In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
Drug nanocrystals are nanoscopic crystals of the parent compound with dimensions less than 1 µm. A decrease in particle size will lead to an increase in effective surface area in the diffusion layer, which, in turn, increases the drug dissolution rate. Drug nanocrystals are one of the most important strategies to enhance the oral bioavailability of hydrophobic drugs.
Cefixime is the first member of what is generally termed the third generation orally active cephalosporins. These third generation cephalosporins are distinct from the older β-lactam antibiotics in their intensive antibacterial activity against a wide range of gram-negative bacteria.
The aim of this study is to prepare nanocrystals of cefixime as a caps
... Show MoreThe present study is to formulate and evaluate Acyclovir (ACV) microspheres using natural polymers like chitosan and sodium alginate. ACV is a DNA polymerase inhibitor used in treating herpes simplex virus infection and zoster varicella infections. Acyclovir is a suitable candidate for sustained-release (SR) administration as a result of its dosage regimen twice or thrice a day and relatively short plasma half-life (approximately 2 to 4 hours). Microspheres of ACV were prepared by an ionic dilution method using chitosan and sodium alginate as polymers. The prepared ACV microspheres were then subjected to FTIR, SEM, particle size, % yield, entrapment efficiency, in vitro dissolution studies and release kinetics mechanism. The FTI
... Show MoreThree cultivars of the crop Almash (Green Indian VC6089A10, Green Indian VC6173B1319, and Black Indian Gold Star) were tested in a field experiment during the 2022 growing season in Ramadi, Anbar province, to determine the impact of spraying levels of zinc (0, 25, and 50) mg Zn L-1 and manganese (0, 30, and 60) mg Mn L-1 on some growth characteristics. The experiment was conducted using a randomized complete block design (RCBD) with three replicates, with each treatment being tested in a separate split plot. The study found that there were statistically significant differences between zinc levels, with the level giving 50 mg Zn L-1
A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
Abstract
The study aimed: To assess the level of trainers' knowledge about the application of strategies and to find out the relationship between Trainer's knowledge and their socio-demographic characteristics.
Methodology: Using the pre-experimental design of the current study, for one group of 47 trainers working at the private Autism Centers in Baghdad, data was collected from 8/January / 2022 to 13 /February /2022. Using non-probability samples (convenient samples), self-management technology in which trainers fill out the questionnaire form themselves was used in the data collection process; it was analyzed through descriptive and inference statistics.
The data presented in this paper are related to the research article entitled “Novel dichloro(bis{2-[1-(4-methylphenyl)-1H-1,2,3-triazol-4-yl-κN3 ]pyridine-κN})metal(II) coordination compounds of seven transition metals (Mn, Fe, Co, Ni, Cu, Zn and Cd)” (Conradie et al., 2018) [1]. This paper presents characterization and structural data of the 2-(1-(4-methyl-phenyl)-1H-1,2,3-triazol-1-yl)pyridine ligand (L2 ) (Tawfiq et al., 2014) [2] as well as seven dichloro(bis{2- [1-(4-methylphenyl)-1H-1,2,3-triazol-4-yl-κN3 ]pyridine-κN})metal (II) coordination compounds, [M(L2 )2Cl2], all containing the same ligand but coordinated to different metal ions. The data illustrate the shift in IR, UV/VIS, and NMR (for diamagnetic complexes) peaks wh
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