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Electrocoagulation of phenol for wastewater treatment
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Electrocoagulation is an electrochemical process of treating polluted water where sacrificial anode corrodes to produce active coagulant (usually aluminum or iron cations) into solution. Accompanying electrolytic reactions evolve gas (usually as hydrogen bubbles). The present study investigates the removal of phenol from water by this method. A glass tank with 1 liter volume and two electrodes were used to perform the experiments. The electrode connected to a D.C. power supply. The effect of various factors on the removal of phenol (initial phenol concentration, electrode size, electrodes gab, current density, pH and treatment time) were studied. The results indicated that the removal efficiency decreased as initial phenol concentration increased, the highest removal obtained at pH in the range (6-8), the removal enhanced with increasing electrode size and decreasing the gab between the electrodes. The optimum current density obtained at 221 A/m2.

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Cultivation of Microalgae Chlorella vulgaris in Airlift photobioreactor for Biomass Production using commercial NPK Nutrients
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Airlift reactors are widely used in the chemical and biochemical applications as effective contactors for mass and heat transfer. The main advantages of airlift contactor compared with simple bubble column are ease of construction, low shear rate, high capacity, good mixing and liquid circulation without mechanical agitators and circulating pumps.

In this work, growth characteristics of Chlorella vulgaris microalgae were studied in an internal loop airlift photobioreactor for biomass production. The bioreactor operated under batch and semi-continuous culture mode using commercially available 20:20:20+TE NPK fertilizer as nutrients. The experiments were conducted to evaluate the growth rate and biomass productivity of

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Synthesis and evaluation of chalcone derivatives for antimicrobial and antioxidant activities using microwave-assisted methodology
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Publication Date
Mon Jul 01 2024
Journal Name
Alexandria Engineering Journal
Comparison of some Bayesian estimation methods for type-I generalized extreme value distribution with simulation
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The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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Publication Date
Tue Apr 02 2024
Journal Name
Journal Of Engineering
Revolutionizing Depth Sensing: A Review Study of Apple LiDAR Sensor for as-built Scanning Applications
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Incorporating the LiDAR sensor in the most recent Apple devices represents a substantial development in 3D mapping technology. Meanwhile, Apple's Lidar is still a new sensor. Therefore, this article reviews the potential uses of the Apple Lidar sensor in various fields, including engineering and construction, focusing on indoor and outdoor as-built 3D mapping and cultural heritage conservation. The affordable cost and shorter observation times compared to traditional surveying and other remote sensing techniques make the Apple Lidar an attractive choice among scholars and professionals. This article highlights the need for continued research on the Apple LiDAR sensor technology while discussing its specifications and limitations. A

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the Critical Success Factors for Total Quality Management Applications (Compared research of many colleges)
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ABSTRACT

This research aim to measure the critical success factors for total quality management applications, in order to know the key and important role played by these factors at applying the total quality management through a comparative study conducted in a number of a private colleges.

The research problem posed a set of questions, the most important ones are: Are the colleges (sample of research) aware of the critical success factors at applying the total quality management? What is the availability of the critical success factors at the work of the colleges (sample of research)? 

What are the critical success factors in the work of the researc

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Publication Date
Thu Jan 01 2026
Journal Name
Procedia Computer Science
Revolutionizing Higher Education by Harnessing the Power of AI and Big Data for Sustainable Education
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The integration of Artificial Intelligence with Big Data Analytics is one of the most groundbreaking developments that could change the face of educational sustainability in higher education.. Using AI and Big Data technologies not only makes the educational process more efficient but also changes the way people learn and thus opens the door for educators and institutions to make decisions based on the data. The document imparts the manner that the use of AI and the digital revolution can remove student requirements, execute the efficiency of the curriculum, and acquire the balance of educational resources through a majority of instances and the latest developments in that field. Furthermore, the paper, along with the issues of morality wit

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Publication Date
Fri Dec 29 2023
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF ORGANIC FERTILIZER AND BORON FOLIAR ON QUANTITATIVE AND QUALTITATIVE TRAITS POTATO FOR PROCESSING
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A field experiment was carried out at University of Baghdad, College of Agricultural Engineering Sciences during fall season of 2020 and spring season of 2021. This study was aimed evaluate the effect of the organic fertilizer and boron foliar on the yield of potatoes for processing. The factorial experiment (5*4) within RCBD and three replicates. The organic fertilizer as palm peat at four levels (0, 12, 24 and 36 ton. ha-1) in addition to the chemical fertilizer recommendation treatment. Boron at four Concentrations 0, 100, 150 and 200 mg. L-1 . The results revealed significant different among application of organic fertilizer at the level of 24 ton. ha-1 and the foliar application of boron at a concentration of 100 mg. L-1 in the

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Faber Polynomial Coefficient Estimates for Subclass of Analytic Bi-Bazilevic Functions Defined by Differential Operator
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In this work,  an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.

         In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.

 

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