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U-Net for genomic sequencing: A novel approach to DNA sequence classification
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences into BRAC, BRAF, and KRAS categories. Our comprehensive methodology includes rigorous data preprocessing, model training, and a multi-faceted evaluation approach. The adapted U-Net model exhibited exceptional performance, achieving an overall accuracy of 0.96. The model also achieved high precision and recall rates across the classes, with precision ranging from 0.93 to 1.00 and recall between 0.95 and 0.97 for the key markers BRAC, BRAF, and KRAS. The F1-score for these critical markers ranged from 0.95 to 0.98. These empirical results substantiate the architecture’s capability to capture local and global features in DNA sequences, affirming its applicability for critical, sequence-based bioinformatics challenges

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Classification of Iraqi Children According to Their Nutritional Status Using Fuzzy Logic
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In this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Tue Oct 04 2022
Journal Name
International Journal Of Dentistry
Comparison between Rolled and Nonrolled U-Shaped Flap in the Second Stage of Dental Implant Surgery: A Randomized Clinical Trial
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Background. The presence of black triangles around the dental implant-supported prosthesis and the failure to construct adequate papillae around them bothers dental implantologists. Peri-implant surgical soft tissue management will improve esthetics, function, and implant survival. Aim. To compare the effects of rolled and nonrolled U-shaped flaps combined with a temporary crown in enhancing the soft tissue around dental implants. Materials and Methods. Forty patients were included in this study; all patients were operated on by the same maxillofacial surgeon at Al-Iraq specialized dental clinics from January 2019 to January 2020. Patients were divided randomly into two groups: group A: at the second stage of implant surgery, a U-sh

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Paleoenvironments and Sequence Stratigraphy of the Turonian-Lower Campanian Succession at Majnoon Oil Field, Southern Iraq
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The Turonian-Lower Companian succession at Majnoon Oil Field is represented by the Khasib, Tanuma, and Saadi formations. Four major paleoenvironments were recognized within the studied succession, there are: Shallow open marine environment, shoal environment, deep marine environment, and basinal environment. They reflect deposition on a carbonate platform of homoclinal ramp setting. The studied succession represents two second order supersequences (A) and (B). Supersequence (A) includes both the Khasib and Tanuma formations. The Saadi Formation represents cycle (B). These second order cycles can be divided each into two third order cycles, This subdivision may reflect the effect of eustacy being the major controlling factor of cycles dev

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
New Approach in Detection MAC Spoofing in a WiFi LAN
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Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

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Publication Date
Fri Feb 26 2021
Journal Name
Life-cycle Civil Engineering: Innovation, Theory And Practice
Shear performance of a novel demountable connector for reusable steel-concrete composite structures
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A novel demountable shear connector is proposed to link a concrete slab to steel sections in a way that resulting steel-concrete composite floor is demountable, i.e. it can be easily dismantled at the end of its service life. The proposed connectors consist of two parts: the first part is a hollow steel tube with internal threads at its lower end. The second part is a compatible partially threaded bolted stud. After linking the stud to the steel section, the hollow steel tube can be fastened over the threaded stud, which create a complete demountable shear connector. The connector is suitable for use in both composite bridges and buildings, and using cast in-situ slabs, precast solid slabs, or hollow-core precast slabs. A series of push-off

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Publication Date
Wed Mar 25 2015
Journal Name
Comptes Rendus Chimie
A novel method for the synthesis of biodiesel from soybean oil and urea
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The increasing demand for energy has encouraged the development of renewable resources and environmentally benign fuel such as biodiesel. In this study, ethyl fatty esters (EFEs), a major component of biodiesel fuel, were synthesized from soybean oil using sodium ethoxide as a catalyst. By-products were glycerol and difatty acyl urea (DFAU), which has biological characteristics, as antibiotics and antifungal medications. Both EFEs and DFAU have been characterized using Fourier transform infrared (FTIR) spectroscopy, and 1H nuclear magnetic resonance (NMR) technique. The optimum conditions were studied as a function of reaction time, reactant molar ratios, catalyst percentage and the effect of organic solvents. The conversion ratio of soybea

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Publication Date
Fri Nov 24 2023
Journal Name
International Journal Of Statistics In Medical Research
A Novel Algorithm for Predicting Antimicrobial Resistance in Unequal Groups of Bacterial Isolates
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Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Thu Jun 01 2023
Journal Name
Electronics
Downlink Training Sequence Design Based on Waterfilling Solution for Low-Latency FDD Massive MIMO Communications Systems
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Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for

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