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Astronomi cal Color Image Compression Using Multilevel Block Truncation Coding –Modified Vector Quantization Technique
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A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high compression ratio and good
subjective performance of modified VQ, a hybrid MBTC- modified VQ color image
compression method is presented. The analysis results have indicated the
performance of the suggested method is better, where the constructed images are less
distorted and compressed with higher factor(59:1).

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Removal of Oil From Wastewater Using Walnut-Shell
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The ability of pulverized walnut-shell to remove oil from aqueous solutions has been studied. It involves two-phase process which consists of using walnut-shell as a filtering bed for the accumulation and adsorption of oil onto its surface. Up to 96% oil removal from synthetic wastewater samples was achieved while tests results showed that 75% of oil can be removed from the actual wastewater discharged from Al- Duara refinery in the south of Baghdad.

 

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of Models (NAGARCH & APGARCH) by Using Simulations
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Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
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The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Engineering
Software Implementation of Binary BCH Decoder Using Microcontroller
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In this paper a decoder of binary BCH code is implemented using a PIC microcontroller for code length n=127 bits with multiple error correction capability, the results are presented for correcting errors up to 13 errors. The Berkelam-Massey decoding algorithm was chosen for its efficiency. The microcontroller PIC18f45k22 was chosen for the implementation and programmed using assembly language to achieve highest performance. This makes the BCH decoder implementable as a low cost module that can be used as a part of larger systems. The performance evaluation is presented in terms of total number of instructions and the bit rate.

 

 

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Hazardous Materials
The removal of caesium ions using supported clinoptilolite
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Using panel data in structural equations with application
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The non static chain is always the problem of static analysis so that explained some of theoretical work, the properties of statistical regression analysis to lose when using strings in statistic and gives the slope of an imaginary relation under consideration.  chain is not static can become static by adding variable time to the multivariate analysis the factors to remove the general trend as well as variable placebo seasons to remove the effect of seasonal .convert the data to form exponential or logarithmic , in addition to using the difference repeated d is said in this case it integrated class d. Where the research contained in the theoretical side in parts in the first part the research methodology ha

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Enhancement of Atorvastatin Tablet Dissolution Using Acid Medium
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         In this study some generic commercial products of Atorvastatin tablets were evaluated by dissolution test in acid medium by comparing with that of parent drug Lipitor of Pfizer Company. Some of solubilizing agents were studied in formulation  of Atorvastatin tablet including;  surface active agent  and PEG 6000 .The most effective factor was the  use of PEG6000 in formulation of Atorvastatin tablet which improved the dissolution and the results of dissolution profile of formulated tablet in this work  was bioequivalent to that of Lipitor .The quantitative analysis of this work was performed by using reversed phase liquid chromatography and a proper mixture of &nbsp

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Publication Date
Wed Feb 01 2023
Journal Name
Trends Technological And Science ,engineering
Automated Sorting for Tomatoes using Artificial Neural Network
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A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr

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Publication Date
Wed Apr 28 2021
Journal Name
Journal Of Engineering
Deasphalting of Atmospheric Iraqi Residue using Different Solvents
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Different solvents (light naphtha, n-heptane, and n-hexane) are used to treat Iraqi Atmospheric oil residue by the deasphalting process. Oil residue from Al-Dura refinery with specific gravity 0.9705, API 14.9, and 0.5 wt. % sulfur content was used. Deasphalting oil (DAO) was examined on a laboratory scale by using solvents with different operation conditions (temperature, concentration of solvent, solvent to oil ratio, and duration time). This study investigates the effects of these parameters on asphaltene yield. The results show that an increase in temperature for all solvents increases the extraction of asphaltene yield. The higher reduction in asphaltene content is obtained with hexane solvent at operating conditions of (90 °C, 4/1

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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