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Extraction of Essential Oils from Citrus By-Products Using Microwave Steam Distillation
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The main objectives of this research is to extract essential oil from: orange ( citrus sinensis), lemon( citrus limon) and mandarin( citrus reticulata) peels by two methods: steam distillation (SD) and microwave assisted steam distillation (MASD), study the effect of extraction conditions (weight of the sample, extraction time, and microwave power, citrus peel type) on oil yield and compare the results of the two methods, the resulting essential oil was analyzed by Gas Chromatography (GC).

   Essential oils are highly concentrated substances used for their flavor and therapeutic or odoriferous properties, in a wide selection of products such as foods, medicines and cosmetics. Extraction of essential oil is one of the most time and effort consuming process. Microwave-assisted extraction is a green technique for the extraction of natural products. (MASD) was better than (SD) in terms of rapidity, energy saving and yield. (MASD) gave higher yield than (SD) with shorter extraction time, yield of orange oil extracted by (MASD) was (1.150%) in (35min.) compared to (1.095%) in (45min.) by (SD) process, same results obtained for lemon and mandarin.

   The optimal microwave power was (135W) gave oil yield: (1.150%, 1.115%, 0.940%) for orange, lemon and mandarin respectively, (MASD) increased extraction temperature in short time and to a higher level compared to (SD). The optimal weight was (398.56gm) gave yield in (SD): (1.095%) and MASD (1.091%) for orange oil, same results obtained for lemon and mandarin. The best citrus peel type which gave the highest yield was orange followed by lemon then mandarin in both processes.

Limonene is the most abundant component in citrus essential oil, (GC) analysis showed that (SD) was more convenient to give high amount of limonene because of the graduate temperature rise, while in microwave extraction exposure to low microwave

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Thu Aug 01 2024
Journal Name
Indonesian Journal Of Chemistry
Cloud Point Extraction Method for Spectrophotometric Determination of 3-Aminophenol in Environmental Samples
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This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
A research taken from Dissertation " Artistic Expression by painting among Kindergarten child"
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The current study aims to identify the artistic expression as well as the aspects of artistic expression by the painting among the kindergarten children. In order to fulfill the research's goals, a sample of (400) children were chosen randomly from 19 public kindergartens of 6 directorates at Al-Rusafa and Al-Karkh in Baghdad city. The children were asked to draw a particular view. The researcher  has adopted  Al-Hamedawi scale  (2009) consisted of  (16) items, which was exposed to group of (25) experts in  psychology, education,  measurement and evaluation,  artistic  education by painting  and plastics  to show  the items reliability. As the researcher applied T-test  for&nbsp

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Influence of water in size of Synthesized Carbon Black Nanoparticles from Kerosene by Flame Method
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Publication Date
Fri Jun 01 2018
Journal Name
Iraqi Journal Of Science
Cleavage of mucin and salivary agglutinin by partiallypurified protease from native strain of Streptococcus mutansan67
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Publication Date
Thu Jul 01 2021
Journal Name
Computers & Electrical Engineering
A new proposed statistical feature extraction method in speech emotion recognition
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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
REMOVAL of HEAVY METALS IONS from AQUEOUS SOLUTIONS USING BIOSORPTION onto BAMBOO
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Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact t

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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Theoretical Calculation of Photon Emission from Quark-Antiquark Annihilation Using QCD Theory
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In this work, we calculate and analyze the photon emission from quark and anti-quark interaction during annihilation process using simple model depending on phenomenology of quantum chromodynamic theory (QCD). The parameters, which include the running strength coupling, temperature of the system and the critical temperature, carry information regarding photon emission and have a significant impact on the photons yield. The emission of photon from strange interaction with anti-strange is large sensitive to decreases or increases there running strength coupling. The photons emission increases with decreases running strength coupling and vice versa. We introduce the influence of critical temperature on the  photon emission  rate in o

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Publication Date
Wed May 31 2017
Journal Name
Journal Of Engineering
Synthesis of Nanozeolite NaA from Pure Source Material Using Sol Gel Method
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In this work, the nano particles of Na-A zeolite were synthesized by sol –gel method. The samples were characterized by X-ray diffraction (XRD), X-ray  luorescence (XRF), Surface  area and pore volume, Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FTIR). Results show that the nano A zeolite is with average crystal size is 74.77 nm., Si/Al ratio 1.03, BET surface area was 581.211m2/g and the pore volume for NaA was found equal to 0.355cm3/g.
 
 
 

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