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Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artificial neural networks in the sports industry in the Republic of Iraq is crucial to ensure successful players. In this study, an artificial neural network model was built to predict Men's 100 meter indexes. Several factors related to the construction of artificial neural networks were studied, including network architecture and internal factors and their impact on the performance of the models. As a result, four easy equations were developed to calculate the four key indexes. The findings of the study indicate that these networks can predict Men's 100 Meter indexes with a high degree of reliability 98.034% and accounting coefficients R = 0.9143.

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The relationship between organizational justice and empowerment and their impact on achieving organizational commitment (field study in the Department of Labor and Vocational Training)
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The research has deal with the relationship between organizational justice and empowerment and their impact on the achievement of organizational commitment in the office of Labour and Vocational Training. To study the research problem which is represented a sense that employees with low levels of organizational justice and empowerment and the reflection on the organizational commitment of the employees, so that Has been collecting data and information relating to research by designing a questionnaire, were distributed to a sample of (50) people in the office mentioned, and the results of the study to confirm the research hypotheses. and the key results of the research was the presence of correlation relationships and the effect o

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The effect of intellectual capital on the Total quality management of higher education and scientific research institutions in Baghdad
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         The purpose and goal of the research revolve around the diagnosis of intellectual capital as the logical indicator to study an effective human resource management practice and its influential role in determining the overall quality management of higher education institutions and scientific research in Baghdad.

       To achieve the purpose of the research, an upgraded standard questionnaire was used to collect data and distribute it to the selected sample in a statistical manner from the study population of (5) institutions affiliated with the Ministry of Higher Education and Scientific Resear

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Effect of Public Debt on The Trade Balance in Iraq For The Period (2003-2021)
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Despite the significant increase in public spending in Iraq, it was not directed toward the important sectors that have an important role in correcting the productive structure. Rather, most of the public expenditure was going to cover the required imports, or to face shocks, whether security or health, and this caused a continuous decrease in the volume of Iraq's exports of goods and services, as the aim of the study was to review the importance of public debt and its impact on the trade balance, as well as to know the economic policies that can contribute to strengthening the trade balance, as the study proved through the (ARDL) model that there is a direct relationship between the domestic debt and the net trade balance, and an invers

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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Dimensional analysis of predicting the removal of chemical oxygen demand from domestic wastewater using moving bed biofilm reactor
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Municipal wastewater sources are becoming increasingly important for reuse, for irrigation purposes, so they must be treated to meet environmentally friendly local or global standards. The aim of this study is to establish, calibrate, and validate a model for predicting chemical oxygen demand for the pilot plant of mobile biofilm reactors operating from municipal wastewater in Maaymyrh located in Hilla city Using the approach of dimensional analysis. The approach of Buckingham's theorem was used to derive a model of dimensional analysis design for the forecast of (COD) in the pilot plant. The effluent concentration (COD) It has been derived as a result of the influential concentration of (COD), dissolved oxygen (DO), volume of pilot plant

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Publication Date
Sat Apr 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis, Characterization and Determination Antioxidant Activities for New Azo Dyederived from Sulfamethoxazole and Some Metal Ion Complexes
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Diazotization reaction between 1-(2,4,6-trihydroxy-phenyl)-ethanone and diazonium salts produced the ligand 4-(3-Acetyl-2,4,6-trihydroxy-phenylazo)-N-(5-methyl-isoxazol-3-yl)- benzenesulfonamide, which in turn reacted with the metal ions (Ni2+, Zn2+, Pd2+ and Pt4+) forming stable complexes with Octahedral geometry suggest of (Ni2+ and Pt4+), Zn2+ complex Tetrahedral and Pd2+ complex Square planer. The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible, which proved the obtained geometries; FT-IR confirmed the formation of the azo group and the coordination with metal ions through it. Thermogravimetric analysis studies demonstrated the coordination of water residues (aqua or hydrate) with m

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Publication Date
Wed Sep 30 2020
Journal Name
Industrial Engineering & Management Systems
Economic Analysis of the Financial Literacy Effects in G20
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ABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS: EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS
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The mucilage was isolated from mustard seeds and identification by some different methods like, thermo gravimetric, FTlR., X-ray powdered, proton NMR, FTIR spectra of the three gums contain different functional group in the gums, major peaks  bands noticed were belong to OH (3410.15 – 3010.88) group from hydroxyl group, CH aliphatic (2925-2343.51), C-O (1072.42-1060.85) group and C=O 1743.65, Thermo chemical parameters of mucilage was evaluated  and compared with the standard gums, Results indicated the mucilage was decomposed in 392°C and mass loss 55%, The X ray process found the mucilage had single not sharp peak

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity
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Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

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Publication Date
Mon Mar 09 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
Sentiment Analysis of Twitter Users Using Deep Learning Models
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

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