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Mathematical Modeling of a Hollow Fiber Module Used in Pressure-Retarded Osmosis Process
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   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The effect of these operational parameters was investigated on the theoretical permeate water flux and power density. According to the theoretical results, the permeate water flux and the power density increased with increasing the concentration of draw solution and the flow rate of the draw solution. While decreased with increasing the feed solution concentration. By increasing the applied hydraulic pressure on the draw solution, the water flux decreased and the produced power density increased. The maximum power density and the corresponding permeate water flux of 2 M NaCl draw solution was approximately 16.414 W/m2 and 11.818 LMH respectively, which occurs at an applied hydraulic pressure of 50 bar.

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Influence of Optical Fiber Diameters on the Performance of Surface Plasmon Resonance Sensor
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In this research, a sensor for chemical solutions was designed and formed using optical fiber-based on a surface Plasmon resonance technology. A single-mode optical fiber with three different diameters (25, 45 and 65) µm was used, respectively.  The second layer of the low refractive fiber was replaced by gold, which was electrically deposited at 40 µm thickness. For each of the three types of optical fiber, different saline concentrations (different index of refraction) were used to evaluate the performance of the refractive index sensor (chemical sensor) by measuring its sensitivity and resolutions. The highest values we could get for these two parameters were 240mm/RIU, and 6*10-5 RIU respectively, when the diameter of a

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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Physics
Effect of industrial powder on mechanical properties of glass fiber reinforced epoxy composite
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In the present study, composites were prepared by Hand lay-up molding and investigated. The composites constituents were epoxy resin as the matrix, 6% volume fractions of Glass Fibers (G.F) as reinforcement and 3%, 6% of industrial powder (Calcium Carbonate CaCO3, Potassium Carbonate K2CO3 and Sodium Carbonate Na2CO3) as filler. Density, water absorption, hardness test, flexural strength, shear stress measurements and tests were conducted to reveal their values for each type of composite material. The results showed that the non – reinforced epoxy have lower properties than composites material. Measured density results had show an incremental increase with volume fraction increase

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Modeling sequential preparation with rheumatoid tonsils in Nineveh for the period 2004-2009
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Abstract
             In this research will be treated with a healthy phenomenon has a significant impact on different age groups in the community, but a phenomenon tonsillitis where they will be first Tawfiq model slope self moving averages seasonal ARMA Seasonal through systematic Xbox Cengnzla counter with rheumatoid tonsils in the city of Mosul, and for the period 2004-2009 with prediction of these numbers coming twelve months, has found that the specimen is the best representation of the data model is the phenomenon SARMA (1,1) * (2,1) 12  from the other side and explanatory variables using a maximum temperature and minimum temperature, sol

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Synthesis of nanostructure diamond-like carbon thin films by atmospheric pressure plasma jet
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In this work, diamond-like carbon (DLC) thin films were prepared from Cyclohexane. Thin films were deposited on quartz substrate by atmospheric pressure Argon plasma jet system. The plasma jet system was applying high voltage sinusoidal waves of frequency 28 kHz and potential difference of 7.5kV peak to peak across the electrodes. The effect of annealing at 400, 500 and 600 °C under vacuum for two hours on optical properties and structural properties of the DLC thin films were investigated. This effect was clarified by X-ray diffraction (XRD), FTIR, UV-Visible absorption, Scanning Electron Microscopy (SEM) and Raman Spectroscopy. The X-ray diffraction patterns for the annealing DLC thin films show two broad peaks at 2θ, 26.62° and 51.58

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Publication Date
Mon Oct 03 2016
Journal Name
International Journal Of Civil Engineering
Development of Excess Pore Water Pressure around Piles Excited by Pure Vertical Vibration
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Publication Date
Mon Apr 01 2024
Journal Name
Chemical Engineering Research And Design
Treatment of petroleum refinery wastewater by a combination of anodic oxidation with photocatalyst process: Recent advances, affecting factors and future perspectives
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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Network Traffic Prediction Based on Time Series Modeling
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    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Modeling Social Networks using Data Mining Approaches-Review
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     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Modeling and Simulating NOMA Performance for Next Generations
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Non-orthogonal Multiple Access (NOMA) is a multiple-access technique allowing multiusers to share the same communication resources, increasing spectral efficiency and throughput. NOMA has been shown to provide significant performance gains over orthogonal multiple access (OMA) regarding spectral efficiency and throughput. In this paper, two scenarios of NOMA are analyzed and simulated, involving two users and multiple users (four users) to evaluate NOMA's performance. The simulated results indicate that the achievable sum rate for the two users’ scenarios is 16.7 (bps/Hz), while for the multi-users scenario is 20.69 (bps/Hz) at transmitted power of 25 dBm. The BER for two users’ scenarios is 0.004202 and 0.001564 for

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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