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bsj-2326
Mefenamic Acid Selective Membranes Sensor and Its Application to pharmaceutical Analysis
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PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M, Nernstian slope of 17.18-18.4 mV/ decade, limit of detection 8.0 × 10–6-9.3 × 10-5M,pH range 3 – 8 and correlation coefficients range between 0.9984 and 0.9891, respectively. The measurement interferences in the presence of Li+, Na+, Mg2+ Ca2+, Fe3+and Al3+ were studied using separate and match potential methods for selectivity coefficient determination. The method was applied for the determination of Mefenamic Acid in pharmaceutical preparations

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Application of the Banzhaf Values for Cooperating Among Producers of Waste Processing in the Al-Mahmudiya Factory
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     The game theory has been applied to all situations where agents’ (people or companies) actions are utility-maximizing, and the collaborative offshoot of game theory has proven to be a robust tool for creating effective collaboration strategies in a broad range of applications. In this paper first, we employ the Banzhaf values to show the potential cost to waste producers in the case of a cooperation and to reduce the overall costs of processing non-recyclable waste during cooperation between producers. Secondly, we propose an application of the methodology to study a case for five waste producers' waste management in the Al-Mahmudiya factory with the aim of displaying the potential cost to waste producers in case of cooperatio

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Sat May 01 2021
Journal Name
Materials Today: Proceedings
WITHDRAWN: Application of net pay for reservoir characterization in carbonate reservoir rock – Case study: South-eastern of Iraq
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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Craniofacial Surgery
Novel Application of Platelet-Rich Fibrin as a Wound Healing Enhancement in Extraction Sockets of Patients Who Smoke
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Publication Date
Wed Sep 11 2024
Journal Name
Edelweiss Applied Science And Technology
Learning styles according to Entwistle model and their relationship to mathematical excellence among scientific fifth-grade female students
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The objective of the present study is to determine the nature and direction of the correlation between mathematical excellence and learning styles as defined by the Entwistle, model in fifth-grade scientific female students. The descriptive correlational approach was implemented by the two researchers to accomplish the research objectives. A scale was developed to assess the learning styles of female students in the sample in accordance with the Entwistle, model. : (Knowledge, understanding, application, analysis, synthesis, evaluation, systematic thinking, creativity), and the research community was determined by the female students of the scientific fifth grade in the morning preparatory and secondary schools of the General Direct

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Cybersecurity And Information Management
A New Automated System Approach to Detect Digital Forensics using Natural Language Processing to Recommend Jobs and Courses
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A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

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Publication Date
Sat Oct 01 2016
Journal Name
Arpn Journal Of Engineering And Applied Sciences
Numerical and experimental analysis of transient temperature and residual thermal stresses in friction stir welding of aluminum alloy 7020-T53
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Fri Jul 10 2020
Journal Name
Int. J. Agricult. Stat. Sci
STUDY EVALUATION AND ANALYSIS OF THE PROPERTIES OF SOME PERFORMANCE STANDARDS FOR AGRICULTURAL TRACTOR AND SORGHUM BICOLOR (L.) MOENCH YIELD
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A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Natural Sciences Research
Spectrophotometric-Assisted Chemometric Method for the Simultaneous Analysis of Furosemide, Carbamazepine, Diazepam, and Carvedilol in Their Bulk and Marketed Formulation
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Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.

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