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bsj-2977
A Hybrid Method of Linguistic and Statistical Features for Arabic Sentiment Analysis
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          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discriminate the polarity of sentiments. This paper proposes a hybrid method of linguistic and statistical features along with classification methods for Arabic sentiment analysis. Linguistic features contains stemming and POS tagging, while statistical contains the TF-IDF. A benchmark dataset of Arabic tweets have been used in the experiments. In addition, three classifiers have been utilized including SVM, KNN and ME. Results showed that SVM has outperformed the other classifiers by obtaining an f-score of 72.15%. This indicates the usefulness of using SVM with the proposed hybrid features.

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Geological Journal
Electrical Resistivity Synthetic Modeling and Field Survey for Subsurface Features Investigation of the Borsippa Archaeological Site, Babylon Governorate, Middle Iraq
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The selection of proper field survey parameters of electrical resistivity can significantly provide efficient results within a reasonable time and cost. Four electrode arrays of 2D Electric Resistivity Imaging (ERI) surveys were applied to characterize and detect subsurface archaeological bodies and to determine the appropriate array type that should be applied in the field survey. This research is to identify the subsurface features of the Borsippa archaeological site, Babylon Governorate, Middle Iraq. Synthetic modeling studies were conducted to determine the proper array and parameters for imaging the shallow subsurface features or targets. The efficiency of many array types has been tested for the detection the buried archaeolog

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
Audio Classification Based on Content Features
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Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Sun Mar 30 2025
Journal Name
Studia Universitatis Babeș-bolyai Chemia
GREEN SPECTROPHOTOMETRIC METHOD FOR CONCURRENT ESTIMATION OF PIROXICAM AND MEFENAMIC ACID MIXTURE
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The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

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Publication Date
Sun Mar 30 2025
Journal Name
Studia Universitatis Babeș-bolyai Chemia
GREEN SPECTROPHOTOMETRIC METHOD FOR CONCURRENT ESTIMATION OF PIROXICAM AND MEFENAMIC ACID MIXTURE
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Flotation Method for Selective Separation of Lead and Zinc from Simulated Wastewater
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In this paper flotation method experiments were performed to investigate the removal of lead and zinc. Various parameters such as pH, air flow rate, collector concentrations, collector type and initial metal concentrations were tested in a bubble column of 6 cm inside diameter. High recoveries of the two metals have been obtained by applying the foam flotation process, and at relatively short time 45 minutes . The results show that the best removal of lead about 95% was achieved at pH value of 8 and the best removal of zinc about 93% was achieved
at pH value of 10 by using 100 mg/l of Sodium dodecylsulfate (SDS) as a collector and 1% ethanol as a frother. The results show that the removal efficiency increased with increasing initial m

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Publication Date
Thu Sep 01 2022
Journal Name
Structures
Hybrid and patch anchors for prevention of IC debonding in RC planks flexurally strengthened using FRP
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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Recognition of Upper Limb Movements Based on Hybrid EEG and EMG Signals for Human-Robot Interaction
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
International Studies Concerning Teachers’ Attitudes towards the Inclusion of Students with Special Educational Needs: Review of Literature
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Over the years, the issue of inclusion of students with special educational needs (SEN) in mainstream schools is controversial worldwide. Evidence from research argues that without a positive teachers’ attitude towards the inclusion of students with SEN in mainstream schools, the successful implementation of inclusion is most likely doubtable. The aim of this paper is to understand teachers’ attitudes towards the inclusion of students with SEN in mainstream schools from different perspectives and from different contexts. The conclusion drawn in this review can be that teachers’ attitude is the most important key towards the appropriate inclusion implementation in mainstream schools. The disparity of teachers’ attitudes towards th

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