The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Objectives To compare the clinical efficacy of microvascular decompression surgery (MVD) and gamma knife radiosurgery (GKR) as a treatment for patients with primary trigeminal neuralgia (TN) and evaluate the outcome regarding pain relief, recurrence, and complications with both modalities of treatment. Patients and Methods A randomized prospective study conducted in SaadAlwitry Neurosciences Hospital, Baghdad, Iraq. Eighty-four patients with TN from January 2016 to January 2018, 45 patients had GKR while 39 patients treated with MVD. The pain evaluated pre-and post-operatively using the Barrow Neurological Institute Pain Intensity scale (BNIPI), visual analog scale (VAS) and Brief Pain Inventory Facial (BPI-Facial) scoring systems. In GKR p

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

In this work, the effect of preparing a composite of copper oxide nanoparticles with carbon on some of its optical properties was studied. The composite preparing process was carried out by exploding graphite electrodes in an aqueous suspension of copper oxide. The properties of the plasma which is formed during the explosion were studied using emission spectroscopy in order to determine the most important elements that are present in the media. The electron’s density and their energy, which is the main factor in the composite process, were determined. The particle properties were studied before and after the exploding process. The XRD showed an additional peak in the copper oxides pattern corresponding to the hexagonal graphite struct

Adsorption of Chlorophenol compounds in aqueous solution on Iraqi siliceouns rocks powder have been investigated. UV technique has been used to determine the adsorption isotherms. The results showed that the adsorption isotherms obeyed Freundlich adsorption equation. The adsorption was endothermic process, increasing temperature leads to increasing adsorption.  H,  S,  G were calculated. The results showed that the adsorption increases with increasing acidity of solutions

This study focused on treatment of real wastewater rejected from leather industry in Al-Nahrawan city in Iraq by Electrocoagulation (EC) process followed by Reverse Osmosis (RO) process. The successive treatment was applied due to high concentration of Cr3+ ions (about 1600 ppm) rejected in wastewater of this industry and for applying EC with moderate power consumption and better results of produced water. In Electrocoagulation process (EC), the effect of NaCl concentration (1.5, 3 g/l), current density (C.D.) (15-25 mA/cm2), electrolysis time (1-2 h), and distance between electrodes (E.D.) (1-2 cm) were examined in a batch cell by implementing Taguchi experimental design. According to the results obtained from multiple regression and signa

Background: A great dental and biomedical interest had been paid to silver nanoparticles because of their antimicrobial activity. Objective: To evaluate the antimicrobial and cytotoxic activity of a newly developed Nano-silver fluoride that was synthesized from moringa oleifera leaf extract against S. mutants.  Material and method: The green synthesis method was used to prepare Nano-silver fluoride from moringa oleifera leaf extract. The minimum inhibitory concentration and the minimum bactericidal concentration were evaluated using brain heart infusion plates, while the cytotoxicity was evaluated by the hemolytic activity. Results: Nano-silver fluoride had a bactericidal and bacteriostatic effect (MIC was 60 ppm and MBC was 120 pp

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob