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A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
The Value of Diffusion Weighted MRI in the Detection and Localization of Prostate Cancer among a Sample of Iraqi Patients
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Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

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Publication Date
Sun Jun 23 2019
Journal Name
American Rock Mechanics Association
Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

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Publication Date
Tue Jan 01 2019
Journal Name
The 53rd U.s. Rock Mechanics/geomechanics Symposium
Using an analytical model to predict collapse volume during drilling: A case study from southern Iraq
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Publication Date
Wed Jan 01 2025
Journal Name
Transportation Engineering
Improving asphalt concrete durability through soda lignin powder
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Lignin has emerged as a promising asphalt binder modifier due to its sustainable and renewable nature, with the potential to improve flexible pavement performance. This study investigates the use of Soda Lignin Powder (SLP), derived from Pinus wood sawdust via alkaline treatment, as an asphalt modifier to enhance mixture durability. SLP was characterized using Fourier Transformation Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy with Energy Dispersive X-ray Analysis (SEM/EDX), revealing significant changes in its chemical structure post-extraction. These analyses showed the presence of phenolic units, including hydroxyphenyl propane, syringyl, and guaiacyl units. The morphology of SLP was identified

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Enhancing Privacy and Improving Security in Scalable Blockchain
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Bitcoin is a decentralized blockchain-based cryptocurrency that has taken the world by storm. Since its introduction in 2009, it has grown tremendously in terms of popularity and market cap. The idea of having a decentralized public ledger while maintaining anonymity and security attracted the attention of developers and customers alike. Special nodes in the bitcoin network, called miners, are responsible for making the network secure by using a concept called proof-of-work. A certain degree of anonymity is also maintained as no personally identifiable information of a person, like name, address, etc., is linked to the bitcoin wallet. In terms of bitcoin, a user is anonymous if different interactions of the user cannot be linked to

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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

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Publication Date
Mon Jun 15 2026
Journal Name
Biomedicines
EEG-ChTABNet: A Dual-Branch Channel-Wise Transformer with Gated Attention-Branch Network for EEG-Based Classification of Dementia
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Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

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Publication Date
Sat Jun 01 2024
Journal Name
Nasaq Journal
The Value of Collaborative Learning in Developing Student's Listening Skills
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Social interaction is the platform that enables people to connect and practice language. Active listening stimulates them to understand the language they are speaking. The problem of the study highlights that less attention to listening among speaking, reading, and writing skills causes the weakness of collaborative learning. This paper contributes to characterizing the effectiveness of collaborative learning in developing learner’s listening skills. It aims to underscore the role of target language learners as members of the learning groups and of the teacher in the collaborative learning process. 130 Iraqi EFL teachers from different colleges at the University of Baghdad participated in this study. The scores in the statistical data wer

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Publication Date
Thu Jan 01 2015
Journal Name
J. Math. Comput. Sci.
INTERVAL VALUE FUZZY n-FOLD KU-IDEALS OF KU-ALGEBRAS
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In this paper, we will introduce the concept of interval value fuzzy n-fold KU-ideal in KU-algebras, which is a generalization of interval value fuzzy KU-ideal of KU-algebras and we will obtain few properties that is similar to the properties of interval value fuzzy KU-ideal in KU-algebras, see [8]. Also, we construct some algorithms for folding theory applied to KU-ideals in KU-algebras.