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The Effect of Dividend Policy on Earnings Quality in The Companies listed in Iraq Stock Exchange
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The dividends is one of difficult and important decisions taken by the administration in the economic units, because this decision has a direct impact on the investor and economic unit, so the main objective of any investor is achieve earnings, as well as information borne by dividends about the earnings quality of the economic unit and the level and efficiency of management to achieving earnings.

The research aims at explaining the effect of the dividends policy on the earnings quality in the companies listed in the Iraq Stock Exchange. The Miller model was used to measure the earnings quality in the companies listed in the Iraq Stock Exchange by using discretionary accruals short-term, the impact of the dividend policy on the earnings quality in the joint stock companies listed in the Iraq Stock Exchange was measured by organizing a questionnaire was distributed to a sample of employees in the companies. The effect of the variables was shown through the use of statistical models in the form of the smallest squares and linear regression model. After testing the hypotheses, a set of conclusions was reached, was the existence of an acceptable level of earnings quality in the financial statements issued by the companies listed in the Iraq Stock Exchange, as well as a significant relationship between dividends policy and earnings quality in the companies listed in the Iraq Stock Exchange, A number of recommendations were made the need to urge the joint stock companies listed in the Iraq Stock Exchange to follow a of fixed dividends policy, and maintain stable levels of dividends on a regular basis to avoid a negative impact on stock prices in the financial market, as well as the need for the Iraq Stock Exchange to increase the awareness of companies listed in the market the concept of earnings quality, as this concept of special economic benefits to the company itself and the general return to the market as a whole.

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Wed Dec 13 2023
Journal Name
Drug And Chemical Toxicology
Single and repeat-dose toxicity and local tolerance assessment of newly developed oil emulsion adjuvant formulations for veterinary purposes
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Publication Date
Wed May 13 2020
Journal Name
Journal Of Plant Nutrition
Seed priming of sorghum cultivars by gibberellic and salicylic acids to improve seedling growth under irrigation with saline water
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An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh

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Publication Date
Fri Mar 10 2017
Journal Name
Superconductor Science And Technology
Conceptual designs of conduction cooled MgB<sub>2</sub> magnets for 1.5 and 3.0 T full body MRI systems
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Water Process Engineering
Removal kinetics of organic carbon from palm oil mill effluent by native duckweeds and its potential as a biofertilizer
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Preparation and characterization of biomass-alumina composite as adsorbent for safranine-o dye from aqueous solution at different temperatures
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Publication Date
Thu Jan 23 2014
Journal Name
مجلة إبن الھيثم للعلوم الصرفة و التطبيقية
Synthesis of Tetra Dentate N2O2 and their Complexes With Cu[II), Zn[II), Cd[II) and Hg[II) Ions
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Publication Date
Sat Jun 01 2024
Journal Name
Results In Engineering
Thermodynamic modeling and performance analysis of photovoltaic-thermal collectors integrated with phase change materials: Comprehensive energy and exergy analysis
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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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