Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Porous silicon (PS) layers are prepared by anodization for
different etching current densities. The samples are then
characterized the nanocrystalline porous silicon layer by X-Ray
Diffraction (XRD), Atomic Force Microscopy (AFM), Fourier
Transform Infrared (FTIR). PS layers were formed on n-type Si
wafer. Anodized electrically with a 20, 30, 40, 50 and 60 mA/cm2
current density for fixed 10 min etching times. XRD confirms the
formation of porous silicon, the crystal size is reduced toward
nanometric scale of the face centered cubic structure, and peak
becomes a broader with increasing the current density. The AFM
investigation shows the sponge like structure of PS at the lower
current density porous begi

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Background: Platelet-rich fibrin (PRF) is a simple, low cost and minimally invasive way to obtain a natural concentration of autologous growth factors and is currently being widely experimented in different fields of medicine for its ability to aid the regeneration of tissue with a low healing potential. Fields of application are sports medicine, orthopedics, dentistry, dermatology, ophthalmology, plastic and maxillofacial surgery, etc. The rationale for using platelets in so many fields for the treatment of different tissues is because PLTs constitute a reservoir of critical GFs and cytokines, which may govern and regulate the tissue healing process that is quite similar in all kinds of tissues. Materials and Methods: Screw titanium implan

 Bored piles settlement behavior under vertical loaded is the main factor that affects the design requirements of single or group of piles in soft soils. The estimation of bored pile settlement is a complicated problem because it depends upon many factors which may include ground conditions, validation of bored pile design method through testing and validation of theoretical or numerical prediction of the settlement value. In this study, a prototype single and bored pile group model of arrangement (1*1, 1*2 and 2*2) for total length to diameter ratios (L/D) is 13.33 and clear spacing three times of diameter, subjected to vertical axial loads. The bored piles model used for the test was 2000

The research aims at the possibility of measuring the technical and scale efficiency (SE) of the departments of the College of Administration and Economics at the University of Baghdad for a period lasting 8 years, from the academic year 2013-2014 to 2018-2019 using the method of Applied Data Analysis with an input and output orientation to maintain the distinguished competitive position and try to identify weaknesses in performance and address them. Nevertheless, the research problem lies in diagnosing the most acceptable specializations in the labor market and determining the reasons for students’ reluctance to enter some departments. Furthermore, the (Win4DEAp) program was used to measure technical and scale efficiency (SE) and rely on

With growing global demand for hydrocarbons and decreasing conventional reserves, the gas industry is shifting its focus in the direction of unconventional reservoirs. Tight gas reservoirs have typically been deemed uneconomical due to their low permeability which is understood to be below 0.1mD, requiring advanced drilling techniques and stimulation to enhance hydrocarbons. However, the first step in determining the economic viability of the reservoir is to see how much gas is initially in place. Numerical simulation has been regarded across the industry as the most accurate form of gas estimation, however, is extremely costly and time consuming. The aim of this study is to provide a framework for a simple analytical method to esti

The study aims to identify the impact of competency-based training in its dimensions (skills, cognitive abilities, attitudes, and attitudes) in improving the performance of employees (achievement, strategic thinking and problem solving) in Jordanian university hospitals.

The study based on analytical descriptive method. The study population consisted of the Jordanian University Hospitals, the University Hospital of Jordan and the King Abdullah Hospital, as applied study case. The sample of the study consists of all upper and middle administrative employees of these hospitals; questionnaire distributed all of them and the number of valid questionnaires for analysis were 182 questionnaire.

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.