The green synthesis of nickel oxide nanoparticles (NiO-NP) was investigated using Ni(NO3)2 as a precursor, olive tree leaves as a reducing agent, and D-sorbitol as a capping agent. The structural, optical, and morphology of the synthesized NiO-NP have been characterized using ultraviolet–visible spectroscopy (UV-Vis), X-ray crystallography (XRD) pattern, Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM) analysis. The SEM analysis showed that the nanoparticles have a spherical shape and highly crystalline as well as highly agglomerated and appear as cluster of nanoparticles with a size range of (30 to 65 nm). The Scherrer relation has been used to estimate the crystallite size of NiO-NP which has been found about 42 nm. The NiO-NPs have subsequently used as adsorbents for adsorption of two types of dyes; methylene blue (MB) as cation dye and methyl orange (MO) as anion dye. The removal efficiency of dyes from contaminated water was investigated during various key parameters at room temperature; initial dye concentration (Co), pH, contact time (t), agitation speed, and adsorbent dosage. The maximum removal of MB dye was found to be 96% (Co=25 mg/l, pH=10, contact time=100 min, agitation speed=300 rpm and adsorbent dosage=6 g/l), while for MO the maximum removal reached 88% at (Co=20 mg/L, pH=2, contact time=160 min, agitation speed=300 rpm and adsorbent dosage=6 g/L). The experimental adsorption data were found to well obey Freundlich isotherm. The kinetic investigation showed that the adsorption process for both dyes followed a pseudo-second-order model with rate constants 0.0109 and 0.0079 (mg/g min) for MB and MO, respectively.
Electrochemical corrosion of hydroxyapatite (HAP) coated performance depends on various parameters like applied potential, time, thickness and sintering temperature. Thus, the optimum parameters required for the development of stable HAP coatings was found by using electrophoretic deposition (EPD) technique. This study discusses the results obtained from open circuit potential-time measurements (OCP-time), potentiodynamic polarisation and immersion tests for all alloy samples done under varying experimental conditions, so that the optimum coating parameters can be established. The ageing studies of the coated samples were carried out by immersing them in Ringer’s solution for a period of 30 days indicates the importance of stable HAP c
... Show MoreIn his post colonial novel, In the Skin of a lion, the Canadian/Sri Lankan writer,
Michael Ondaatje is so interested in the term "Post colonialism" because he wants to show
that the term doesn't only refer to a period of time that comes after colonialism. In other
words, post colonialism is not only referred to as a literal description of formerly colonial
societies. He deals with the termas a literary genre and an academic construct that describes
the global conditions of a man after a period of colonialism. He shows that post colonialism is
a theory that tries to examine and explore the different styles and faces of European authority
to control the colonized. Ondaatje's attempt through such term is to unmask Europ
Current search aims to identify the creative thinking of the kindergarten teachers and
solving professional problems among kindergarten teachers skills, and whether the level of
creative thinking in solving professional problems, according on marital status years of
service academic achievement of teachers as well as to identify the correlation between the
two variables the current sample consisted of (300) teachers to achieve the objectives of the
stndy , the researcher used two measures, one to measure creative thinking and the other to
measure the solution to the problems of professional kindergarten teachers skills. It has been
shown. validity and reliability of the two measures. The present stndy aims to identif
This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota
... Show MoreVideo streaming is widely available nowadays. Moreover, since the pandemic hit all across the globe, many people stayed home and used streaming services for news, education, and entertainment. However, when streaming in session, user Quality of Experience (QoE) is unsatisfied with the video content selection while streaming on smartphone devices. Users are often irritated by unpredictable video quality format displays on their smartphone devices. In this paper, we proposed a framework video selection scheme that targets to increase QoE user satisfaction. We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. Video Content Selection (VCS) are classified in
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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