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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
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Evaluation of Bearing Capacity of Strip Foundation Subjected to Eccentric Inclined Loads Using Finite Element Method
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In real conditions of structures, foundations like retaining walls, industrial machines and platforms in offshore areas are commonly subjected to eccentrically inclined loads. This type of loading significantly affects the overall stability of shallow foundations due to exposing the foundation into two components of loads (horizontal and vertical) and consequently reduces the bearing capacity.

Based on a numerical analysis performed using finite element software (Plaxis 3D Foundation), the behavior of model strip foundation rested on dry sand under the effect of eccentric inclined loads with different embedment ratios (D/B) ranging from (0-1) has been explored. The results display that, the bearing capacity of st

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Publication Date
Tue Nov 01 2022
Journal Name
Chemical Methodologies
Study of Optical and Structural Properties of CdTe Quantum Dots Capped with 3MPA Using Hydrothermal Method
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Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Science
Archaeological prospecting using the Electric Resistivity Imaging method at the Borsippa site, Near Babylon, Central Iraq
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Many important archaeological sites in Iraq still need to be preserved. Some of these sites were subjected to destruction and negligence. So, exploring these sites represents a priority for its protection. A 2D Electrical Resistivity Imaging (ERI) as a non-invasive geophysical survey method was implemented at a part of the Borsippa archaeological site near Babylon to search for the subsurface archaeological artefacts/structures. Electrical resistivity measurements were carried out using a Dipole-Dipole array. Steps were taken to process and filter using Horizontal profiles, forward modelling, and 2D inverse models to analyze the resistivity measurements. The ERI inversion results show that the superficial conductive zone produced va

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Publication Date
Wed Aug 20 2025
Journal Name
International Journal Of Advanced Research In Computer Science
IMPROVE DATA ENCRYPTION BY USING DIFFIE-HELLMAN AND DNA ALGORITHMS, AUTHENTICATED BY HMAC-HASH256
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: The need for means of transmitting data in a confidential and secure manner has become one of the most important subjects in the world of communications. Therefore, the search began for what would achieve not only the confidentiality of information sent through means of communication, but also high speed of transmission and minimal energy consumption, Thus, the encryption technology using DNA was developed which fulfills all these requirements [1]. The system proposes to achieve high protection of data sent over the Internet by applying the following objectives: 1. The message is encrypted using one of the DNA methods with a key generated by the Diffie-Hellman Ephemeral algorithm, part of this key is secret and this makes the pro

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Publication Date
Tue Dec 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Reasons for Partial Compliance and Non-compliance to the Routine Childhood Vaccination Schedule in Al-Karkh District
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Abstract

      Objective (s): To evaluate reasons for partial compliance and non-compliance to the

                              routine childhood vaccination schedule in Al-Karkh district 

Methodology: Descriptive study , using the evaluation approach, is carried throughout the present study to determine the reasons for the Routine Childhood Vaccination at  health care sectors and primary health care centers at  Al-Karkh District in Baghdad City, Convenient, non-probability, sample of (90) mother who are recruited from health care sectors at Al-Karkh District in Baghdad City. All mothers, who ha

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some robust methods to estimate parameters of partial least squares regression (PLSR)
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   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

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Crossref
Publication Date
Sat Aug 01 2020
Journal Name
Biochemical And Cellular Archives
PARTIAL PURIFICATION AND CHARACTERIZATION OF PHOSPHOENOLPYRUVATE CARBOXYKINASE FROM SERUM OF TYPE 2 DIABETIC PATIENTS
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: Partial purification of phosphoenolpyruvate carboxykinase (PEPCK) from type 2 diabetic patients sera take place using some purification steps such as participation with ammonium sulphate (55-80%) and filtered through dialysis, then ion exchange chromatography by DEAE sepharose anion column, gel filtration chromatography by sephadex G-100 column. In ion exchange step, there are four peak are obtained, the highest enzyme activity obtained by (0.4 M Nacl) with purification fold (2.18), yield (44.3) of enzyme and specific activity (13.5) mg/ng, which obtained a single peak by gel filtration chromatography, the degree of purification (5.34) fold, yield of enzyme (20%) with specific activity (33.109mg/ng). The purified enzyme had an optimum tem

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