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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
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
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
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Ciphered Text Hiding in an Image using RSA algorithm
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In this paper, a method for hiding cipher text in an image file is introduced . The
proposed method is to hide the cipher text message in the frequency domain of the image.
This method contained two phases: the first is embedding phase and the second is extraction
phase. In the embedding phase the image is transformed from time domain to frequency
domain using discrete wavelet decomposition technique (Haar). The text message encrypted
using RSA algorithm; then Least Significant Bit (LSB) algorithm used to hide secret message
in high frequency. The proposed method is tested in different images and showed success in
hiding information according to the Peak Signal to Noise Ratio (PSNR) measure of the the
original ima

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Publication Date
Wed Jul 24 2024
Journal Name
Journal Of Plant Protection Research
Developing smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model
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The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys

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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
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
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
Thu Jul 21 2022
Journal Name
International Journal Of Health Sciences
Effect of transglutaminase on mechanical and barrier properties of edible films made from soybeen and why protein isolate
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This study was aimed to study the effect of adding transglutaminase (TGase) on the mechanical and reservation properties of the edible films manufactured from soybean meal protein isolate (SPI) and whey protein isolate(WPI). The results showed an improvement in the properties with increase in the WPI ratios. Thickness of the SPI films amounted 0.097 mm decreased to 0.096 mm for the WPI: SPI films at a ratio of 2:1, when TGase was added decreased to 0.075 mm. While the tensile strength increased from 7.64 MPa for SPI films to eight MPa for the WPI: SPI films at a ratio of 2:1, when TGase was added increased to 11.04 MPa. Also, the elongation of the WPI: SPI films at a ratio of 2:1 presence of the TGase decreased to 40.6% compared wit

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