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Path Planning and Obstacle Avoidance of a Mobile Robot based on GWO Algorithm
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planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the performance of the proposed algorithm. Simulations results showed that the proposed path planning algorithm effective performance by finding the shortest and free-collision path in different collide environments. Furthermore, the superiority of the proposed algorithm was proved through comparisons with other famous path planning algorithms with different static environments.

 

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Publication Date
Wed Sep 29 2021
Journal Name
Al-khwarizmi Engineering Journal
Simulation of a Self-Balancing Platform on the Mobile Car
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In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-deriva

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
Imagination as a Path to Reality
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Imagination as a Path to Reality

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Publication Date
Wed Jun 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Path-Tracking Based Multi-PID-PSO Controller Design
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Publication Date
Tue Feb 15 2022
Journal Name
مجلة جامعة الإمام جعفر الصادق ( عليه السلام) للعلوم الإنسانية والاجتماعية
Words of Elements and Natural Phenomena of Heavenly Nature in the Diwan of Muhammad Mustafa al-Mahi
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يدور هذا البحث حول جمع الالفاظ التي تتعلق بعناصر الطبيعة السماويّة وظواهرها في ديوان محمد مصطفى الماحيّ, وترتيبها في حقول دَلاليّة على وفق دراسة معجمية, تناولت فيها الالفاظ التي تتعلّق بعناصر الطبيعة السماويّة وظواهرها, فكان الهدف من هذه الدراسة هو دراسة الألفاظ التي ترتبط دَلالتها بمفهوم عام يجمعها حقل دلاليّ واحد كجمع الفاظ (السماء،والقمر، والبدر، والنجم، والكوكب), تحت مفهوم (عناصر السماوية وظواهرها الطب

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Research In Science And Technology
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

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Publication Date
Thu Jan 29 2026
Journal Name
Journal Of The College Of Languages
מסורת ומנהגים יהודי אירן ביצירותה של דורית רביניאן ( עיון ברומן סמטת השקדות בעומריג'אן " , Iranian Jews' Costoms and Traditions in the works of dorit Rabinya ( A Study Of The Persian Brids Novel)
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Publication Date
Thu Mar 14 2019
Journal Name
Al-khwarizmi Engineering Journal
Creeping Gait Analysis and Simulation of a Quadruped Robot
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A quadruped (four-legged) robot locomotion has the potential ability for using in different applications such as walking over soft and rough terrains and to grantee the mobility and flexibility. In general, quadruped robots have three main periodic gaits:  creeping gait, running gait and galloping gait. The main problem of the quadruped robot during walking is the needing to be statically stable for slow gaits such as creeping gait. The statically stable walking as a condition depends on the stability margins that calculated particularly for this gait. In this paper, the creeping gait sequence analysis of each leg step during the swing and fixed phases has been carried out. The calculation of the minimum stability margins depends up

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Sat Jul 08 2017
Journal Name
Neural Computing And Applications
A new algorithm of modified binary particle swarm optimization based on the Gustafson-Kessel for credit risk assessment
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