Corncob is an agricultural biomass waste that was widely investigated as an adsorbent of contaminants after transforming it into activated carbon. In this research carbonization and chemical activation processes were achieved to synthesize corncob-activated carbon (CAC). Many pretreatment steps including crushing, grinding, and drying to obtain corncob powder were performed before the carbonization step. The carbonization of corncob powder has occurred in the absence of air at a temperature of 500 °C. The chemical activation was accomplished by using HCl as an acidic activation agent. Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) facilitated the characterization of (CAC). The results showed the CAC has non-uniform morphological features with different shapes of its active sites. The prepared CAC was utilized in adsorption of sulfur in its highly complex form of dibenzothiophene (DBT). Particular adsorption parameters of contacting time, temperature, and adsorbent dose were optimized to select the best conditions. These certain conditions are then applied in the adsorption of different DBT concentrations. The maximum removal of DBT reached around 83% at optimal conditions of contacting time (30 min), temperature (60 °C), and adsorbent dose (3 g L-1). The removal efficiency was significantly increased by decreasing the initial concentration of DBT. The experimental data fitted well with the Freundlich isotherm model compared with the Langmuir one. The maximum capacity of CAC for adsorption of DBT at equilibrium was 833.3 mg g-1 at 60 °C. The findings of this research introduce the CAC as a feasible adsorbent for removal DBT from simulated liquid petroleum fuels.
String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-co
... Show MoreIn this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the
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In The Bluest Eye (1970), the American-African writer, Toni Morrison explores how
Western standards of ideal beauty are created and propagated with and among the black
community. The novel not only portrays the lives of those whose dark skinned and Negroid
features blight their lives; it also shows how the standard of white beauty, when imposed on
black youth, can drastically damage one’s self-love and esteem which usually occurs when
beauty goes unrecognized. Morrison in this novel focuses on the damage that the black
women characters suffer through the construction of femininity in a racialised society where
whiteness is used as a standard of beauty.
The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
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