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Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation Evaluation for Nasiriyah Oil Field Based on The Non-Conventional Techniques
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The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:

  • Apparent resistivity Rwa
  • Rxo /Rt

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Strategic Intelligence on the Process of Green Manufacturing An Explorative Study for the Managers Opinions of Sample of Mineral water factories at Dahuk
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         The studying trying to determine the role of  Strategic Intelligence on the Process of Green Manufacturing  of  Sample of Mineral water factories at Dahuk city.  The study submit a theoretical frame of Strategic Intelligence and Green Manufacturing, a supposed sample, had been set to reverye   the nature of the relations and effect in the study  Varity, the study  depend on group of the main and branch concurring with the relations and effect between the Strategic Intelligence and Green Manufacturing to answer the following questions about research to problems:

 What are the relationships and effects between stra

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Forgiveness and its relation to the social intelligence among elementary school students
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The study aims to identify the relationship between forgiveness and social intelligence among elementary school students. The study employed a descriptive analytical approach, whereby a total of (500) elementary school student were selected randomly regarding the variable of gender and economical status. Two scales were prepared: one to measure the forgiveness depending on Albort’s theory that consist of (20) item, and the other to measure the social intelligence according to Tony’s theory which composed of (20) item as well. The result revealed that 6th grade students have interested level of the forgiveness and social intelligence, the girl showed significant differences according to the forgiveness variable, the sample

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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