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Graphite-Catalyzed Electro-Oxidation of Hydrazine Derivatives Using Sodium Chloride under Green and Sustainable Chemistry
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The development of efficient and environmentally friendly catalysts for the electro-oxidation of hydrazine derivatives is of great importance in various industrial applications. In this study, we report the utilization of graphitebased catalysts for the electro-oxidation of hydrazine derivatives, using sodium chloride as a green and sustainable chemical approach. Graphite, a two-dimensional carbon material with exceptional properties, offers numerous advantages as a catalyst, including its high surface area, excellent electrical conductivity, and chemical stability. These characteristics make graphite an ideal candidate for promoting electrochemical reactions. Sodium chloride (NaCl), a readily available and cost-effective salt, serves as a green alternative to traditional oxidants used in hydrazine oxidation processes. By replacing conventional oxidizing agents with NaCl, we aim to reduce the environmental impact associated with the production and disposal of hazardous chemicals. This process enables the transformation of the HN-NH bond within hydrazines, leading to the formation of azo compounds (N¼N). Azo compounds are important organic molecules with diverse applications in organic synthesis. This novel approach has successfully showcased the efficacy of utilizing various azo compounds in 13 different examples, yielding excellent or moderate to good results. The method capitalizes on electricity as the final oxidizing agent, providing an environmentally friendly oxidation strategy. Its high efficiency and gentle reaction conditions make this technique valuable for synthesizing azo derivatives, even when working with hydrazines containing diverse functional groups, resulting in yields ranging from moderate to excellent. Through systematic experiments, we evaluated the catalytic performance of graphite-based catalysts in the electro-oxidation of hydrazine derivatives. The catalysts demonstrated remarkable catalytic activity due to their efficient conversion of hydrazine derivatives into desired products. Moreover, the system exhibited good stability and recyclability, suggesting its suitability for practical applications.

Scopus
Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems
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            In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

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Publication Date
Sat Aug 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Text hiding in text using invisible character
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Steganography can be defined as the art and science of hiding information in the data that could be read by computer. This science cannot recognize stego-cover and the original one whether by eye or by computer when seeing the statistical samples. This paper presents a new method to hide text in text characters. The systematic method uses the structure of invisible character to hide and extract secret texts. The creation of secret message comprises four main stages such using the letter from the original message, selecting the suitable cover text, dividing the cover text into blocks, hiding the secret text using the invisible character and comparing the cover-text and stego-object. This study uses an invisible character (white space

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Scopus (4)
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Scopus (25)
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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Scopus (13)
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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
Multiple and Coherent Noise Removal from X-Profile 2D Seismic Data of Southern Iraq Using Common Depth Point Muting Procedures and Depending on Madagascar Open-Source Package
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This article describes how to predict different types of multiple reflections in pre-track seismic data. The characteristics of multiple reflections can be expressed as a combination of the characteristics of primary reflections. Multiple velocities always come in lower magnitude than the primaries, this is the base for separating them during Normal Move Out correction. The muting procedure is applied in Time-Velocity analysis domain. Semblance plot is used to diagnose multiples availability and judgment for muting dimensions. This processing procedure is used to eliminate internal multiples from real 2D seismic data from southern Iraq in two stages. The first is conventional Normal Move Out correction and velocity auto picking and

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Scopus (1)
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Publication Date
Mon Sep 07 2020
Journal Name
Environmental Science And Pollution Research
The biosorption of reactive red dye onto orange peel waste: a study on the isotherm and kinetic processes and sensitivity analysis using the artificial neural network approach
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Publication Date
Thu Mar 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Radiological Evaluation of the Anatomic Characteristic of Lingual Foramina and Their Vascular Canals in the Anterior Region of the Mandible Using Cone Beam Computed Tomography
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Background: presence of lingual vascular foramina and canals in the interforaminal region may increase the risk ofsurgical complications during implant placement or any surgical procedure in this area. Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended Al-Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canal

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Crossref (1)
Crossref
Publication Date
Fri Dec 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Radiological Evaluation of The Anatomic Characteristic of Lingual Foramina and Their Vascular Canals in The Anterior Region of The Mandible Using Cone Beam Computed Tomography
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Background: presence of lingual vascular foramina and canals in the interforaminal regionmay increase the risk ofsurgical complications during implant placement or any surgical procedure in this area.Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended AL- Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canals

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