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Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts involving Happiness and Sadness emotions (with 80% accuracy for Aman’s dataset and 76.7% for Alm’s datasets) and texts involving Ekman’s six basic emotions for the LiveJournal dataset (87.8% accuracy). Results also show that the method outperforms traditional feature-based classifiers such as Naïve Bayes and SMO in most cases in terms of accuracy, precision, recall and F-measure.

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
Contemporary experimental currents and its impact on the structure of the contemporary Iraqi theatrical text "The epic theater as a model": هيثم حمزة سلمان الحمداني
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  In this research study, I tried to trace the epic effect to learn how it was understood and how it was used. Following the descriptive and analytical approach in the research, the first chapter dealt with a presentation of the methodological framework of the problem, the goal, the limits of the research, the importance and the need for it and the definition of terms, as well as the theoretical framework which consisted of two topics, including the impact of the epic theater on the world theater and the second the effect of the epic theater on the Arab theater, This came by tracing the epic impact on the world stage of the Greeks, the Middle Ages, the Renaissance, and the Arab theater of the twentieth century.
As for the second

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Oral Disintegrating Tablets of Ketoprofen by Dirct Compression
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Ketoprofen is a non-steroidal anti-inflammatory (NSAID) drug with analgesic, anti-inflammatory, and antipyretic effects. It is widely used in the treatment of inflammation and pain associated with rheumatic disorders such as rheumatoid arthritis, osteoarthritis, and in soft tissue injury. The purpose of this study was to prepare an  oral disintegrating tablets of ketoprofen by simple method. The tablets were prepared by direct compression method and different ratios of various subliming agents or superdisintegrants were incorporated. Then these tablets were evaluated for hardness, friability, weight variation, water absorption ratio, disintegrating time and dissolution time. The results showed that Formula F11 batch had short disint

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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)
Genetic Variations of Echinococcus granulosus Isolated from Sheep and Cows by Using Fingerprint DNA Method in Iraq
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The fingerprinting DNA method which depends on the unique pattern in this study was employed to detect the hydatid cyst of Echinococcus granulosus and to determine the genetic variation among their strains in different intermediate hosts (cows and sheep).  The unique pattern represents the number of amplified bands and their molecular weights with specialized sequences to one sample which different from the other samples.   Five hydatitd cysts samples  from cows and sheep were  collected, genetic analysis for  isolated DNA was done using PCR technique and  Random Amplified Polymorphic DNA reaction(RAPD) depending on (4) random primers, and the results showed:      

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Publication Date
Mon May 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparison hybrid techniques-based mixed transform using compression and quality metrics
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Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Fri Jan 01 2021
Journal Name
Communications In Computer And Information Science
Audio Compression Using Transform Coding with LZW and Double Shift Coding
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Home New Trends in Information and Communications Technology Applications Conference paper Audio Compression Using Transform Coding with LZW and Double Shift Coding Zainab J. Ahmed & Loay E. George Conference paper First Online: 11 January 2022 126 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1511) Abstract The need for audio compression is still a vital issue, because of its significance in reducing the data size of one of the most common digital media that is exchanged between distant parties. In this paper, the efficiencies of two audio compression modules were investigated; the first module is based on discrete cosine transform and the second module is based on discrete wavelet tr

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language
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Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette

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