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Nurse Scheduling Problem Using Hybrid Simulated Annealing Algorithm
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Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Simulated annealing algorithm (SA),  35.7% for Improved Simulated annealing (SA*), 26.25% for Genetic algorithm ( GA) and 45.6% for Improved Genetic algorithm for all problems (2000 problems).                                                                                                 

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Publication Date
Sun Feb 26 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Study the Effect of Annealing Temperature on the Structural, Optical and Electrical Properties of ZnS Thin Films
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The structural, optical and electrical properties of ZnS films prepared by vacuum evaporation technique on glass substrate at room temperature and treated at different annealing temperatures (323, 373, 423)K of thickness (0.5)µm have been studied. The structure of these films is determined by X-ray diffraction (XRD). The X-ray diffraction studies show that the structure is polycrystalline with cubic structure, and there are strong peaks at the direction (111). The optical properties investigated which include the absorbance and transmittance spectra, energy band gab, absorption coefficient, and other optical constants. The results showed that films have direct optical transition. The optical band gab was found to be in the range t

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Publication Date
Wed May 01 2019
Journal Name
Thin Solid Films
Studies of annealing impact on the morphological, opto-dielectric and mechanical behaviors of molybdenum-doped CrN coatings
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Publication Date
Thu May 04 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Annealing on the Physical Properties of Silver Selenide Thin Film at Different Temperatures by Thermal Evaporation
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This survey investigates the thermal evaporation of Ag2Se on glass substrates at various thermal annealing temperatures (300, 348, 398, and 448) °K. To ascertain the effect of annealing temperature on the structural, surface morphology, and optical properties of Ag2Se films, investigations and research were carried out. The crystal structure of the film was described by Xray diffraction and other methods.The physical structure and characteristics of the Ag2Se thin films were examined using X-ray and atomic force microscopy (AFM) based techniques. The Ag2Se films surface morphology was examined by AFM techniques; the investigation gave average diameter, surface roughness, and grain size mutation values with increasing annealing temperature

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Publication Date
Mon Oct 01 2012
Journal Name
Iraqi Journal Of Physics
Effects of copper doping and annealing on the structure and optical properties of ZnxCdx-1S thin films
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Effect of copper doping and thermal annealing on the structural and optical properties of Zn0.5Cd0.5S thin films prepared by chemical spray pyrolysis have been studied. Depositions were done at 250°C on glass substrate. The structural properties and surface morphology of deposited films were studied using X-ray diffraction (XRD) and photomicroscope (PHM) techniques. XRD studies reveal that all films are crystalline tetragonal structure. The film crystallinity are increased with 1% Cu-doping concentration and also increased for the films annealed at 300°C than the other studied cases. The lattice constant 'a' and 'c' varies with doping concentrations from 5.487Å to 5.427Å and 10.871Å to 10.757Å respectively. The grain size attained

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Publication Date
Sat Jan 01 2011
Journal Name
Trends In Network And Communications
Header Compression Scheme over Hybrid Satellite-WiMAX Network
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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
Wed Feb 01 2023
Journal Name
International Journal Of Engineering, Ije Transactions B: Applications
Adaptive Polynomial Coding of Multi-Base Hybrid Compression
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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Hybrid LDPC-STBC communications system based on chaos
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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Hybrid Controller for a Single Flexible Link Manipulator
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In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra

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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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