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Microencapsulation of Green Coffee Beans (Coffea canephora) Extract using Whey Protein Concentrate
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Coffee bean contains bioactive compounds including caffeine and chlorogenic acid (CGA) that have a stimulant effect and are used for combating fatigue and drowsiness, and enhancing alertness. However, when the coffee bean was processed in the form of green coffee bean (GCB) extract, it has an unpleasant flavour and limitations instability, activity, and bioavailability. This study aimed to produce microcapsules of the GCB (Coffea canephora) ethanolic extract containing considerable amounts of the bioactive compounds for nutraceutical supplements. The GCB ethanolic extract was microencapsulated by spray drying using a whey protein concentrate (WPC) biopolimer. The particle size (PSA), morphology (SEM), and physicochemical characteristics (UV and LC-MS/MS), as well as radical scavenging activity (DPPH) of the microcapsule were determined. We found that the microencapsulation yield was 95.85% of the extract, with the particle mean of volume diameter was 1.312 µm (span value: 1.285 µm). The morphology of microcapsule particles was irregular microspheres with dense, smooth, wrinkle and shrivel, compact, and homogeneous surface. The microcapsule demonstrated the caffeine content of 15.25%, the CGA content of 8.52%, the total phenolic content of 1794.7 ± 77.0 mg GAE/100g and the radical scavenging activity of 179.23 µg/mL.

The WPC can be used to encapsulate the GCB extract by using spray drying microencapsulation to produce a high yield microcapsule with a smaller and narrower particle diameter. This microencapsulation was able to engulf and package unpleasant flavor and aroma, and to preserve considerable amounts of the bioactive compounds.

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
strong criminal capabilities، Using simulation .
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The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PREPARATION OF PVC HOLLOW FIBER MEMBRANE USING (DMAC/ACETONE)
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Membrane manufacturing system was operated using dry/wet phase inversion process. A sample of hollow fiber membrane was prepared using (17% wt PVC) polyvinyl chloride as membrane material and N, N Dimethylacetamide (DMAC) as solvent in the first run and the second run was made using (DMAC/Acetone) of ratio 3.4 w/w. Scanning electron microscope (SEM) was used to predict the structure and dimensions of hollow fiber membranes prepared. The ultrafiltration experiments were performed using soluble polymeric solute poly ethylene glycol (PEG) of molecular weight (20000 Dalton) 800 ppm solution 25 °C temperature and 1 bar pressure. The experimental results show that pure water permeation increased from 25.7 to 32.2 (L/m2.h.bar) by adding aceton

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Publication Date
Mon Sep 19 2016
Journal Name
Spie Proceedings
Simulation of push-pull inverter using wide bandgap devices
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Publication Date
Wed Aug 15 2018
Journal Name
Al-khwarizmi Engineering Journal
Bioremediation of Soil Contaminated with Diesel using Biopile system
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil:

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Publication Date
Thu Dec 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering
SENTIMENT RETRIEVAL OF HEALTH RECORDS USING NLP-BASED ALGORITHM
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
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In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Investigation of Superhydrophobic/Hydrophobic Materials Properties Using Electrospinning Technique
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     The aim of this research is to study the surface alteration characteristics and surface morphology of the superhydrophobic/hydrophobic nanocomposite coatings prepared by an electrospinning method to coat various materials such as glass and metal. This is considered as a low cost method of fabrication for polymer solutions of Polystyrene (PS), Polymethylmethacrylate (PMMA) and Silicone Rubber (RTV). Si were prepared in various wt% of composition for each solutions. Contact angle measurement, surface tension, viscosity, roughness tests were calculated for all specimens. SEM showed the morphology of the surfaces after coated. PS and PMMA showed superhydrophobic properties for metal substrate, while Si showed hydroph

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Publication Date
Tue Jan 01 2008
Journal Name
Journal Of Al-nahrain University
DETERMINATION THE AGE OF GALAXIES USING STRONG GRAVITATIONAL LENSING
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Most of the known cases of strong gravitational lensing involve multiple imaging of an active galactic nucleus. The properties of lensed active galactic nuclei make them promising systems for astrophysical applications of gravitational lensing. So we present a simple model for strong lensing in the gravitational lensed systems to calculate the age of four lensed galaxies, in the present work we take the freedman models with (k curvature index =0) Euclidian case, and the result show a good agreement with the other models.