O3) nanoparticles. We also showed that GO-Al2O3 nanoparticles were synthesised successfully by using a one-pot hydrothermal method. The nanocomposite membranes were characterised by Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), nitrogen adsorption-desorption isotherms, energy-dispersive X-ray spectroscopy (EDX), thermogravimetric analysis (TGA), and water contact angle. The loading of GO and Al2O3 was investigated to improve the hydrophilic and oil rejection of the matrix membrane. It was shown that by using 1.5 wt.% GO-Al2O3 loaded in polysulfone, ~74% volume of oil was separated from the oil/water emulsion at 0.87 bar and 30 min. This figure was higher than that of the process using the unmodified membrane (PSf/GO) at the same conditions, in which only ~60% volume of oil was separated. The pH, oil/water emulsion concentration, separation time, and irreversible fouling coefficient (FRw) were also investigated. The obtained results suggested that the GO-Al2O3 nanoparticles loaded in the polysulfone membrane might have potential use in oily wastewater treatment applications

Green Synthesis and Antibacterial Activity of HAp@Ag Nanocomposite Using Centella asiatica (L.) Urban Extract and Eggshell

In recent years, the green synthesis of nanoparticles via biological processes has attracted considerable attention. Herein, we introduce a facile and green approach for the synthesis of poriferous silver nanoparticles (Ag-NPs) decorated hydroxylapatite (HAp@Ag) nanoparticles with excellent antibacterial properties. All the nanocomposites were fully characterized in the solid state via various techniques such as X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and energy-dispersive X-ray spectrometer (EDX), in which the synthesized Ag-NPs (24 nm in diameter) and their homogeneous incorporation on HAp have been studied by ultraviolet-visible (UV-vis) technique, transmission electron microscopy (TEM), and dynamic light scattering (DLS) analysis. The obtained results indicate that the structure and morphology of HAp have no significant changes after the incorporation of Ag-NPs on its surface. Moreover, an impressive antibacterial activity of HAp@Ag nanocomposite against Gram-positive bacterium Staphylococcus aureus and Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa has been recorded by using the agar well diffusion method. As a result, the HAp@Ag nanocomposite promises to be a great biomedical material with high antibacterial properties