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Phytochemical Investigation of the Aerial Part of Iraqi Convolvulus arvensis
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Convolvulus arvensis is a species of bindweed that is rhizomatous and is in the morning glory family (Convolvulaceae) native to Europe and Asia. The plant is naturally grown in Iraq. The plant was reported to be used in traditional medicine from as early as 1730s.

The Aerial parts of Convolvulus arvensis were macerated in 80% ethanol for 6 days. The concentrated extract was partitioned with n-hexane, chloroform, ethyl acetate- and n-butanol successively. The n-hexane and ethyl acetate, fractions were examined for the presence of phytochemicals by thin layer chromatography and high performance liquid chromatography and its steroid and flavonoid contents were investigated. Stigmasterol was isolated from n-hexane fraction and identified by liquid chromatography/mass spectroscopy. Rutin was isolated from the ethyl acetate fraction and identified by liquid chromatography/mass spectroscopy. The aim is to examine the phytochemical constituents of the aerial parts of Convolvulus arvensis, literature survey available so far revealed that there were no studies about the phytochemical investigation for Convolvulus arvensis in Iraq.

 Different chromatographic techniques like Thin Layer Chromatography and mass spectroscopy were used and the presence of Stigmasterol and Rutin in aerial parts of Convolvulus arvensis was indicated.

 

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving Press Bending Production Quality through Finite Element Simulation: Integration CAD and CAE Approach
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Efficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Intelligent Age Estimation From Facial Images Using Machine Learning Techniques
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     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Sentiment Analysis on Roman Urdu Students’ Feedback Using Enhanced Word Embedding Technique
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Students’ feedback is crucial for educational institutions to assess the performance of their teachers, most opinions are expressed in their native language, especially for people in south Asian regions. In Pakistan, people use Roman Urdu to express their reviews, and this applied in the education domain where students used Roman Urdu to express their feedback. It is very time-consuming and labor-intensive process to handle qualitative opinions manually. Additionally, it can be difficult to determine sentence semantics in a text that is written in a colloquial style like Roman Urdu. This study proposes an enhanced word embedding technique and investigates the neural word Embedding (Word2Vec and Glove) to determine which perfo

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Publication Date
Thu Jan 02 2020
Journal Name
Journal Of The College Of Languages (jcl)
Linguistic Errors in second language learning through Error Analysis theory: هه‌ڵه‌ زمانییه‌كان له‌ فێربوونی زمانی دووه‌مدا (له‌ ڕوانگه‌ی تیۆری شیكاری هه‌ڵه‌ییه‌وه‌)
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Second language learner may commit many mistakes in the process of second language learning. Throughout the Error Analysis Theory, the present study discusses the problems faced by second language learners whose Kurdish is their native language. At the very stages of language learning, second language learners will recognize the errors committed, yet they would not identify the type, the stage and error type shift in the process of language learning. Depending on their educational background of English as basic module, English department students at the university stage would make phonological, morphological, syntactic, semantic and lexical as well as speech errors. The main cause behind such errors goes back to the cultural differences

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Comparative Reliability Analysis between Horizontal-Vertical-Diagonal Code and Code with Crosstalk Avoidance and Error Correction for NoC Interconnects
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Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages.  So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Efficient Approximate Analytical Methods to Solve Some Partial Differential Equations
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     The goal of this research is to solve several one-dimensional partial differential equations in linear and nonlinear forms using a powerful approximate analytical approach. Many of these equations are difficult to find the exact solutions due to their governing equations. Therefore, examining and analyzing efficient approximate analytical approaches to treat these problems are required. In this work, the homotopy analysis method (HAM) is proposed. We use convergence control parameters to optimize the approximate solution. This method relay on choosing with complete freedom an auxiliary function linear operator and initial guess to generate the series solution. Moreover, the method gives a convenient way to guarantee the converge

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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