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Access Control Security Review: Concepts and Models
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HS Saeed, SS Abdul-Jabbar, SG Mohammed, EA Abed, HS Ibrahem, Solid State Technology, 2020

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Publication Date
Wed Jun 26 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
VSM Based Models and Integration of Exact and Fuzzy Similarity For Improving Detection of External Textual Plagiarism admin June 29, 2019
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Publication Date
Thu Jul 20 2023
Journal Name
Polymers In Medicine
Effect of subinhibitory doses of rifaximin on in vitro Pseudomonas aeruginosa adherence and biofilm formation to biotic and abiotic surface models
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Crossref
Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

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Crossref
Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Use special Erwa to determine the number of live bacteria in different models
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Used in the study especially calibrated Erwa to determine the number of neighborhood or the Alayoshi number of bacteria in the count modeling and casting method dishes in addition to using the drop method yielded significant results for a match between the methods used ..

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Limits between the Cosmological Parameters from Strong Lensing Observations for Generalized Isothermal Models
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This paper including a gravitational lens time delays study for a general family of lensing potentials, the popular singular isothermal elliptical potential (SIEP), and singular isothermal elliptical density distribution (SIED) but allows general angular structure. At first section there is an introduction for the selected observations from the gravitationally lensed systems. Then section two shows that the time delays for singular isothermal elliptical potential (SIEP) and singular isothermal elliptical density distributions (SIED) have a remarkably simple and elegant form, and that the result for Hubble constant estimations actually holds for a general family of potentials by combining the analytic results with data for the time dela

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Crossref
Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Particle Swarm Algorithm to Solve Queuing Models with Practical Application
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This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six  employees , and it was chosen queuing model is a single-service channel  M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and  it was composed of data collection times (arrival time , service time, departure time)

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Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Wormholes Models for the Optimum Matrix Acidizing in Mi4 Unit-Ahdeb Oil Field
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Innovative laboratory research and fluid breakthroughs have improved carbonate matrix stimulation technology in the recent decade. Since oil and gas wells are stimulated often to increase output and maximum recovery, this has resulted in matrix acidizing is a less costly alternative to hydraulic fracturing; therefore, it is widely employed because of its low cost and the fact that it may restore damaged wells to their previous productivity and give extra production capacity. Limestone acidizing in the Mishrif reservoir has never been investigated; hence research revealed fresh insights into this process. Many reports have stated that the Ahdeb oil field's Mishrif reservoir has been unable to be stimulated due to high inj

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Crossref
Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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