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Kinetic Study on Catalytic Wet Air Oxidation of Phenol in a Trickle Bed Reactor
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Kinetics study on the phenol oxidation by catalytic wet air oxidation (CWAO) using CuO.NiO/Al2O3 as heterogeneous catalyst is presented. 4 g/l phenol solution of pH 7.3 was oxidized in a trickle bed reactor with gas flow rate of 80% stochiometric excess (S.E).. In order to verify the proposed kinetics, a series of CWAO experimental tests were done at two temperatures (140 and 160° C), oxygen partial pressures (9 and 12 bar), and weight hourly space velocity (WHSV) (1, 1.5, 2, 2.5, and 3 h-1). According to Power Law, the reaction orders are found to be approximately 1 and 0.5 with respect to phenol concentration and oxygen solubility, respectively. These values favorably compare with those cited in the literature for intrinsic kinetics, which indicates minimal mass transfer limitations in the trickle bed reacting system used in this study.

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Jordan Higher Bi- Homomorphism and Co- Jordan Higher Bi- Homomorphism on Banach Algebra
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The concepts of higher Bi- homomorphism and Jordan higher Bi- homomorphism have been introduced and studied the relation between Jordan and ordinary higher Bi- homomorphism also the concepts of Co- higher Bi- homomorphism and  Co- Jordan higher Bi- homomorphism introduced  and the relation between them in Banach algebra have also been studied.

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Low-Rate High-Quality Parametric Audio Coder based on Sinusoidal plus Noise Representations
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This paper presents a parametric audio compression scheme intended for scalable audio coding applications, and is particularly well suited for operation at low rates, in the vicinity of 5 to 32 Kbps. The model consists of two complementary components: Sines plus Noise (SN). The principal component of the system is an. overlap-add analysis-by-synthesis sinusoidal model based on conjugate matching pursuits. Perceptual information about human hearing is explicitly included into the model by psychoacoustically weighting the pursuit metric. Once analyzed, SN parameters are efficiently quantized and coded. Our informal listening tests demonstrated that our coder gave competitive performance to the-state-of-the- art HelixTM Producer Plus 9 from

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Interior Visual Intruders Detection Module Based on Multi-Connect Architecture MCA Associative Memory
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Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

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Publication Date
Sun Jan 24 2016
Journal Name
Al-academy
Shift formal regulations on Mesopotamian pottery (Pottery Samarra model): محمد جاسم محمد العبيدي
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Operated Alandziahih "drift theory" as a science talk in most of the cash and technical studies in the early twentieth century, making him and the sciences, arts and culture both fields of experiences, in an attempt to explore the institutions that theory, a number of laws which took control in the internal structures of those acts, resulting in for those institutions to be actively contribute their ideas to guide the pace on the right track. And thus lay the foundations of this theory, which was a big affair in the early twentieth century and still vigorous pace to this day, particularly their applications in various fields of the arts.Although each type of Arts, both in the composition or the theater or means of communication, took joi

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Iraq public exposuring to foreign satellites and its effect on the cultural identity
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The summary of this study is to identify the relation ship between exposuing of the
public to foreign satellites and the degree of cultural of Iraqi public . the danger Iraqi public
exposure to foreign satellite specially some groups of the public are still own limited culture
and ideology without enough conscious to attitude of society . such people cun easily be
controlled by satellites , because these satellites may be the only cultural source for them
which may badly affect their behaviour . This study also aims to identify the level of Iraqi
people exposure to foreign satellites and the types and motivations of that exposure , then to
realize the relationship between exposing to foreign satellites and the cultur

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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Publication Date
Mon Dec 03 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Condition assessment and rehabilitation for trunk sewer deterioration based on Semi-Markov model
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An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

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