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An Evolutionary Algorithm With Heuristic Operator for Detecting Protein Complexes in Protein Interaction Networks With Negative Controls
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Using the Elzaki decomposition method to solve nonlinear fractional differential equations with the Caputo-Fabrizio fractional operator
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The techniques of fractional calculus are applied successfully in many branches of science and engineering, one of the techniques is the Elzaki Adomian decomposition method (EADM), which researchers did not study with the fractional derivative of Caputo Fabrizio. This work aims to study the Elzaki Adomian decomposition method (EADM) to solve fractional differential equations with the Caputo-Fabrizio derivative. We presented the algorithm of this method with the CF operator and discussed its convergence by using the method of the Cauchy series then, the method has applied to solve Burger, heat-like, and, couped Burger equations with the Caputo -Fabrizio operator. To conclude the method was convergent and effective for solving this type of

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Applying Social Stories in Developing Social Interaction Skills among Children with Autism Spectrum Disorder
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Abstract

The current research aims to identify the effectiveness of social stories in increasing social interaction among children with an autism spectrum disorder. The researcher used the single-subject design methodology (Single Subject Designs, SSD) with

 (A-B) design to answer the research questions. The study sample consisted of (3) children with autism spectrum disorder enrolled in a transit daycare center in the Asir region, Saudi Arabia. The results of the study showed that there is a positive functional relationship between social stories and play to increase social interaction among children with autism spectrum disorder, which contributed to the acquisition and generalization of this behav

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Constructional Steel Research
Demountable steel-concrete composite beam with full-interaction and low degree of shear connection
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It is suitable to use precast steel-concrete composite beams to quickly assemble a bridge or a building, particularly in isolated regions where cast-in-situ concrete is not a practical option. If steel-concrete composite beams are designed to allow demountability, they can also be extremely useful in the aftermath of natural disasters, such as earthquakes or flooding, to replace damaged infrastructure. Furthermore, rapid replacement of slabs is extremely beneficial in case of severe deterioration due to long-term stressors such as fatigue or corrosion. The only way to rapidly assemble and disassemble a steel-concrete composite structure is to use demountable shear connectors to connect/disconnect the steel beams to/from the concrete slab. I

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Wed Apr 01 2020
Journal Name
Biochemical & Cellular Archives
INVESTIGATION OF VITAMIN D, ESTRADIOL AND C-REACTIVE PROTEIN LEVELS IN PRE AND POST-MENOPAUSAL IRAQI TYPE 2 DIABETES MELLITUS IN WOMEN.
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Diabetes mellitus is a metabolic chronic disease, with global estimation increase in patient (around 100 million in 2030).The aim of the current study is to investigate vitamin D, C-reactive protein and estradiol levels in pre and postmenopausal Iraqi women with type 2 diabetes (T2MD).A total of 176 female distributed into two groups: the first included 90 women withT2MD (43 pre and 47 post-menopausal); the second group included 86 healthy subjects (41 pre and 45 postmenopausal) considered as control. This study has shown that women in premenopausal (20-40 years) had highly significant difference in the estradiol and vitamin D levels in diabetes subjects (62.192 ± 17.643pg/ml, 10.522 ± 1.958ng/ml) compared with healthy (131.793 ± 1

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Sun Nov 12 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Indirect lmunofluorescent Antibody Test for Detecting Chlamydial Infection
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A total of 243 serum samples  were tested  for the presence of

Chlamydia antibodies by ind irect immunofluorescent antibody test.Ninety

nine females were suffering from abortions, 64 were infertile and other 80 were  none  aborted  women.  The  incidence of  Ch lamydia  were  (15%,

9.4%)   and   (3.8%)   in  abortion,   infertile   and   non   aborted   group,

respecti vely.  The  results  also  showed  a difference  in  prevalence rate between the age groups. The  highest  incidence was found  in the age group  20-39 &

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Publication Date
Sat Dec 31 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE : PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE
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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

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Publication Date
Wed Nov 16 2016
Journal Name
Eurasip Journal On Wireless Communications And Networking
Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm
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Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

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