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Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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Publication Date
Sun Apr 01 2012
Journal Name
Journal Of Educational And Psychological Researches
Family Atmosphere and Relationship to Academic Adjustment for Student at Baghdad University
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The research aimed: 1. Definition of family climate for the university students. 2. Definition of statistical significance of differences in family climate variable depending on the sex (males - females) and specialization (Scientific - humanity). 3. Definition of academic adjustment for university students. 4. Definition of correlation between climate and academic adjustment. The research sample formed of (300) male and female students by (150) male of scientific and humanitarian specialization and (150) female of scientific and humanitarian specialization randomly selected from the research community. To achieve the objectives of the research the researcher prepared a tool to measure family climate. And adopted the measure (Azzam 2010)

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
Analytical Study of the Content of Social and National Studies Textbooks of the Middle Stage in Kingdom of Saudi Arabia in the Light of the Values of Social Peace
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This study aimed to reveal the extent to which the values of social peace are included in the content of social and national studies textbooks of the middle stage in kingdom of Saudi Arabia. To achieve this goal, the researcher used the descriptive analytical approach. The study sample consisted of all developed social and national studies textbooks of the middle stage in kingdom of Saudi Arabia in first and second semester of student books in edition of 1439-1440. The study tool was the analysis card. The study reached the following results: 1-The content of social and national studies textbooks of the middle stage in kingdom of Saudi Arabia as a whole included (38) social peace values of total (40) values, corresponding to the inclusio

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering & Science (iconmeas 2019)
New application of pervaporation to enhance the conversion of consecutive reaction
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This study investigates consecutive reaction assisted by pervaporation for the first time. It studies the saponification of diethyladipate DA with sodium hydroxide NaOH solution synchronous with separating ethanol from the reaction mixture through an aqueous – organic membrane. The effect of time on some variables such as: permeated ethanol concentration EtOH wt%, separation factor (α), concentration of NaOH solution CB in the reaction medium and the conversion of DA to monoethyladipate (the intermediate product) was studied. It was shown that EtOH wt% and the conversion increased with increasing time unlike CB but (α) showed the existence of maximum value during the time of experiment. The process of reaction assisted by pervaporation

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Publication Date
Tue Apr 11 2023
Journal Name
Sensors
EEG Signal Complexity Measurements to Enhance BCI-Based Stroke Patients’ Rehabilitation
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The second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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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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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Prediction of bearing capacity, angle of internal friction, cohesion, and plasticity index using ANN (case study of Baghdad, Iraq)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Scopus (9)
Scopus
Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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