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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
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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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
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

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Publication Date
Mon Oct 27 2025
Journal Name
Journal Of Education College
Photographing the Arab heritage and its impact on Hebrew literature Comparative analysis study
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
تحلیل محادثة منتدى: نص مختار من مجلة بول كیمب الالكترونیة: تحلیل محادثة منتدى: نص مختار من مجلة بول كیمب الالكترونیة
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الخلاصة:
ان المحادثة كانت الشغل الشاغل لكثیر من العلماء المھتمین بدراستھم بھذا المجال من امثال ساكس
.( واخرون ( ١٩٧٤ ) وغرایس ( ١٩٧٥ ) و شكلوف و اخرون ( ١٩٧٧ ) و دانكن ( ١٩٧٢ ) و بیرتن ( ١٩٨٠
قدمت بیرتن ( ١٩٨٠ ) تحلیلا لمسرحیة النادل الابكم لغرض تقدیم طریقتھا. تتوخى الباحثة من
تقدیم ھذا البحث تحلیل تركیب المحادثة منتدى حول القصة الادبیة و القصة الروائیة باستعمال نموذج بیرتن
١٩٨٠ ). و یمیل البحث الى الاجابة عن ا

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
A discoursal analysis of the plot unity in one- act play
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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Scopus (10)
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Publication Date
Tue Apr 09 2019
Journal Name
Journal Of The College Of Education For Women
The Role of Civil Society Institutions for the Care of Young People in Iraq ( Possibilities and constraints): A Field Study from the Point of view of University Students
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Besides the role of state institutions that come in the forefront of their priorities and obligations to provide security and development of the economy and reduce the unemployment rate and the reduction of inflation and improving education, health and others, the Community Partnership At frames what has become known as the institutions of society civil-with the state does not eliminate the role, but rather complements its role ; it is the role of civil society partner and an extension of the role of the state in the face of challenges and crises, but it may be sometimes a race role in addressing social, political and economic issues of the role played by the state, not complementary.
The highlighting the specificity of the relationsh

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