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Diabetes Diagnosis Using Deep Learning
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     Hyperglycemia is a complication of diabetes (high blood sugar). This condition causes biochemical alterations in the cells of the body, which may lead to structural and functional problems throughout the body, including the eye. Diabetes retinopathy (DR) is a type of retinal degeneration induced by long-term diabetes that may lead to blindness. propose our deep learning method for the early detection of retinopathy using an efficient net B1 model and using the APTOS 2019 dataset. we used the Gaussian filter as one of the most significant image-processing algorithms. It recognizes edges in the dataset and reduces superfluous noise. We will enlarge the retina picture to 224×224 (the Efficient Net B1 standard) and utilize data augmentation methods to enhance the dataset photographs, and balance the dataset (which was quite uneven), to avoid overfitting. By using Transfer learning we save training time by using a previously learned deep CNN and transfer learning weights. In this research, EfficientNetB1 is compared against Xception, InceptionV3, MobileNet, and ResNet50 as a deep transfer learning model. The proposed model's accuracy, precision, recall, and f1-score are all examined. The EfficientNetB1 model outperforms all others in terms of overall testing accuracy (86.1%), sensitivity (87.24%), precision (97.6%), and F1-Score (89.32 percent). This approach might help physicians diagnose Diabetic Retinopathy earlier.

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Effect of Successive Convolution Layers to Detect Gender
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Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Spectrophotometric Determination of Micro Amount of Chromium (III) Using Sodium 4-((4,5-diphenyl-imidazol-2-yl)diazenyl)-3-hydroxynaphthalene-1-sulfonate in the Presence of Surfactant, Study of Thermodynamic Functions and Their Analytical Applications
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          Using sodium4-((4,5-diphenyl-imidazol-2-yl)diazenyl)-3-hydroxynaphthalene-1-sulfonate (SDPIHN) as a chromogenic reagent in presence of non-ionic surfactant (Triton x-100) to estimate the chromium(III)  ion if the wavelength of this reagent 463 nm to form a dark greenish-brown complex in wavelength 586 nm at pH=10,the complex was stable for longer than 24 hours. Beer's low, molar absorptivity 0.244×104L.mol-1.cm-1, and Sandal's sensitivity 0.021 µg/cm2 are all observed in the concentration range 1-11 µg/mL. The limits of detection (LOD) and limit of quantification (LOQ), respectively, were 0.117 µg/mL and 0.385µg/mL. (mole ratio technique, job's method) were employed to

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Publication Date
Mon Jan 13 2025
Journal Name
Al.qadisiya Journal For The Sciences Of Physical Education
The Influence of Using Special Exercises with Weights to Develop Moments of Force to Some of the Striking Shoulder and Arm Muscles and Accuracy of the Skill of the Smash and Rectum in Volleyball
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This research is an attempt to develop exercise with weights to strengthen some of the striking muscles in the shoulder and arm and to develop the accuracy of the smash and rectum skills. The importance of this paper lies in the study of moments of force to achieve the ability to control muscular work and to explore the impact of physical and skill exercises with weights to develop moments of force for some muscles. The experimental method on a sample of players, selected according to the intentional method, including ( 9) advanced players representing Air Force Club participating in the Premier League for season 2011-2012. It is concluded that the exercises proposed have their effective impact on developing the variables of moments force f

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Publication Date
Mon Jan 01 2018
Journal Name
Al–bahith Al–a'alami
Using Social Media sites by the Iraqi women and the Achieved The Use of Iraqi Women of Social Networking Sites and the Satisfactions Generated from Them.: A Survey Study of the City of Baghdad
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The problem of this research lies in the fact that there is a lack of accurate scientific perceptions about the size of the use of Iraqi women’s social networking sites and the motives behind this use and the expectations generated by them.
The goals of the research are as follows:
1- Determine the extent of Iraqi women’s use of social networking sites (Facebook, YouTube, twitter, and Instagram).
2- Investigative the motives behind the use of social networking sites by Iraqi women.
3- Detecting the repercussions of Iraqi women’s use of social networking sites (Facebook, you tube, twitter, and Instagram).
The research is classified as a descriptive one. The researchers use the survey methodology. The research commu

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Publication Date
Mon May 15 2023
Journal Name
Iraqi Journal Of Science
Determination of hydrogen peroxide in some local pharmaceutical disinfectants by continuous flow injection analysis via turbidimetric (T180o) and scattered light effect at two opposite positions (2N90o ) using Ayah 4SW-3D-T180o -2N90o -Solar - CFI Analyse
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An indirectly method is used to determine hydrogen peroxide. The method based on oxidation of chromium (III) ion by hydrogen peroxide in basic medium to form chromate ion which react with barium (II) ion to produce a yellow precipitate (BaCrO4). Under the optimum established conditions, the linear range of 0.50-25.00 mmol L-1 along with correlation coefficient (r) of 0.9992, Limit of detection (LOD) 0.68 μg / 100 μL, precision expressed as relative standard deviation for six replication measurements at 5.0 mmol.L-1 H2O2 of less than 2% were obtained for hydrogen peroxide. The developed method was successfully applied for the estimation of H2O2 in three pharmaceuticals preparation of different companies using continuous flow injection o

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Publication Date
Wed Nov 27 2019
Journal Name
Iraqi Journal Of Science
An Improved Segmentation Technique for Early Detection of Exudates of Diabetic Retinopathy Disease
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Diabetic retinopathy (DR) is a diabetes- caused disease that is associated with  leakage of fluid from the blood vessels into the retina, leading to its damage. It is one of the most common diseases that can lead to weak vision and even blindness. Exudates is a clear indication of diabetic retinopathy, which is the main cause of blindness in people with diabetes. Therefore, early detection of exudates is a crucial and essential step to prevent blindness and vision loss is in the analysis of digital diabetic retinopathy systems. This paper presents an improved approach for detection of exudates in retina image using supervised-unsupervised Minimum Distance (MD) segmentation method. The suggested system includes three stages; First, a

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Publication Date
Sat Dec 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Molecular Cloning of large DNA Fragments of The Sal t Tolerant wild Tetra ploid bermudagrass Cynodon Dactylon L. Using A Bacteriophage Cloning Vector 2. Ligation a nd in vitro packaging of The Recombinant Phage DNA Molecules
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This  paper represent  the second  step  i n  a molecular clon i ng program ai ming to clone large DNA  fi·agmen ts of the sal t tolerant  bermudagrass (Cyrwdon  dactylon  L.)  DNA  usi ng  the  bacteriophage  (EM13L3) as    a vector.

In th is  work, a yield of about  I 00  g bacteriophage  DNA  per one  liter culture.was obtained  with.a  purity ranging between (1.7-1.8). The vector JJNA  v.as  completely   double   digested   with  the  restriction   enzymes llamHI   and  EcoRI,  followed  by  pu

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Publication Date
Tue Jan 01 2013
Journal Name
Journal Of Geochemical Exploration
Geochemical exploration using surveys of spring water, hydrocarbon and gas seepage, and geobotany for determining the surface extension of Abu-Jir Fault Zone in Iraq: A new way for determining geometrical shapes of computational simulation models
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Intelligent System for Multi-Layer Lip Reading Based Microlearning
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     Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo

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