Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

The study is aimed at social support to the students of the College of Education for women (The research sample) and measuring the quality of life at students of the College of Education for women (The research sample) And to identify the relationship between social support and quality of life of students of the College Education for Women and research sample consisted of 200 students The adoption of the resolution as a tool for data collection and the most important results of the search results that the students of the College Education for Women have social support. In other words, parents and friends are supporting the students. The students have the quality of life any positive meaning to life and that when a person has a quality of

Background: Imprelon® Biostar foils are new alternative tray material that has become increasingly popular because oftheir several advantages. Also, (Duran®) is another type of Biostar foils which is used in splint therapy. This study assessed some mechanical properties of these two types Biostar sheets in comparison with some types of acrylic resins used for construction of trays and splints. Materials and Methods: A total of 150 specimens were prepared, 30 specimens for each test, 10 for each group material in order to assess some mechanical properties of the Imprelon® Biostar foil (dimension stability, surface roughness and shear bond strength of Imprelon® materialto zinc oxide impression material) and compare them to that of the oth

This study was carried out to evaluate parasitological and immunological of the effect of chitosan and chitosannanoparticles loaded with spiramycin on toxoplasmosis infected mice. After injection intra peritoneal with 103viable tachyzoites for acute infection, treatments given for seven days. Peritoneal fluid examination revealed a significant decrease in the number of Toxoplasmagondiitachyzoites in all treated infected mice compared with infected non-treated. The combined therapy gave better results than single. The best effect was observed in group of mice treated with spiramycin combined with chitosan nanoparticles. Also immunoglobulin Ig Manti body and gamma Interferon (INFγ), Tumor Necrosis Factor alpha (TNF-α) cytokines responses ag

The induced photodegradation of methyl cellulose (MC) films in air was investigated in the absence and presence of aromatic carbonyl compounds(photosenssitizers): 1,4-naphthaquinone (NQ) and benzophenone (BPH) by accelerated weathering tester. The addition of (0.01 wt %) of low molecular weight aromatic carbonyl compounds to cellulose derivatives films(25µm in thickness) enhanced the photodegradation of the polymer films.The photodegradation rate was measured by the increase in carbonyl absorbance. Decreases in solution viscosity and reduction of molecular weight were also observed in the irradiated samples. Changes in the number-average chain scission, the degree of deterioration and in the quantum yield of chain scission values are als

This study was conducted during the spring season of 2023-2024 and the fall season of 2024-2025 at the fields of the College of Agricultural Engineering Sciences, University of Baghdad, to investigate effects of irrigation intervals I1 ,I2 (3 and 6 days) , soil amendment with zeolite at three concentrations Z0 ,Z1,Z2 (0, 4, and 8 g. kg soil⁻¹), and foliar spraying with kaolin for three concentrations C0,C1,C2 (0, 0.5, and 1 g .L⁻¹). The results revealed that the treatment I1Z2C2 ​ significantly excelled in leaf area, chlorophyll concentrations, and yield for both seasons, achieving 31.0 dm², 21.5 mg per 100 g fresh weight, and 1984.7 g in the first season, and 34.08 dm², 23.6 mg per 100 g fresh weight, and 2526.3 g in the

Arabic calligraphy is one of the ancient arts rooted in history, And that he grew up conflicting views and writings addressed as a, communication tool for the linguistic The teaching calligraphy note an art and science because it depends on the fixed assets and precise rules in his art because centered Beauty It targets teach Arabic calligraphy speed as the education and recitation helps to write fast Which have great interest in the field of education and in life both Also accompanied Arabic calligraphy and scientific renaissance significant knowledge in the Ara

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

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