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Implementation and performance evaluation of multi level pseudo random sequence generator
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In this paper, introduce a proposed multi-level pseudo-random sequence generator (MLPN). Characterized by its flexibility in changing generated pseudo noise (PN) sequence according to a key between transmitter and receiver. Also, introduce derive of the mathematical model for the MLPN generator. This method is called multi-level because it uses more than PN sequence arranged as levels to generation the pseudo-random sequence. This work introduces a graphical method describe the data processing through MLPN generation. This MLPN sequence can be changed according to changing the key between transmitter and receiver. The MLPN provides different pseudo-random sequence lengths. This work provides the ability to implement MLPN practically in more than one method such as microcontroller or field programmable gate array (FPGA). In this paper discusses MLPN performance using MATLAB as compared with golden PN sequence generator with different modulation schemes such as binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), and quadrature amplitude modulation 16QAM. The simulation results show that MLPN performs almost likely golden PN sequence but sure with advantage its flexibility to change generated MLPN between transmitter and receiver. The MLPN sequence is applicable in the same field of PN sequence applications such as code division multiple access (CDMA), spread spectrum system (SSS), and data scrambling.

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Publication Date
Sun Apr 06 2014
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of cooperative learning in at the implementation of floral material for celli graph and decoration
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The purpose of this resesrh know (the effectiveness of cooperative lerarning implementation of floral material for calligraphy and ornamentation) To achieve the aim of the research scholar put the two zeros hypotheses: in light of the findings of the present research the researcher concluded a number of conclusions, including: -
1 - Sum strategy helps the learner to be positive in all the information and regulations, monitoring and evaluation during the learning process.
2 - This strategy helps the learner to use information and knowledge and their use in various educational positions, and to achieve better education to increase its ability to develop thinking skills and positive trends towards the article.
In light of this, the

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Random Dynamic Programming in Production Planning with Application in the midland Refineries Company
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Abstract

     This research deals with Building A probabilistic Linear programming model  representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution .              &

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Incidence of intestinal parasitic infections among random samples at Al- Aziziyah hospital in Wasit province/Iraq
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     The study is designed to identify intestinal parasitic infections examined at Al-Aziziyah Hospital in Wasit Governorate in Iraq. In this study, a total of (460) internal and external patients were monitored for intestinal parasitic infections. All stool samples were analyzed by the direct method (microscopic exam.) to discover the trophozoite stages and cyst stages for intestinal protozoan parasites. The most incidence parasites in different sex, area residence and different age groups. Out of (460) patient sample were infected with 217 at a percentage of (47.17%), 101(46.5%) were for males and 116 (53.5%) were for females. It was found that the numbers and percentages of a single (one

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Publication Date
Wed Jun 01 2022
Journal Name
Optik
High-purity narrow emission line display of titanium dioxide nanoparticles in laser dyes as random gains
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In this work, the dyes Rhodamine B and Coumarin 102 containing titanium dioxide nanoparticles were used as scattering centers to fabricate a random gain medium. The laser dye was dissolved in hexanol and methanol solvent respectively. The titanium dioxide nanoparticles were synthesized by DC reaction magnetron spraying technique. The random-gain medium was made by adding 2.5 mg of titanium dioxide nanoparticles to Rhodamine and coumarin 102 dyes by coating the glass cell with two-sided titanium dioxide with high spectral efficiency and low production cost. A narrow line optical emission was detected at 565 nm for Rhodamine B and 534 nm for coumarin 102, where it was found that rhodamine B dye has FWHM 8 nm and coumarin dye 102 has FWHM 9 nm

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Publication Date
Thu Dec 15 2011
Journal Name
Iraqi Journal Of Laser
Generation of Truly Random QPSK Signal Waveforms for Quantum Key Distribution Systems Based on Phase Coding
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In this work a model of a source generating truly random quadrature phase shift keying (QPSK) signal constellation required for quantum key distribution (QKD) system based on BB84 protocol using phase coding is implemented by using the software package OPTISYSTEM9. The randomness of the sequence generated is achieved by building an optical setup based on a weak laser source, beam splitters and single-photon avalanche photodiodes operating in Geiger mode. The random string obtained from the optical setup is used to generate the quadrature phase shift keying signal constellation required for phase coding in quantum key distribution system based on BB84 protocol with a bit rate of 2GHz/s.

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the Population Mean in Stratified Random Sampling Using Combined Regression with the Presence of Outliers
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In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Value of random urinary calcium to creatinine ratio in diagnosing hypercalciuria in children with nocturnal enuresis
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Background:Nocturnal Enuresis is a common problem affecting 20% of five years old children and up to 2% of adolescent and young adult. Although it is a self limiting benign condition, it has social and psychological impact on the child and his family. Many pathophysiological theories had been suggested, but none is confirmed. Hypercalciuria has been suggested to be associated with higher incidence of nocturnal enuresis. Objectives:The aim of our study to test the value of Ca/Cr ratio, on random urine sample, in diagnosing hypercalciuria in enuretic children. Type of study: Cross sectional study.Methods:Forty four enuretic children were enrolled in this study and forty five children without nocturnal enuresis were taken as control group.

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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