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ijs-2910
Inspecting Hybrid Data Mining Approaches in Decision Support Systems for Humanities Texts Criticism
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The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content.   When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniques in humanities when summarizing and eliciting automated decisions. This process relies on technological advancement and considers (1) the automated-decision support-techniques commonly used in humanities, (2) the performance evolution and the use of the stylometric approach in text-mining, and (3) the comparisons of the results of chunking text by using different attributes in Burrows' Delta method. This study also provides an overview of the efficiency of applying some selected data-mining (DM) methods with various text-mining techniques to support the critics' decision in artistry ‒ one field of humanities. The automatic choice of criticism in this field was supported by a hybrid approach to these procedures.

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Publication Date
Sun Jan 01 2012
Journal Name
Journal Of The College Of Languages (jcl)
Difficulties Faced by Engineering Students in Reading and Comprehending English Texts
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Reading is an interactive process that goes on between the reader and the text, resulting in comprehension. The text presents letters, words, sentences, and paragraphs that encode meaning. The reader uses knowledge, skills, and strategies to determine what that meaning is. Reading comprehension is much more than decoding; it results when the reader knows which skills and strategies are appropriate for the type oftext, and understands how to apply them to accomplish the reading purpose.Reading comprehension is important because without it reading is nothing more than tracking symbols on a page with your eyes and sounding them out leaving the reader with no information. Instead of promoting traditional approaches, reading should be ta

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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Publication Date
Sat May 16 2009
Journal Name
Journal Of Planner And Development
Information technology and replacement system in decision-making in the city
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IT has its impact on all aspects of life, including its planning and operations. Based on the assumption that the plan can adapt any technique as an analytical tool within broader dimensions to include society in general and meet the requirements of that society. They have neutral values, meaning and usefulness rather than being adopted as abstract goals or objectives so that the planner or the decision-maker can benefit greatly from them. This information technology is summarized in three main axes: First: Geographic Information Systems. Second: computer modeling. Third: visual simulation and the Internet. The problem of research is that the decision-making environment of the plan is surrounded by uncertain information-planning conditio

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Publication Date
Fri Sep 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Vapor-Liquid-Liquid Equilibrium (VLLE) Data for the Systems Ethyl acetate + Water, Toluene + Water and Toluene + Ethyl acetate + Water at 101.3 kPa. Using Modified Equilibrium Still
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Isobaric Vapor-Liquid-Liquid equilibrium data for the binary systems ethyl acetate + water, toluene + water and the ternary system toluene + ethyl acetate + water were determined by a modified equilibrium still, the still consisted of a boiling and a condensation sections supplied with mixers that helped to correct the composition of the recycled condensed liquid and the boiling temperature readings in the condensation and boiling sections respectively. The VLLE data where predicted and correlated using the Peng-Robinson Equation of State in the vapor phase and one of the activity coefficient models Wilson, NRTL, UNIQUAC and the UNIFAC in the liquid phase and also were correlated using the Peng-Robinson Equation of State in both the vapo

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Publication Date
Thu Oct 01 2020
Journal Name
Defence Technology
A novel facial emotion recognition scheme based on graph mining
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Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Developing Systems Engineering for Sustainable Infrastructure Projects
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Abstract<p>Globally, Sustainability is very quickly becoming a fundamental requirement of the construction industry as it delivers its projects; whether buildings or infrastructures. Throughout more than two decades, many modeling schemes, evaluation tools, and rating systems have been introduced en route to realizing sustainable construction. Many of these, however, lack consensus on evaluation criteria, a robust scientific model that captures the logic behind their sustainability performance evaluation, and therefore experience discrepancies between rated results and actual performance. Moreover, very few of the evaluation tools available satisfactorily address infrastructure projects. The res</p> ... Show More
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
The Impact of the Sowt Strategy on the Development of Systemic Intelligence among Students of the Ibn Rushd College of Education for the Humanities
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The aim of the current research is to identify the impact of the SWOT strategy on developing systemic intelligence among students of the Ibn Rushd College of Education for Human Sciences University of Baghdad / College of Education Ibn Rushd for Human Sciences. The current research community consists of (8590) male and female students, divided into (7) departments. The current research relied on one of the partial control designs, which is the design of non-random groups: experimental group and a control group with a pre and post-test. As for the research tool, It was represented by Tourmanin’s Systemic Intelligence Scale (2012) of (50) items that measure the eight components of systemic intelligence. The results of the Mann Whitney te

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Multilayer Perceptron for analyzing satellite data
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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