Pore pressure means the pressure of the fluid filling the pore space of formations. When pore pressure is higher than hydrostatic pressure, it is named abnormal pore pressure or overpressure. When abnormal pressure occurred leads to many severe problems such as well kick, blowout during the drilling, then, prediction of this pressure is crucially essential to reduce cost and to avoid drilling problems that happened during drilling when this pressure occurred. The purpose of this paper is the determination of pore pressure in all layers, including the three formations (Yamama, Suliay, and Gotnia) in a deep exploration oil well in West Qurna field specifically well no. WQ-15 in the south of Iraq. In this study, a new appro

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin

Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is

Abstract:

Objectives: The present study aims to evaluate effectiveness of educational program the nurses' knowledge towards early prediction of acquired weakness in the intensive care unit.

Methodology: A pre-experimental study design (comparison of two groups), which was achieved through the pre and post-test method for the study sample through the application of an educational program in the intensive care unit of Al-Zahra Teaching Hospital in Kut city, Wasit Governorate. The study was conducted for the period from 28^th April 2022 to 15^th August 2022 by selecting a purposive (non-probability) sample for this study. The study sample size was (52) nu

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The Capparis spinosa L. is a species has a great interest in the field of traditional medicine for its pharmacological properties with many bioactive compounds. Our study is aiming at the recovery of this species through a phytochemical analysis and an evaluation of antibacterial and antioxidant activities of leaves of Capparis spinosa L. collected from natural habitats within the region of Al-Jadriya, Baghdad, Iraq. Phytochemical investigation demonstrated the presence of flavonoids, phenols, alkaloids, tannins, and glycosides in the methanolic extract of leaves. The quantitative analysis of total phenolic contents is being performed by Folin-Ciocalteau method and expressed in terms of gallic acid equivalents. C. spinosa exhibited progress

In this paper, a new 5G Passive Optical Network (5G-PON) employing all-optical orthogonal frequency division multiplexing (AO-OFDM) is proposed in hybrid bidirectional standard single mode fiber (SSMF)/free space optical (FSO). Additionally, an optical frequency generator (OFG) source is utilized. The proposed model is simulated using VPI photonics software. Analytical modeling and simulations have been conducted for a new approach to generate OFG by cascaded two-frequency modulators and one electro-absorption modulator. A sinusoidal RF signal source is utilized to drive all these modulators. The results reveal that 64 optical multiplexed carriers with a frequency spacing of 30 GHz are generated. These optical carriers have power variations

An approach for hiding information has been proposed for securing information using Slanlet transform and the T-codes. Same as the wavelet transform the Slantlet transform is better in compression signal and good time localization signal compression than the conventional transforms like (DCT) discrete cosine transforms. The proposed method provides efficient security, because the original secret image is encrypted before embedding in order to build a robust system that is no attacker can defeat it. Some of the well known fidelity measures like (PSNR and AR) were used to measure the quality of the Steganography image and the image after extracted. The results show that the stego-image is closed related to the cover image, with (PSNR) Peak Si