Research on Embroidery Feature Recognition Algorithm of Traditional National Costumes Based on Double-Layer Model

In order to improve the visual communication ability of traditional national costume patterns, it is necessary to carry out image texture intelligent matching processing. A traditional national costume embroidery feature recognition algorithm based on a double-layer model is proposed. The traditional national costume pattern texture intelligent information acquisition model under the double-layer model is constructed to carry out texture imaging and feature segmentation of traditional national costume patterns, extract the texture histogram of traditional national clothing pattern and national design language, carry out texture segmentation and automatic matching under the two-layer model according to the histogram distribution, enhance and optimize the texture information of traditional national clothing pattern, extract the edge contour feature points of traditional national clothing pattern, and complete the embroidery feature recognition of traditional national clothing. The experimental results show that the designed recognition algorithm has high integrity and accuracy.

Structural and Electrical Characteristics of FeTiVO6 Double Perovskite

In this paper, studies of structural as well as electrical characteristics of the double perovskite material FeTiVO6 (iron titanium vanadate), synthesized by a high-temperature mixed oxide reaction method have been discussed. The room temperature X-ray diffraction analysis confirms the formation of a single-phase orthorhombic structure without any secondary phase. All the electrical characteristics (i.e., dielectric, impedance, conductivity and modulus) of the sample, studied at various temperatures (25–300°C) and frequencies (1[Formula: see text]kHz–1[Formula: see text]MHz), provide many remarkable characteristics of the material. The dielectric parameters as a function of frequency explain the presence of different polarization mechanisms based on the Maxwell–Wagner double-layer model. Impedance analysis describes the grain (bulk) and grain boundary (bulk interior) effect on the material using the equivalent RQC-RC circuits. The presence of non-Debye type of relaxation behavior in the material is confirmed by the depressed semicircles of Nyquist plots. The conductivity study provides information about the CBH and OLPT type of conduction phenomenon. The temperature dependence of leakage current behavior follows the Ohmic (semiconductor) and space charge limited conduction mechanisms at a different range of applied fields. The occurrence of the room temperature hysteresis loop obtained from the PE loop tracer confirms the ferroelectric behavior of the studied compound.

Adsorption of Congo Red on Pb doped FexOy: experimental study and theoretical modeling via double-layer statistical physics models

Size-controlled Pb0.06Fe0.7O3 nanoparticles (Pb-FeONPs) werefabricated by the thermal co-precipitation method and characterized by FE-SEM, EDX, XRD, and IR techniques. The SEM and XRD images showed the average size distribution and average crystallite size of 19.21 nm and 4.9 nm, respectively. The kinetic model of congo red (CR) adsorption onto Pb-FeONPs was verified and found to bea pseudo-second-order reaction. The Langmuir plot best fitted (R2 = 0.990) than other isotherm models with a Qmax (mg/g) of 500 for congo red (CR) dye in 40 min. The double-layer statistical physics model based on two energies was used to calculate the significant parameters. The n (Stoichiometric coefficient) values obtained from the statistical physics double-layer model were found to be 0.599, 0.593, and 0.565 which are less than 1, indicating the multi-docking process. The regeneration of Pb-FeONPs was used upto 5 cycles effectively, making the material highly economical. The Pb-FeONPs were fruitfully applied for the removal of CR dye from wastewater on a laboratory and industrial scale.

Competitive Adsorption of As(III), As(V), and PO4 by an Iron Oxide Impregnated Activated Carbon: Surface Complex Modeling

The objective of this study was to predict the competitive adsorption of As(III), As(V), and PO4 by an iron oxide impregnated carbon (L-Act, 9% Fe(III) amorphous iron oxide) over a range of environmental conditions using the surface complexation modeling (SCM) approach. L-Act surface complexation constants determined from a single pH-adsorption edge were used to predict pH-dependent competitive removal in singular, binary, and tertiary adsorbate systems. As(III), As(V), and PO4 complexes were modeled as bidentate binuclear species at low pH and monodentate species at high pH using the two monoprotic surface site/diffuse electric double layer model (2MDLM). F values determined based on 2MDLM predictions were close to those calculated by FITEQL (a statistical optimization program) demonstrating the effectiveness of the 2MDLM in describing adsorption behavior. F values were generally in the recommended range of 0.1–20 indicating a good fit between the data and the model. The 2MDLM also successfully predicted As(III)/As(V)/PO4 adsorption data of hydrous ferric oxide and goethite adsorbents from the literature.