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Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.

Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Eco friendly synthesis of AgNPs using Green apple and pepper extracts for antibacterial application
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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Sat Jan 02 2021
Journal Name
Al-qadisiyah Journal For Engineering Sciences
Improving the Moisture Damage Resistance of HMA by Using Ceramic Fiber and Hydrated Lime
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The Moisture damage is considered as one of the main challenge for the experts in the field of asphalt pavement design. The aims of the present study is to modify moisture resistance of the asphalt concrete by utilizing ceramic fibers as a type of reinforcement incorporated with hydrated lime. For this purpose, a penetration grade of the asphalt cement (40-50) was utilized as a binder with an aggregate of the maximum nominal size of 12.5mm and mineral filler limestone dust. A series of specimens has been fabricated by utilizing 0.50, 1.0, 1.5, and 2.0 percentages of ceramic fibers. For each of these contents, another subsequent group of specimens with hydrated lime with 0.0, 1.0, 1.5, and 2.0 percentages were moulded. For the additi

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Effect of Skill and Physical Exercises Using Smart Virtual Reality for Volleyball Players
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Publication Date
Sun Jun 15 2025
Journal Name
Iraqi Journal Of Laser
Performance Enhancement of Metasurface Grating Polarizer Using Deep Learning for Quantum Key Distribution Systems
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance
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Publication Date
Tue Aug 01 2023
Journal Name
Advances In Mechanical Engineering
Using a spherical inverted pendulum and statokinesigram for modeling and evaluating quiet standing posture
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This paper proposes a new approach to model and analyze erect posture, based on a spherical inverted pendulum which is used to mimic the body posture. The pendulum oscillates in two directions, [Formula: see text] and [Formula: see text], from which the mathematical model was derived and two torque components in oscillation directions were introduced. They are estimated using stabilometric data acquired by a foot pressure mapping system. The model was quantitatively investigated using data from 19 participants, who were first were classified into three groups, according to the foot arch-index. Stabilometric data were then collected and fed into the model to estimate the torque’s components. The components were statistically proce

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Qualitative and Quantitative Determination of Dapagliflozin Propanediol Monohydrate and Its Related Substances and Degradation Products Using LC-MS and Preparative Chromatography Methods
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Dapagliflozin is a novel sodium-glucose cotransporter type 2 inhibitor. This work aims to develop a new
validated sensitive RP-HPLC coupled with a mass detector method for the determination of dapagliflozin, its
alpha isomer, and starting material in the presence of dapagliflozin major degradation products and an internal
standard (empagliflozin). The separation was achieved on BDS Hypersil column (length of 250mm, internal
diameter of 4.6 mm and 5-μm particle size) at a temperature of 35℃. Water and acetonitrile were used as
mobile phase A and B by gradient mode at a flow rate of 1 mL/min. A wavelength of 224nm was selected to
perform detection using a photo diode array detector. The method met the

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Publication Date
Mon Dec 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MOLECULAR CHARACTERIZATION OF ANISAKID NEMATODES HYSTEROTHYLACIUM SPECIES FROM JAPANESE THREADFIN BREAM NEMIPTERUS JAPONICUS (BLOCH, 1791) (PERCIFORMES, NEMIPERIDAE) FROM IRAQI MARINE WATER FISH
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The present study provides a new insight into valuable information on the diverse structure of the Anisakid population and discusses the limited species richness in the Nemipterus japonicus (Bloch,1791) (Perciformes, Nemiperidae). The fishing area consists of various locations in the Arabian Gulf (29°58 0 33 00 N48°28 0 20 E). A total of 315 marine fish were examined, (n=287) were infected. Larval stages (n= 763) encysted within the mesenteries peritoneum and viscera of fish organs were isolated, with a prevalence of 91.11% of infection and, the intensity was 2.65. Molecular analysis was carried out on thirty individuals who have examined the morphology and showed some appearance differences, by amplifying internal transcribed spacers

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Publication Date
Thu Jan 12 2023
Journal Name
Journal Of The Saudi Society Of Agricultural Sciences
Effect of planting density, foliar spraying and overlapping system on the growth and productivity using soilless culture system
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