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A comparison between PCA and some enhancement filters for denoising astronomical images
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This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-PCA method gives better performance, especially in image fine structure preservation, compared with other general denoising algorithms.

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Publication Date
Tue Oct 01 2024
Journal Name
Esic
Comparative Analysis of Economic Policy Stability between Monarchical and Republican Systems: A Theoretical Fundamental Research
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Comparative Analysis of Economic Policy Stability between Monarchical and Republican Systems: A Theoretical Fundamental Research

Publication Date
Mon Sep 30 2024
Journal Name
The Scientific World Journal
Relationship Between the Level of Vitamin D3 Deficiency and Successful Osseointegration: A Prospective Clinical Study
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Purpose: This study aimed to evaluate the influence of vitamin D3 levels on bone density, primary dental implant stability, and successful osseointegration.

Materials and Methods: Clinical and radiological examination with a standardized cone‐beam computed tomography (CBCT) machine and laboratory investigation for serum levels of vitamin D3 were performed for all patients. Only patients in need of single or multiple straightforward dental implant surgery in either jaw with no history of systemic disease or condition that may interfere with bone healing were included in this study to receive the dental implant by the same oral and maxillofacial surgeon, which re‐opened

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Publication Date
Mon Sep 30 2024
Journal Name
The Scientific World Journal
Relationship Between the Level of Vitamin D3 Deficiency and Successful Osseointegration: A Prospective Clinical Study
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Purpose: This study aimed to evaluate the influence of vitamin D3 levels on bone density, primary dental implant stability, and successful osseointegration.

Materials and Methods: Clinical and radiological examination with a standardized cone‐beam computed tomography (CBCT) machine and laboratory investigation for serum levels of vitamin D3 were performed for all patients. Only patients in need of single or multiple straightforward dental implant surgery in either jaw with no history of systemic disease or condition that may interfere with bone healing were included in this study to receive the dental implant by the same oral and maxillofacial surgeon, which re‐opened

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of The College Of Education For Women
Common Origin of Languages: A Comparative Study between the Holy Quran and the Heavenly Religions
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This research is a new reading of some of the words in the Holy Quran, which is very old. It is a human reading in which religions are intertwined by recognizing the relationship between man and his fellow man in the unity of existence and the unity of the source of religions and the unity of language. The importance of this research in comparing some of the Arabic words has been contained among books believed by followers that it is from the one God Sunday.

When words are spoken in one way in the form of one creature, from the beginning of creation to the present day, this indicates the single origin of the languages..

The research tools were books of heavenly religions, the Quran, dictionaries and interpretations.

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Serum Pseudocholinesterase as a Biomarker in the Differentiation between Gastric Cancer and Benign Gastric Diseases
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Background: Worldwide gastric cancer is the fifth most common cancer with poor prognosis. In early stages, it is hard to distinguish gastric cancer from benign gastric diseases, resulting in delayed diagnosis. There is a need to develop a biomarker for differentiating between gastric cancer and benign gastric diseases. Serum cholinesterase is synthesized in liver and released into plasma, and it has an important role in oncogenesis.

Objectives: To determine the correlation between serum cholinesterase activity and gastric cancer, in comparison to benign gastric diseases.

Subjects and Methods: A case control study carried out at Medical City Direct

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Publication Date
Tue Jan 01 2019
Journal Name
African Journal Of Hospitality, Tourism And Leisure
Employing marketing information systems for the success of small and medium enterprises: A field study of some Tourism and Travel companies in Baghdad
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some Estimation methods for the two models SPSEM and SPSAR for spatially dependent data
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ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

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