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The Phenomenon of Phonological Follow in Al-Amali Abi Ali Al-Qali’s Book (seq.356 Hijri): A Phonological Study: هند فاضل عباس
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This research discusses the verbal follow phenomenon in Al-Amali Abi Al-Qali’s book (seq.356 Hijri). It aims to limit the examples of this phenomenon in the book, and  examine it phonologically. Accordingly, the researcher adopted the analaytical descriptive approach, taking into account Al-Rawi’s letter when ordering the verbal follow-based examples, and the order they took in the book in question. The purposes behind this phonological study of verbal follow in Al-Amali’s book are to: reach the sounds which Arabs prefer in the process of following, confirm different beautiful and desirable senses, have easy and speedy pronunciation, maintain harmony between adjacent sounds, count the sounds that occur at the beginning of the follower- a disputable phonological issue between the follower and following- and spot the phonological change that occurs to the follower. Accordingly, a caution is needed to maintain harmony and homogeneity between two pronunciations to achieve the process of following. Or, the structure of the word follower is changed to match its peer followed word.The study has shown that Al-Qali was the eldest in dealing with the formal aspect of the phenomenon. He pointed to the idea of merging the last letter in the subordinate and the follower, and compared it with a stylistic, artistic, and acoustic characteristic, which is included in the innate rhetoric, i.e., assonance. By that, he has determined the most important formal acoustic features of the rhythmic complex as represented by the endings of the sequences, which have a musical rhythm.

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A comparison between banana peel powder and gel for removing methylene blue dye from aqueous solution
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This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

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Publication Date
Tue Sep 01 2020
Journal Name
Optical Fiber Technology
A novel modified fiber Bragg grating (FBG) based ammonia sensor coated with polyaniline/graphite nanofibers nanocomposites
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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Linear Programming Method Based Optimal Power Flow Problem for Iraqi Extra High Voltage Grid (EHV)
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The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

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Publication Date
Fri Dec 15 2023
Journal Name
Iraqi Journal Of Laser
D-shape Optical Fiber Development and Enhancement as a Refractive Indices Sensor Using Surface Plasmon Resonance
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This article showcases the development and utilization of a side-polished fiber optic sensor that can identify altered refractive index levels within a glucose solution through the investigation of the surface Plasmon resonance (SPR) effect. The aim was to enhance efficiency by means of the placement of a 50 nm-thick layer of gold at the D-shape fiber sensing area. The detector was fabricated by utilizing a silica optical fiber (SOF), which underwent a cladding stripping process that resulted in three distinct lengths, followed by a polishing method to remove a portion of the fiber diameter and produce a cross-sectional D-shape. During experimentation with glucose solution, the side-polished fiber optic sensor revealed an adept detection

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Tue Aug 25 2020
Journal Name
Journal Of Clinical Medicine
Self-Limiting versus Rotary Subjective Carious Tissue Removal: A Randomized Controlled Clinical Trial—2-Year Results
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Background: the aim of this study was to assess the 2-year pulp survival of deep carious lesions in teeth excavated using a self-limiting protocol in a single-blind randomized controlled clinical trial. Methods: At baseline, 101 teeth with deep carious lesions in 86 patients were excavated randomly using self-limiting or control protocols. Standardized clinical examination and periapical radiographs of teeth were performed after 1- and 2-year follow-ups (REC 14/LO/0880). Results: During the 2-year period of the study, 24 teeth failed (16 and 8 at T12 and T24, respectively). Final analysis shows that 39/63 (61.9%) of teeth were deemed successful (16/33 (48.4%) and 23/30 (76.6%) in the control and experimental groups, respectively wit

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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