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Partial Least Squares Method for the Multicomponent Analysis of Antibacterial Mixture
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This study's objective is to assess how well UV spectrophotometry can be used in conjunction with multivariate calibration based on partial least squares (PLS) regression for concurrent quantitative analysis of antibacterial mixture (Levofloxacin (LIV), Metronidazole (MET), Rifampicin (RIF) and Sulfamethoxazole (SUL)) in their artificial mixtures and pharmaceutical formulations. The experimental calibration and validation matrixes were created using 42 and 39 samples, respectively. The concentration range taken into account was 0-17 μg/mL for all components. The calibration standards' absorbance measurements were made between 210 and 350 nm, with intervals of 0.2 nm. The associated parameters were examined in order to develop the optimal calibration model. The cross-validation method was used to determine the ideal number of components. The coefficient of determination (R2) and the root mean square error of calibration (RMSEC) are used to evaluate the calibration model. The relation between the LEV, MET, RIF, and SUL actual values and predicted values had a coefficient of determination that was higher than 0.997, showing very good accuracy of the devised approach. The obtained RMSEC values, 0.181056465 (LEV), 0.180375418 (MET), 0.142767171 (RIF), and 0.17157454 (SUL), show an analytical procedure with adequate precision. The suggested technique for quantitative analysis of the quaternary mixture of LEV, MET, RIF, and SUL have been applied successfully in different pharmaceutical preparations. The UV spectrophotometry assisted with chemometric-PLS without prior treatment, be utilised to resolve multicomponent mixtures successfully.

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Publication Date
Mon Apr 15 2024
Journal Name
Journal Of Engineering Science And Technology
Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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Publication Date
Fri Feb 05 2021
Journal Name
Research In Intelligent And Computing In Engineering
Implementing Web Testing System Depending on Performance Testing Using Load Testing Method.
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Web testing is very important method for users and developers because it gives the ability to detect errors in applications and check their quality to perform services to users performance abilities, user interface, security and other different types of web testing that may occur in web application. This paper focuses on a major branch of the performance testing, which is called the load testing. Load testing depends on an important elements called request time and response time. From these elements, it can be decided if the performance time of a web application is good or not. In the experimental results, the load testing applied on the website (http://ihcoedu.uobaghdad.edu.iq) the main home page and all the science departments pages. In t

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Publication Date
Sat Jul 01 2023
Journal Name
Int. J. Advance Soft Compu. Appl,
Arabic and English Texts Encryption Using Proposed Method Based on Coordinates System
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposed method to estimate missing values in Non - Parametric multiple regression model
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In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

 

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Positron Interactions with Some Human Body Organs Using Monte Carlo Probability Method
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In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Mon Sep 30 2024
Journal Name
Nasaq
A Semiotic Analysis Of Visual-Textual Elements In TobaccoFree Initiative 2021 Advertisements
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The provided research paper offers a thorough analysis of the semiotic analysis present in tobacco-free initiative advertisements from the year 2021. The study delves into the intricate process of decoding the diverse signs, symbols, and visual components integrated into these anti-smoking campaigns. The core aim of this investigation is to comprehend and explore the semiotic tactics that underlie these advertisements, with a particular emphasis on visual communication as a pivotal tool in shaping the public's attitudes and behaviors towards tobacco usage. The research introduces a significant theoretical framework, the "Taxonomy of Image-Text Relations and Functions" theory, as proposed by Emily E. Marsh and Marilyn Dom

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Publication Date
Fri Jan 01 2021
Journal Name
Bulgarian Journal Of Veterinary Medicine
First isolation and molecular phylogenetic analysis of Coxiella burnetii in lactating cows
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Q fever is an infectious disease of animals and humans, caused by globally distributed C. burnetii. In Iraq, there are no previous studies associated with the detection of the organism in cattle. An overall of 130 lactating cows were submitted to direct collection of milk samples. Initially, the samples of milk were tested using the molecular polymerase chain reaction (PCR) assay targeting three genes (16S rRNA, IS1111a transposase, and htpB). However, positive results (18.46%; 24/130) were detected only with the 16s rRNA gene. Concerning risk factors, the highest prevalence of C. burnetii was showed in the district of Badra (42.86%), whereas the lowest - in Al-Numaniyah and Al-Suwaira districts (P=0.025). There was no significant v

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Publication Date
Tue Nov 01 2022
Journal Name
Chemical Methodologies
Study of Optical and Structural Properties of CdTe Quantum Dots Capped with 3MPA Using Hydrothermal Method
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Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee

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