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Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is implemented based on hybrid Crossoved Firefly Algorithm with Artificial Bee Colony (CFA-ABC) to tune the controller's parameters to achieve the optimal path. The performance of the hybrid optimization algorithm is verified by various benchmark functions. The simulation results show that the utilizing of CFA and (CFA-ABC ) are better than the original Firefly Algorithm. A simulation example is given to indicate the effectiveness of the proposed algorithm, the results have been done using MATLAB (R2013b), and all trajectory tracking results with two reference trajectories (circular and lemniscates ) are presented.

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Publication Date
Tue Sep 09 2025
Journal Name
Nursing Science Quarterly
Artificial Intelligence in Nursing: Toward a Global Perspective
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The use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of

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Publication Date
Fri Jan 16 2026
Journal Name
F1000research
Update Quasi-Newton Algorithm for Training ANN
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The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
Spatial contrast of the slums in the unity of the new municipal of Baghdad
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The slums one of the main problem plaguing the city of Baghdad in general and
the unity of municipality of New Baghdad, especially, where the characteristics of the study
area a prominent role in population growth and the emergence of slums where a private,
although the region suffer from the housing crisis is the lack of the number of housing units
compared to the number of families in which, With high land prices and the level of rent
which was accompanied by the absence of the law, which was followed by the year 2003, has
become the study area and one of the most municipalities of the city of Baghdad Contain
slums which took fills abandoned buildings and acquires vacant land agricultural ones and
allocated to d

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Publication Date
Tue Dec 30 2025
Journal Name
Alnahrain Journal Of Legal Scienci
Elements and Conditions of Personal Civil Liability (Based on Fault) for the Government for Damages Caused by Demonstrations: A Comparative Study
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This study examines the position of comparative legislation (French legislation, English legislation, and Egyptian legislation) in addressing the regulation of personal civil liability (based on fault) for the government. About the damages caused by demonstrations in terms of their legal nature, their legal basis, and the pillars and conditions of that responsibility. Then, we explain the position of the Iraqi legislator and compare it with what is the case in the legislation mentioned above

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Outdoor Testing of a Zig-Zag Solar Air heater with and without Artificial Roughness on Absorber Plate
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In this paper, thermal performance of a zig-zig solar air heater (ZZSAH) with and without using steel wire mesh on the absorber plate of the collector is experimentally investigated. The experimental work includes four inclination angles of the collector 20o, 30o, 45o, and 60o and four air mass flow rates of 0.03, 0.04, 0.06, and 0.08 kg/s under varieties of operating conditions of a geographic location of  Baghdad. New correlation equations of Nusselt number are obtained from experimental results for both types of collectors where the effect of varying of the inclination angle of collector taken into consideration in the experiment. The correlations show good agreement wi

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Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
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Publication Date
Mon Jan 01 2018
Journal Name
Internet And Distributed Computing Systems
A Proposed Adaptive Rate Algorithm to Administrate the Video Buffer Occupancy for Smooth Video Streaming
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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