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Sentiment Analysis in Social Media using Machine Learning Techniques
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Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show the success of this system where the accuracy of the system is more than 95% on social media data.

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Molecular Analysis of Bacterial Meningitis in Suspected Cases
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      One hundred and seventy-six cases of suspected meningitis (SMN) were included in a cross-sectional study. Their ages ranged from less than 1 year to 80 years, of whom 44.3% were male. The aim was to assess bacterial meningitis (BMN) in terms of incidence and types of causative bacteria. Cerebrospinal fluid (CSF) specimens were collected and polymerase chain reaction (PCR) analysis was conducted with universal primers designed to amplify a DNA fragment (996 bp) of the 16S rRNA gene of eubacteria. Resolving PCR products in agarose-gel electrophoresis revealed that 37.5% of CSF specimens were PCR positive, while 62.5% of CSF specimens showed no band and were considered PCR-negative. Eighty percent of the latter specimens were not

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Statistical Analysis of COVID-19 Data in Iraq
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The analysis of COVID-19 data in Iraq is carried out. Data includes daily cases and deaths since the outbreak of the pandemic in Iraq on February 2020 until the 28th of June 2022. This is done by fitting some distributions to the data in order to find out the most appropriate distribution fit to both daily cases and deaths due to the COVID-19 pandemic. The statistical analysis includes estimation of the parameters, the goodness of fit tests and illustrative probability plots. It was found that the generalized extreme value and the generalized Pareto distributions may provide a good fit for the data for both daily cases and deaths. However, they were rejected by the goodness of fit test statistics due to the high variability of the data.<

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Measurement and analysis of financial liberalization in Iraq
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Abstract :                                                                                                            

In light of the trend of the countries of t

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Publication Date
Sun May 08 2011
Journal Name
Journal Of Planner And Development
spatial analysis of health services in wasit governorate
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The spatial variation of regional development means that some regions to be a center of activities and services and job opportunities and economic development, and are usually in major urban centers, while lacking in other regions to such activities and services. Perhaps the studies of spatial variation SPATIAL INEQUALITY, regional development, REGIONAL DEVELOPMENT has had the greatest impact on the operations of regional planning in particular the study of the regional dimension of any city requires that you review the basis and theoretical framework, which refers to the inevitability of the existence of disparities across regions, due to the properties of the regions population and economic political and environmental The study

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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Tue May 07 2019
Journal Name
Acm Journal On Emerging Technologies In Computing Systems
Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis
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Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Self-organized learning strategies and self-competence among talented students
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Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016.  the researcher setup two scales based on the previous studies: one to measure  the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
A Study of the Problems of Learning and Translating Idioms
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Idioms are a very important part of the English language: you are told that if you want to go far (succeed) you should pull your socks up (make a serious effort to improve your behaviour, the quality of your work, etc.) and use your grey matter (brain).1 Learning and translating idioms have always been very difficult for foreign language learners. The present paper explores some of the reasons why English idiomatic expressions are difficult to learn and translate. It is not the aim of this paper to attempt a comprehensive survey of the vast amount of material that has appeared on idioms in Adams and Kuder (1984), Alexander (1984), Dixon (1983), Kirkpatrick (2001), Langlotz (2006), McCarthy and O'Dell (2002), and Wray (2002), among others

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