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Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is consider better. For this purpose the  study used real data. The results show the (DRBLTS) estimators are more accuracy than other.

 

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Publication Date
Wed Oct 12 2022
Journal Name
Axioms
Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
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Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

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Publication Date
Sun Dec 01 2019
Journal Name
Applied Soft Computing
A new evolutionary multi-objective community mining algorithm for signed networks
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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Sat Jul 25 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An Evaluation of Olive Oil as a Separating Medium and Its Effect on Some Mechanical Properties of Processed Acrylic Resin Denture Base (A Comparative Study). Part Two
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Background: During acrylic resin processing, the mold must be separated from the surface of the gypsum to prevent liquid resin from penetrating into the gypsum, and water from the gypsum seeping into the acrylic resin. For many years, tin foil was the most acceptable separating medium, and because it's difficult to apply, a tin-foil substitute is used. In this study, olive oil is used as an alternative to tin foil separating medium for first time, and evaluating its effect as a separating medium on some mechanical properties such as (indentation hardness and transverse strength) of acrylic resins denture base comparing it with those processed using tin-foil and tin foil substitute such as (cold mold seal) separating medium. Materials and M

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Tue Sep 28 2021
Journal Name
Journal Of The College Of Education For Women
Social Safety Nets and Sustainable Development in Fragile Environments: A Field Social Study of Slums in the City of Baghdad/Al-Karkh: هبة صالح مهدي, عدنان ياسين مصطفى
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Almost human societies are not void of poverty, as the latter accompanied the emergence of humanity, and it, thus, represents an eternal problem. To advance an individual's reality and raise the level of the poor social classes, social security networks have been established. Such networks operate in society following social systems and laws to provide food, and material support. Besides, such networks help to rehabilitate the individual academically and vocationally. They empower vulnerable groups through the establishment of courses and workshop, provide (conditional) subsidies related to the health and educational aspects in order to achieve the sustainable development goals of (2030), and apply developmental roles of social safety ne

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Publication Date
Tue Jan 10 2012
Journal Name
Iraqi Journal Of Community Medicine
Evaluation of physical parameters in mitral valve stenosis by using Doppler Ultrasound
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Background: Mitral valve stenosis is a condition in which the hearts mitral valve is narrowed (stenosis), This narrowing blocks the valve from opening properly obstructing blood flow through the heart and the rest of the body and this causes changes in physical parameters (resistance and conductance). Aim of the study: To assess the changes in the physical parameters in mitral valve stenosis disease in different gender and age by using Doppler ultrasound. Methods : The examination of patients at the Division of Echo - at the Iraqi Center for Heart Disease in Medical City for surgery specialist - Baghdad - Iraq, during(February2009 till November2010). The current study included fifty eight cases containing (27 males and 31 females) ages rang

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Determination of Mono-crystalline Silicon Photovoltaic Module Parameters Using Three Different Methods
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For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Sun Jan 01 2023
Journal Name
Health Science Reports
Correlation of amyloid and ameloblast‐associated proteins to odontogenic cysts and tumors: A cross‐sectional study
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Abstract<sec><title>Background and Aims

Odontogenic cysts and tumors often form hard and soft structures that resemble odontogenesis. It is well known that amyloid is produced in Pindborg tumors; however, it is still debatable whether it is also formed in other odontogenic tumors and cysts. This study aimed to detect the presence of amyloid in different odontogenic cysts and tumors in correlation to matrix proteins secreted during enamel formation; namely amelogenin and odontogenic ameloblast‐associated protein.

Methods

This study included formalin fixed paraffin embedded tissue blocks of 106 different types of odontogenic

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