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Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint repulsive force and the off-sensors attractive force. These secondary forces and modified primary forces are merged to overcomethe drawbacks like dead ends and U shape traps. The proposed algorithm acquirs information of unknown environment by collecting the readings of five infrared sensors with detecting range of 0.8 m. The proposed algorithm is applied on two different environments also it is compared with another algorithm. The simulation and experimental results confirm that the proposed algorithm always converges to the desired target. In addition, the performance of algorithm is well and meets the requirements in terms of saved time and computational resources.

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Publication Date
Fri May 28 2021
Journal Name
Journal Of Microbiology And Biotechnology
Bioactive Levan-Type Exopolysaccharide Produced by <i>Pantoea agglomerans</i> ZMR7: Characterization and Optimization for Enhanced Production
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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
An Enhanced Document Source Identification System for Printer Forensic Applications based on the Boosted Quantum KNN Classifier
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

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Publication Date
Sat Jan 12 2013
Journal Name
Pierb
RADAR SENSING FEATURING BICONICAL ANTENNA AND ENHANCED DELAY AND SUM ALGORITHM FOR EARLY-STAGE BREAST CANCER DETECTION
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A biconical antenna has been developed for ultra-wideband sensing. A wide impedance bandwidth of around 115% at bandwidth 3.73-14 GHz is achieved which shows that the proposed antenna exhibits a fairly sensitive sensor for microwave medical imaging applications. The sensor and instrumentation is used together with an improved version of delay and sum image reconstruction algorithm on both fatty and glandular breast phantoms. The relatively new imaging set-up provides robust reconstruction of complex permittivity profiles especially in glandular phantoms, producing results that are well matched to the geometries and composition of the tissues. Respectively, the signal-to-clutter and the signal-to-mean ratios of the improved method are consis

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Testing the cytotoxic potential of biosynthesized nanoparticles using Conocarpus erectus Leaves against human breast cancer cells
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Sliding mode control based on high-order extended state observer for flexible joint robot under time-varying disturbance
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Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Online 3D path planning for Tri-copter drone using GWO-IBA algorithm
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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Mon Sep 01 2014
Journal Name
Engineering And Technology Journal
Analysis of the Capacity, Spectral Efficiency and Probability of Outage of Adaptive Mobile Channel for WiMAX System
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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of Time of Survival Rate by Using Clayton Function for the Exponential Distribution with Practical Application
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Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho

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