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The modeling techniques of the second‐order correlation function <i>g</i> <sup>(2)</sup> ( <i>τ</i> ) for a quantum emitter
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Publication Date
Sun Feb 20 2022
Journal Name
Egyptian Journal Of Chemistry
Simulation of the remediation of groundwater contaminated with ciprofloxacin using grafted concrete demolition wastes by ATPES as reactive material: Batch and modeling study
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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
Fri Jul 18 2014
Journal Name
International Journal Of Computer Applications
3-Level Techniques Comparison based Image Recognition
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Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

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Publication Date
Thu Oct 18 2018
Journal Name
Al–bahith Al–a'alami
Modalities and Methodological Techniques in Media Studies
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There have been many writings and discussions that dealt with the details and interpretation of the research methods and the identification of the methods and methodological methods used by researchers and writers as they deal with research topics and problems in all fields of natural and human sciences. But we noticed that the movement of science and its knowledge and development requires the identification of suitable tools and methodological methods appropriate for each type of science. In other words, attempts should be established to build appropriate methodological tools for human and cognitive activity that can be referred to as a specific science that sets out certain paths of the human sciences which is certainly the ori

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Urban Morphological Studies (Concepts, Techniques, and Methods)
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Urban morphological approach (concepts and practices) plays a significant role in forming our cities not only in terms of theoretical perspective but also in how to practice and experience the urban form structures over time. Urban morphology has been focused on studying the processes of formation and transformation of urban form based on its historical development. The main purpose of this study is to explore and describe the existing literature of this approach and thus aiming to summarize the most important studies that put into understanding the city form. In this regard, there were three schools of urban morphological studies, namely: the British, the Italian, and the French School. A reflective comparison between t

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Publication Date
Wed Dec 04 2024
Journal Name
F1000research
Correlation between plasma homocysteine and ischemic heart disease in young Adults
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Background Cardiovascular disease (CVD) is a leading cause of death worldwide. Ischemic heart disease is a major cause of morbidity and mortality. Lack of blood supply to the brain can cause tissue death if any of the cerebral veins, carotid arteries, or vertebral arteries are blocked. An ischemic stroke describes this type of event. One of the byproducts of methionine metabolism, the demethylation of methionine, is homocysteine, an amino acid that contains sulfur. During myocardial ischemia, the plasma level of homocysteine (Hcy) increases and plays a role in many methylation processes. Hyperhomocysteinemia has only recently been recognized as a major contributor to the increased risk of cardiovascular disease (CVD) owing to its eff

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Correlation between malondialdehyde and metanephrine in patients with acute lymphoblastic leukemia
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Acute lymphoblastic leukemia (ALL) is one of the most common diseases , so in this study the serum level of malondialdehyde and its relationship with metanephrine was investigated in acute lymphoblastic leukemia patients over one month of treatment. Some biochemical parameters (serum glucose , total serum protein , malondialdehyde ,vitamin C, and metanephrine) changed as well as white blood cell count and blood hemoglobinlevelswere analyzed in sixty patients diagnosed with acute lymphoblastic leukemia over one month of treatment compared to healthy control group.Statistically significant increases (p<0.01) in white blood cell (WBC) count, mean concentrations of malondialdehyde (MDA) (p< 0.05) and metanephrine (p< 0.001) were observed in

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Correlation between Serum and Tissue Markers in Breast Cancer Iraqi Patients
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Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor.  The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and

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