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Removal of Fluoride Ions from Wastewater Using Green and Blue-green Algae Biomass in a Fluidized Bed System
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The removal of fluoride ions from aqueous solution onto algal biomass as biosorbent in batch and continuous fluidized bed systems was studied. Batch system was used to study the effects of process parameters such as, pH (2-3.5), influent fluoride ions concentration (10- 50 mg/l), algal biomass dose (0–1.5 g/ 200 ml solution), to determine the best operating conditions. These conditions were pH=2.5, influent fluoride ions concentration= 10 mg/l, and algal biomass dose=3.5 mg/l. While, in continuous fluidized bed system, different operating conditions were used; flow rate (0.667- 0.800 l/min), bed depth (8-15 cm) corresponded to bed weight of (80- 150 g). The results show that the breakthrough time increases with the increase of bed depth but decreases with the increase of flow rate. Thomas and Yoon-Nelson models were used to analyze the experimental data and there was a good matching between the theoretical and the experimental data for both models. Desorption studies indicate that NaOH solutions at different pH values (8-10) were used to recover the fluoride ions sorbed onto the algal biomass. It is noteworthy that the desorption efficiency at pH =10 remains close to 95 % of the initial value of sorption capacity. So the desorption performance remains appreciable.

 

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Thu Aug 15 2013
Journal Name
Journal Of The College Of Basic Education
Synthesis and Characterization Mixed Ligands of Phenylalanine and Tributylphosphine Complexes with Selected Metal Ions.
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Complexes of Co(II),Ni(II),Cu(II) and Zn(II) with mixed ligands of phenylalanine (L) and tributylphosphine (TBPh) were prepared in aqueous ethanol with (2:1:1) (M:L:TBPh). The prepared complexes were characterized using flame atomic absorption,(C.H.N)Analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition biological activity of the phenylalanine and complexes against two selected type of bacteria were also examined. Some of the complexes exhibit good bacterial activities. From the obtained data the octahedral structure was suggested for all prepared complexes.

Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Comparative Study between RIPASA Scoring System and ALVARADO Scoring System in Diagnosing Acute Appendicitis in Adults
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Background: Acute appendicitis is regarded as one of the most common inflammation that needs surgical intervention. Different scoring systems have been used for diagnosing of acute appendicitis. ALVARADO score is one of the most widely used score in diagnosing of acute appendicitis, but the accuracy of the latter is insufficiently low in Middle-East patients. Thus a new scoring system called RIPASA score has been designed for diagnosing of acute appendicitis in those patients. The aim of this study is to use RIPASA score and compare its result with ALVARADO score in diagnosing of acute appendicitis.

Subjects and Methods: The study includes 200 patients with symptoms and signs of

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Change detection of the land cover for three decades using remote sensing data and geographic information system
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Publication Date
Mon Oct 18 2021
Journal Name
Microorganisms
Catalysis of Chlorovirus Production by the Foraging of Bursaria truncatella on Paramecia bursaria Containing Endosymbiotic Algae
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Chloroviruses are large viruses that replicate in chlorella-like green algae and normally exist as mutualistic endosymbionts (referred to as zoochlorellae) in protists such as Paramecium bursaria. Chlorovirus populations rise and fall in indigenous waters through time; however, the factors involved in these virus fluctuations are still under investigation. Chloroviruses attach to the surface of P. bursaria but cannot infect their zoochlorellae hosts because the viruses cannot reach the zoochlorellae as long as they are in the symbiotic phase. Predators of P. bursaria, such as copepods and didinia, can bring chloroviruses into contact with zoochlorellae by disrupting the paramecia, which results in an increase in virus titers in micr

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Publication Date
Sat Mar 01 2025
Journal Name
Al-iraqia Journal For Scientific Engineering Research
Blue Laser Optical NOMA Communication Applied on Control Drone-to-Underwater Vehicle
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oday deep ocean life has not been discovered by humans including many secret world things to be explored. The researcher has focused on underwater optical wireless communications using various kinds of complex digital Signal processing most of them used in air and starting applied in underwater communication. The Internet of Things (IoT) uses underwater called Internet of Underwater Things (IoUT) applications to explore the underwater world with other devices. However, the difference in concentration between air and water surfaces is not easy making wireless communication more complicated. Visible light passes the water's surface with scattering and distortion inside the water and each color of light has different attenuation the blue laser

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Geological Journal
A Predictive Model for Estimating Unconfined Compressive Strength from Petrophysical Properties in the Buzurgan Oilfield, Khasib Formation, Using Log Data
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Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Protection of Galvanized steel from corrosion in salt media using sulfur nanoparticles
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                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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