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bsj-9750
Prioritized Text Detergent: Comparing Two Judgment Scales of Analytic Hierarchy Process on Prioritizing Pre-Processing Techniques on Social Media Sentiment Analysis
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Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Making (MCDM) methods, the Analytic Hierarchy Process (AHP) is preferred for handling complicated decision-making challenges using several criteria. The Consistency Ratio (CR) scores were used to examine pair-wise comparisons to evaluate the AHP. This study used two judgment scales to get the most consistent judgment. Firstly, the Saaty judgment scale (SS), then the Generalized Balanced Scale (GBS). It investigated whether two different AHP judgment scales would affect decision-making. The main criteria for prioritizing pre-processing techniques in sentiment analysis are Punctuation, Spelling, Number, and Context. These four criteria also contain sub-criteria. GBS pair-wise comparisons are closer to the CR value than SS, reducing the alternatives’ weight ratios. This paper explains how AHP aids logical decision-making. Prioritizing pre-processing techniques with AHP can be a paradigm for other sentiment analysis stages. In short, this paper adds another contribution to the Big Data Analytics domain.

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Slums and its implication on security in Baghdad
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The research team seeks to study the phenomena of random housing in Iraqi society in general and Baghdad city in particular by standing on the causes behind this phenomena and its relation with security situation in Baghdad. The researchers adopted a theoretical and practical framework. The main objective is to diagnose the risks caused by the escalation of slums in Baghdad city. 

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Estimation of cellular immune response by evaluation of some cytokines in immunopathogenesis of chronic hepatitis B and C pre- and post- treated Iraqi patients (in vivo and in vitro)
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Two groups of chronic hepatitis B and C virus patients were divided into Pre-treated patients (25 CHB patients with positive HBs Ag for more than 6 months and 40 CHC patients), and post-treated patients [12 CHB patients (4, 6, and 2 were treated with lamivudine, IFN-? and combination of LMV + IFN-? respectively), and 27 patients for CHC (3, 13 and 11 patients were treated with Ribavirin, IFN-? and combination therapy (RBV+ IFN-?) respectively].These patients were followed up for 6 months. By using ELISA technique, levels of IL-6, IL-10, IFN-? and TNF-? were measured in vivo and in vitro (supernatant of PBMCs stimulated with PHA) and compared with healthy control. The mean level of IL-6, IL-10 and TNF-? in CHB patients showed significant dif

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Mon Nov 01 2021
Journal Name
Proceedings Of First International Conference On Mathematical Modeling And Computational Science: Icmmcs 2020
Study the Stability for Ordinary Differential Equations Using New Techniques via Numerical Methods
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Nonlinear differential equation stability is a very important feature of applied mathematics, as it has a wide variety of applications in both practical and physical life problems. The major object of the manuscript is to discuss and apply several techniques using modify the Krasovskii's method and the modify variable gradient method which are used to check the stability for some kinds of linear or nonlinear differential equations. Lyapunov function is constructed using the variable gradient method and Krasovskii’s method to estimate the stability of nonlinear systems. If the function of Lyapunov is positive, it implies that the nonlinear system is asymptotically stable. For the nonlinear systems, stability is still difficult even though

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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
Estimating the plain and negative tendonography techniques for evaluating injured tendon in rabbit
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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Mon Mar 25 2019
Journal Name
Al-academy
Digital Image Visual Communication in Internal Virtual Spaces between the Graphic Design and the Internal Design: وسام حسن هاشم - رغد منذر احمد
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The digital revolution had greatly affected the methods through which we communicate, starting from the basic concepts of the internet technology and the web content in addition to the important issues that concern the culture of the digital media, the internet governance and the variation in the digital age in general and the graphic and internal design in particular.
This research addresses an important topic that goes along with the scientific development in the field of the digital design, especially in the internal and graphic designs. This study consists of two sections: the first includes the problem of the study and the need for it. Starting from the problem of the research, there is no clear perception of the formal characte

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Engineering
Development of Spatial Data Infrastructure based on Free Data Integration
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In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Asset Utilization Efficiency and its effect on the sustainable Stockholder’s Wealth: Apply Study of Iraqi Companies listed on the Iraqi Stock Exchange
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The research discusses one of the most critical issues of corporate finance which is related to asset utilization efficiency. Researchers used internal growth rate as independent variable (Proxy of asset utilization efficiency) and sustainable growth rate-dependent variable (proxy of stockholders wealth). According to these two variables, researchers formulate major hypotheses (There is no significant effect of internal growth rate on sustainable growth rate), as well as two sub-hypotheses, examine the components of major variables. Sample of Iraqi industrial companies which listed in the Iraqi stock exchange selected to test and examine main hypotheses. Result of simple and multiple regressions explain there is a significant effect of i

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