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A Cognition Path Planning with a Nonlinear Controller Design for Wheeled Mobile Robot Based on an Intelligent Algorithm
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This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated reference path as well as it has obtained a perfect torque control action without spikes and no saturation torque state that leads to minimize the tracking error for the wheeled mobile robot.

 

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Early marriage for the minors: a phenomenon of family violence against children
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It is certain that marriage has the favor of the continuity of human kind since the Prophet Adam till now. But this important event is threatened by some justifications which lead to its delay or abandonment. In the West, sexual relations, illegal friendships, and disrespect of marriage sacredness lead to this delay. While the reasons behind the delay of marriage in the Arab world refer to high dowries, women go out to work, and the religious and scientific ignorance of the need and importance of marriage. The problem also differs according to the difference between the rural and urban regions. On one hand, we find that early marriage is a necessity in the rural regions; on the other hand, the delay of marriage is a clear and nat

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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
A Fixed Point Theorem for L-Contraction in Generalized D-Metric Spaces
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We define L-contraction mapping in the setting of D-metric spaces analogous to L-contraction mappings [1] in complete metric spaces. Also, give a definition for general D- matric spaces.And then prove the existence of fixed point for more general class of mappings in generalized D-metric spaces.

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Publication Date
Tue Jan 01 2019
Journal Name
Iop
Water cut comparison for a really similar gridding system (line drive pattern)
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Proposed Management System for Construction Practices during Sustainable Buildings Life Cycle
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For many years, the construction industry damages have been overlooked such as unreasonable consumption of resources in addition to producing a lot of construction waste but with global awareness growth towards the sustainable development issues, the sustainable construction practices have been adopted, taking into account the environment and human safety. The research aims to propose a management system for construction practices which could be adopted during constructing different types of sustainable buildings besides formulating flowcharts which clarify the required whole phases of sustainable buildings life cycle. The research includes two parts: theoretical part which generally ,handles the sustainability concepts at construction i

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Publication Date
Fri Sep 01 2017
Journal Name
International Research Journal Of Engineering And Technology
A POWERFUL AUTOMATED IMAGE INDEXING AND RETRIEVAL TOOL FOR SOCIAL MEDIA Sample
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The Internet image retrieval is an interesting task that needs efforts from image processing and relationship structure analysis. In this paper, has been proposed compressed method when you need to send more than a photo via the internet based on image retrieval. First, face detection is implemented based on local binary patterns. The background is notice based on matching global self-similarities and compared it with the rest of the image backgrounds. The propose algorithm are link the gap between the present image indexing technology, developed in the pixel domain, and the fact that an increasing number of images stored on the computer are previously compressed by JPEG at the source. The similar images are found and send a few images inst

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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of The College Of Education For Women
(A Message in Nile) For Ahmed هbn Imad ibn Yusuf al-Aqfhasi
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Ahmed ibn Imad ibn Yusuf al-Aqfhasi (808 AH / 1405 AD) is a small message that speaks about the Nile River in all its sides, despite its limited papers, but it is one of the manuscripts of the important geographical literature for its geographical, historical, religious and grammatical information. it was not limited to the information of the author alore, but taken from many sources below, which added to the importance of the fact that it has saved us the names of the sources that preceded him in mentioning this river with the names of its authors.The method of the Aqfhasi was characterized by scientific methodology in writing and clarity, with reference to some of the myths that people carried in their minds about the Nile River at tha

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Publication Date
Sat Aug 01 2015
Journal Name
Modern Applied Science
A New Method for Detecting Cerebral Tissues Abnormality in Magnetic Resonance Images
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We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

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Publication Date
Sat Jun 01 2024
Journal Name
Alexandria Engineering Journal
U-Net for genomic sequencing: A novel approach to DNA sequence classification
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Hybrid Method of Linguistic and Statistical Features for Arabic Sentiment Analysis
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          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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