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An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-cancerous cells to find the best combination of parameters in CNN to predict lung cancer accurately.  The proposed system recorded the highest accuracy of 92.79%. In addition to that, the paper addresses 192 observations made using the CNN model. 

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Tue May 16 2023
Journal Name
Political Sciences Journal
The Impact of Putinism on the Russian-Ukrainian Conflict: an analysis of the contents of the speeches of Russian President Vladimir Putin on the causes of the Russian war on Ukraine in 2022
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this research seeks to shed light on the study of the impact of Putinism on the Russian-Ukrainian war that broke out in early 2022, by studying the contents of the speeches of Russian President Vladimir Putin before the start of the war. This research uses the structural approach in analyzing the components of the Russian political regime. The research tools used in this research include case studies, content analysis of Russian speeches, and personal meetings of researchers and specialists in Russian affairs. It sums up a number of important conclusions, most notably are : 1) Putinism is a totalitarian regime that includes the political doctrine during the era of Russian President Vladimir Putin. 2) Duginism represents the totality of t

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Publication Date
Mon Jan 01 2018
Journal Name
Current Research In Microbiology And Biotechnology
Serodiagnosis of Human Cytomegalovirus in Iraqi Breast cancer and fibroadenoma patients
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Human cytomegalovirus (HCMV) has a worldwide distribution and extremely common infections. The presence of HCMV genome and antigens has been detected in many kinds of human cancers especially breast cancer. In Iraq, the incidence of breast cancer generally exceeds any other type of malignancies among Iraqi population. The study was performed in the period between October 2016 and June 2017 in Central public health laboratory/Baghdad. It involve samples from 90 women including 60 breast cancer patients, 20 benign tumor patients, and 10 normal breast tissues. A blood sample was obtained from each woman included in this study. Anti-HCMV IgG antibody was presented in 9/10 (90%) of normal women, benign breast tumor patients 19/20 (95%) and malig

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Publication Date
Wed May 22 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Assessment of Urine and Serum Exosomes as Biomarkers for the Diagnosis of Bladder Cancer
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Background: Bladder cancer (BC) is the most common malignant tumor in the urinary tract and the tenth most common malignancy worldwide. Exosomes are 40–100 nm-diameter nanovesicles that are either released straight from the plasma membrane during budding or merged with the plasma membrane by multivesicular bodies. Objectives: To assess the proportion of serum and urinary Exosome levels in urinary bladder cancer patients, as well as their impact on the disease. Methods: From January 2023 to June 2023, a total of 45 samples of blood and urine were collected from individuals diagnosed with bladder cancer at the Ghazi Hariri Hospital for Specialized Surgery. They included 45 male and female patients, varying in age, as well as 45 heal

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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Color Image Compression of Inter-Prediction Base
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Influential Relationship of Environmental Analysis Processes in the Organization's Development Strategy An exploratory study of the views of a sample of the leaders of the Iraqi Ministry of Interior
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The study aims at diagnosing the importance of environmental analysis (external, industrial and internal) in the organization's strategy for the development of public organizations. The theoretical problem derived from the existence of a knowledge gap for studies and research that dealt with the variables of the study. Three public organizations were selected as the study society (the Civil Defense Directorate, the Directorate of Nationality, Passports and Residency, the General Traffic Directorate). The sample of the study was a sample of (215) managers (managers, department managers, Analysis of the data and hypothesis testing using the appropriate statistical tools, Pearson, the simple and multiple regression coefficient to te

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Publication Date
Fri May 01 2026
Journal Name
2026 Xxix International Conference On Soft Computing And Measurements (scm)
Hierarchical Multi-Stage Intrusion Detection with Feature Inheritance and Prediction Verification
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One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad

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Publication Date
Sat Jun 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction and Correlations of Residual Entropy of Superheated Vapor for Pure Compounds
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Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one

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Publication Date
Mon Jun 30 2025
Journal Name
مجلة القادسية للقانون والعلوم السياسية
Insurance of Unlawful Risks: Towards a Reinterpretation of Public Policy in Light of the Protection of Innocent Victims and Freedom of Contract
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The issue of insurance against unlawful risks raises a jurisprudential and judicial debate between two opposing trends: the first considers coverage of these risks invalid due to their impact on public order or morals, while the second—which this research analyses—calls for the possibility of covering these risks in specific circumstances, based on contractual considerations in accordance with the principle that the contract is the law of the contracting parties, and based on the obligation to compensate the harmed third party—the victim—who has no connection to the unlawful act. In this context, our research highlights that contractual considerations can justify coverage of some unlawful risks, provided that the goal is to achieve

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Publication Date
Sat Apr 01 2023
Journal Name
Fluid Phase Equilibria
Prediction of solubility of vitamins in the mixed solvents using equation of state
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