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An Improved Adaptive Spiral Dynamic Algorithm for Global Optimization
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This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF) algorithm is designed so that the chemotaxis phase of bacteria represents the exploration part of the search operation. In contrast, the SDA represents the exploitation part.

Additionally, to improve search operation efficiency, the spiral model's radius and angular displacement are adaptively set according to a linear correlation concerning the fitness value. An additional phase, the elimination and dispersal phase, is obtained from BFA and added to the end of the SDA. This phase aims to improve the algorithm's final solution's accuracy by enhancing the algorithm's search strategy and performance. Simulation tests are run on unimodal and multimodal standard benchmark functions to verify the proposed algorithm. The proposed algorithm significantly outperforms SDA and Adaptive SDA (ASDA) algorithms regarding fitness value and accuracy.

 

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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 Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Efficient approach for solving high order (2+1)D-differential equation
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Wed Mar 01 2023
Journal Name
Ecological Engineering & Environmental Technology
Environmental Impact Assessment for Industrial Organizations Using Rapid Impact Assessment Matrix
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Publication Date
Fri May 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
A review of ultra-high temperature materials for thermal protection system
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Abstract<p>Ultra-High Temperature Materials (UHTMs) are at the base of entire aerospace industry; these high stable materials at temperatures exceeding 1600 °C are used to manage the heat shielding to protect vehicles and probes during the hypersonic flight through reentry trajectory against aerodynamic heating and reducing plasma surface interaction. Those materials are also recognized as Thermal Protection System Materials (TPSMs). The structural materials used during the high-temperature oxidizing environment are mainly limited to SiC, oxide ceramics, and composites. In addition to that, silicon-based ceramic has a maximum-use at 1700 °C approximately; as it is an active oxidation process o</p> ... Show More
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Publication Date
Wed Dec 06 2017
Journal Name
International Journal Of Science And Research (ijsr)
The Conceptual Mathematical Knowledge and Analytical Thinking for the First Stage Students at Math Sciences Department, Faculty of Education for Pure Sciences, IBN Alhaithem, University of Baghdad
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Publication Date
Wed May 28 2025
Journal Name
Retos
The effect of exercises in the third intensity zone of the strength characteristic of speed for the legs on some physiological and biochemical indicators for handball players
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Objective: preparing exercises for the third intensity zone for strength and speed for the legs, and identifying their effect on some physiological and biochemical indicators for (the level of lactic acid concentration, the concentration of sodium bicarbonate, the concentration level of (potassium K+) and (sodium Na+) in the blood, and the number of breathing times (RF) Research methodology: the experimental research method was adopted by designing the experimental and control groups on a sample of Army Sports Club players amounting to (16) players, deliberately selected (100%) from their community using a comprehensive enumeration method, and then divided into two groups of equal number, After determining the tests for physiologica

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Publication Date
Mon May 25 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Training for Anaerobic Differential Threshold Stand and its Impact on Lactic Acid Concentration and LDH Enzyme and VO2MaX and Cortisol Hormone for Free 400 m men-runners
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The study aimed at designing a training program by using training for the anaerobic differential threshold stand and the effects of those trainings on the variables of (Concentration of Lactic Acid and LDH Enzyme, VO2 MaX and Cortisol Hormone). The Researchers used the experimental program with one-group style. Also, they used a sample with (8) men-players in a (free 400 m men-runners) and they used many instruments and procedures, most notably the training-program prepared for 10 weeks and for 3 training units weekly, (70-90 min) for each unit. They used the training intensity from 85-100% of the player's ability. After finishing the training program and doing some pre-tests and post-tests then statistically checking the results, the resea

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Publication Date
Mon Dec 21 2020
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MONITORING OF THE WILD MAMMAL FAUNA IN BAMO MOUNTAIN IN NORTHERN IRAQ (KURDISTAN) FOR THE FIRST TIME USING CAMERA TRAP METHOD AND RAISING AWARENESS FOR ITS CONSERVATION
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Mammals are under threat worldwide due to deforestation, hunting, and other human activities. In Iraq, a total of 93 species of wild mammals have been recorded including species with global conservation concern. Bamo Mountain is situated within the Zagros Mountains in northern Iraq which is a suitable habitat for wild mammals. Due to scarcity of the field survey efforts and cryptic behavior, monitoring of the wild mammals fauna in Zagros Mountain seems challenging. Therefore, we used a camera trap which seems to be an ideal way to determine species diversity of wild mammals in Bamo Mountain. Moreover, interviews with local villagers were performed. The mammalian diversity of Bamo Mountain is not fully explored but seemed threatened by lo

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Suggested Technique for Creating Physical Growth Curves Charts for Anthropometric Measurements in Admixed form in a sample of children under two years of age In Diyala Governorate
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Objective: This study aimed to assessing new suggested technique of Physical Growth Curves (PGC) charts in
children under two years old of a non-probability sample.
Methodology: A non-probability sample of size (420) children under two years selected from 12 Primary
Health Care Centers in Diyala governorate during the period from 15th Nov. 2010 to 13th Mar. 2011
according to admix of a different properties together in one chart/or growth curve chart included in at least
weight, Height, and Head circumference.
Results: the results showed different properties that can be admix together in one chart/or growth curve
chart included in at least weight, Height, and Head circumference. And to overtake the problem of the norm

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