The performance of a diesel engine was tested with diesel oil contaminated with glycol at the engineering workshop/Department of Agricultural Machines and Equipment / College of the Agricultural Engineering Sciences at the University of Baghdad. To investigate the impact of different concentrations of glycol on the performance of a diesel engine, an experimental water-cooled four-stroke motor was utilized, with oil containing 0, 100, and 200 parts per million (ppm). Specific fuel consumption, thermal efficiency, friction power, and exhaust gas temperature were examined as performance indicators. To compare the significance of the treatments, the study employed a full randomization design (CRD), with three replicates for each treatment at th

 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

Wellbore stability is considered as one of the most challenges during drilling wells due to the
reactivity of shale with drilling fluids. During drilling wells in North Rumaila, Tanuma shale is
represented as one of the most abnormal formations. Sloughing, caving, and cementing problems
as a result of the drilling fluid interaction with the formation are considered as the most important
problem during drilling wells. In this study, an attempt to solve this problem was done, by
improving the shale stability by adding additives to the drilling fluid. Water-based mud (WBM)
and polymer mud were used with different additives. Three concentrations 0.5, 1, 5 and 10 wt. %
for five types of additives (CaCl2, NaCl, Na2S

      Manganese-zinc ferrite Mn_xZn_1-xFe₂O₄ (MnZnF) powder was prepared using the sol-gel method. The morphological, structural, and magnetic properties of MnZnF powder were studied using X-ray diffraction (XRD), atomic force microscopy (AFM), energy dispersive X-ray (EDX), field emission-scanning electron microscopes (FE-SEM), and vibrating sample magnetometers (VSM). The XRD results showed that the MnxZn1-xFe2O4 that was formed had a trigonal crystalline structure. AFM results showed that the average diameter of Manganese-Zinc Ferrite is 55.35 nm, indicating that the sample has a nanostructure dimension. The EDX spectrum revealed the presence of transition metals (Mn, Fe, Zn, and O) in Mang

A simple, cheap, fast, accurate, Safety and sensitive spectrophotometric method for the determination of sulfamethaxazole (SFMx), in pure form and pharmaceutical dosage forms. has been described The Method is based on the diazotization of the drug by sodium nitrite in acidic medium at 5Cº followed by coupling with salbutamol sulphate (SBS) drug to form orange color the product was stabilized and measured at 452 nm Beer’s law is obeyed in the concentration range of 2.5-87.5 ?g ml-1 with molar absorptivity of 2.5x104 L mole-1 cm-1. All variables including the reagent concentration, reaction time, color stability period, and sulfamethaxazole /salbutamol ratio were studied in order to optimize the reaction conditions. No interferences were

Electrochemical method was used to prepare carbon quantum dots (CQDs). Size of matter was nature when evaluate via X-ray diffraction (XRD). A distinct peak at 2θ equal to 31.6° and three other small peaks at 38.28°, 56.41° and 66.12° were observed. The measures of Fourier Transform Infrared Spectroscopy (FTIR) showed the bonds in the transmittance spectrum are manufactured with carbon nanostructures in view. The first peaks are the O–H stretching vibration bands at (3417 and 2922) cm−1, (C–O–H at 1400, and 1317) cm−1, (C–H), (C=C), (C–O–H), (C=O), and (C–O) bonds at 2850, 1668, 1101, and 1026 cm−1 sequentially. The transmission electron microscopy (TEM) results presented that the spherical CQDs are in shape and on a

The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina