This research had been achieved to identify the image of the subsurface structure representing the Tertiary period in the Galabat Field northeast of Iraq using 2D seismic survey measurements. Synthetic seismograms of the Galabat-3 well were generated in order to identify and pick the reflectors in seismic sections. Structural Images were drawn in the time domain and then converted to the depth domain by using average velocities. Structurally, seismic sections illustrate these reflectors are affected by two reverse faults affected on the Jeribe Formation and the layers below with the increase in the density of the reverse faults in the northern division. The structural maps show Galabat field, which consists of longitudinal Asymmetrical narr

Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

تُعبّرُ الصُّورةُ الحسَّيةُ في شعرِ ابن دُنَينير الموصليِّ^([i]) في بنيتها عن تجربةِ الشاعرِ الوجدانيةِ والذهنيةِ, وأفكارهِ ومشاعرِهِ؛ فيصوغُ بها مَفهومًا جديدًا للواقعِ الماديِّ والمعنويِّ، الذي يتسمُ بالوضوحِ أولاً، وبالقرْبِ من الذهنِ ثانيًا، للربْطِ بين الحواسِّ الإنسانيةِ والمعاني الذهنيةِ، لِتُقَدِّمَ الصُّورةُ الحسيَّةُ إلى ((المتلقي صُورًا مرئيةً، يُعادُ تشكيلُها سياق

This research is a result of other studies made about the iraqi public and its relationship with different states institutions, until recently, such studies were almost non-existent. The main characteristic that distinguishes scientific research is that it involves a specific problem that needs to be studied and analysed from multiple aspects. What is meant by identifying the problem, is to limit the topic to what the researcher wants to deal with, rather than what the title suggests as topics which the researcher doesn’t want to deal with. The problem of this research is the absence of thoughtful and planned scientific programs to build a positive mental image of the institutions of the modern state in general and the House of Represe

ABSTRACT

Metal (II) complexes of Co, Ni, Cu and Zn with cefdinir C₁₄H₁₃N₅O₅S₂ derivative (L) were synthesized and identification by elemental analysis CHNS Uv-Vis, FTIR, TGA, metal analysis AA, magnetic susceptibility and conduct metric measurement. by analysis the ligand behaves as a bidentate. For the cobalt complex, Tetrahedral geometry shape was suggested, while other complexes that have nickel, copper and zinc ions were proposed as octahedral geometry shape. The experimental method was studied for prevention of corrosion carbon steel in 3.5% NaCl by using a novel Cefdinir derivations drugs. The results showed that metal complex was a strong corro

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification