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bsj-1049
Automatic Block Selection for Synthesizing Texture Images using Genetic Algorithms
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Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.

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Publication Date
Thu Feb 15 2024
Journal Name
Evolving Systems
Boosted Aquila Arithmetic Optimization Algorithm for multi-level thresholding image segmentation
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Publication Date
Thu May 15 2014
Journal Name
Monthly Notices Of The Royal Astronomical Society
Gravitational lensing in WDM cosmologies: the cross-section for giant arcs
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The nature of the dark sector of the Universe remains one of the outstanding problems in modern cosmology, with the search for new observational probes guiding the development of the next generation of observational facilities. Clues come from tension between the predictions from Λ cold dark matter (ΛCDM) and observations of gravitationally lensed galaxies. Previous studies showed that galaxy clusters in the ΛCDM are not strong enough to reproduce the observed number of lensed arcs. This work aims to constrain the warm dark matter (WDM) cosmologies by means of the lensing efficiency of galaxy clusters drawn from these alternative models. The lensing characteristics of two samples of simulated clusters in the Λ warm dark matter and ΛCDM

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System
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 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Sat Oct 08 2016
Journal Name
Methods In Molecular Biology
Production of Adjuvant-Loaded Biodegradable Particles for Use in Cancer Vaccines
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Publication Date
Wed Nov 17 2021
Journal Name
International Journal Of Knowledge Management
Assessing the Success of the Perceived Usefulness for Knowledge Management Systems
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Recently, Knowledge Management Systems (KMS) consider one of the major fields of study in educational institutions, caused by the necessity to identify their knowledge value and success. Hence, based on the updated DeLone and McLean’s Information Systems Success Model (DMISSM), this study set out to assess the success of the Perceived Usefulness of Knowledge Management Systems (PUKMS) in Iraqi universities. To achieve this objective, the quantitative method is selected as the research design. In total, 421 university administration staff members from 13 Iraqi private universities were conducted. This study highlights a number of significant results depending on structural equation modeling which confirms that system, information, and s

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Publication Date
Tue Jun 18 2024
Journal Name
2024 Ieee 33rd International Symposium On Industrial Electronics (isie)
An Adaptive Integral Sliding Mode Control for Disturbed Servo Motor Systems
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Abstract-Servo motors are important parts of industry automation due to their several advantages such as cost and energy efficiency, simple design, and flexibility. However, the position control of the servo motor is a difficult task because of different factors of external disturbances, nonlinearities, and uncertainties. To tackle these challenges, an adaptive integral sliding mode control (AISMC) is proposed, in which a novel bidirectional adaptive law is constructed to reduce the control chattering. The proposed control has three steps to be designed. Firstly, a full-order integral sliding manifold is designed to improve the servo motor position tracking performance, in which the reaching phase is eliminated to achieve the invariance of

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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Evaluation of FEMM software for magnetic analysis of the magnetorheological application
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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Materials Science: Materials In Electronics
Fabrication and characterization of CoxMn0.25−xMg0.75Fe2O4 nanoparticles for H2S sensing applications
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