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On mildly-regular space
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In this paper mildly-regular topological space was introduced via the concept of mildly g-open sets. Many properties of mildly - regular space are investigated and the interactions between mildly-regular space and certain types of topological spaces are considered. Also the concept of strong mildly-regular space was introduced and a main theorem on this space was proved.

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Publication Date
Wed Aug 17 2022
Journal Name
Aip Conference Proceedings
Remove phenolic pollutant on Bentonite surface nanopowder
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Publication Date
Sat Dec 30 2023
Journal Name
Al-kindy College Medical Journal
Effect of Palmaris Longus on Handwriting Skills
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Background: Kinesiologists, Physical Anthropologists, and Anatomists have all long been captivated by the structure and development of the superficial forearm flexor, the Palmaris longus.

Objective: To study the effect of Palmaris Longus on certain handwriting skills.

Subjects and Methods: Three Palmaris Longus occurrence tests were conducted on 200 students (100 males and 100 females) affiliated to Colleges of Medicine of Baghdad University then the participants were tested for certain handwriting skills to correlate the presence of Palmaris Longus in the dominant side with handwriting.

Results: 89% of all subject

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Effect of uncontrolled dewatering on adjacent building
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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Image Compression based on Quadtree and Polynomial
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Publication Date
Thu Nov 13 2025
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Interdisciplinary Mathematics
On Tˉ-pure sub-acts over moniods
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The notion of a Tˉ-pure sub-act and so Tˉ-pure sub-act relative to sub-act are introduced. Some properties of these concepts have been studied.

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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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Publication Date
Sun Mar 01 2009
Journal Name
The Third International Conference Of The College Of Science –university Of Baghdad
On Maximal solution of nonlinear operator equation
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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