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Graph based text representation for document clustering
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Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship and meanings of words in the document. As a result the sparsity and semantic problem that is prevalent in textual document are not resolved. In this study, the problem of sparsity and semantic is reduced by proposing a graph based text representation method, namely dependency graph with the aim of improving the accuracy of document clustering. The dependency graph representation scheme is created through an accumulation of syntactic and semantic analysis. A sample of 20 news groups, dataset was used in this study. The text documents undergo pre-processing and syntactic parsing in order to identify the sentence structure. Then the semantic of words are modeled using dependency graph. The produced dependency graph is then used in the process of cluster analysis. K-means clustering technique was used in this study. The dependency graph based clustering result were compared with the popular text representation method, i.e. TFIDF and Ontology based text representation. The result shows that the dependency graph outperforms both TFIDF and Ontology based text representation. The findings proved that the proposed text representation method leads to more accurate document clustering results.

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
A Control Program for Hydropower Operation Based on Minimizing the Principal Stress Values on the Dam Body: Mosul Dam Case Study
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This study examines the vibrations produced by hydropower operations to improve embankment dam safety. This study consists of two parts: In the first part, ANSYS-CFX was used to generate a three-dimensional (3-D) finite volume (FV) model to simulate a vertical Francis turbine unit in the Mosul hydropower plant. The pressure pattern result of the turbine model was transformed into the dam body to show how the turbine unit's operation affects the dam's stability. The upstream reservoir conditions, various flow rates, and fully open inlet gates were considered. In the second part of this study, a 3-D FE Mosul dam model was simulated using an ANSYS program. The operational turbine model's water pressure pattern is conveyed t

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Power Sources
Impact of tetracyanoethylene plasticizer on PEO based solid polymer electrolytes for improved ionic conductivity and solid-state lithium-ion battery performance
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Poly(ethylene oxide) is a promising material for solid-state lithium batteries due to its safety, ease of processing, and compatibility with lithium. However, conventional linear PEO falls short of practical requirements due to its limited ionic conductivity, a consequence of the high crystallinity of its ethylene oxide chains. This crystallinity hinders the movement of lithium ions, limiting its performance in solid-state battery applications. In this study, we successfully prepared the plasticized solid polymer electrolytes (PSPEs) based on poly(ethylene oxide) (PEO)/ tetracyanoethylene (TCE) complexed with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt and studied the effect of TCE on structural, mechanical, electrical and elec

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Publication Date
Mon Oct 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
<b>Enhanced Multi-Objective Evolutionary Algorithm for Community Detection Using a Community Strength-Based Mutation Strategy</b>
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Community structures are fundamental in understanding the structure and functionality of complex networks. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of community detection. Recently, multi-objective evolutionary algorithms (MOEAs) have attracted many researchers to identify communities in static networks. Many algorithms have been proposed to find a solution that achieves a trade-off between exploring new areas of the solution space and improving the quality of existing solutions. In this trade-off is crucial; whereas exploitation improves existing solutions, it may fail to find better solutions from insufficiently explored regions o

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Publication Date
Sun Jan 01 2012
Journal Name
Tikrit Journal For Dental Sciences
Microleakage Evaluation of a Silorane-Based and Methacrylate-Based Packable and Nanofill Posterior Composites (in vitro comparative study)
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This study compared in vitro the microleakage of a new low shrink silorane-based posterior composite (Filtek™ P90) and two methacrylate-based composites: a packable posterior composite (Filtek™ P60) and a nanofill composite (Filtek™ Supreme XT) through dye penetration test. Thirty sound human upper premolars were used in this study. Standardized class V cavities were prepared at the buccal surface of each tooth. The teeth were then divided into three groups of ten teeth each: (Group 1: restored with Filtek™ P90, Group 2: restored with Filtek™ P60, and Group 3: restored with Filtek™ Supreme XT). Each composite system was used according to the manufacturer's instructions with their corresponding adhesive systems. The teeth were th

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem
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Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program for Children with Autism and their Mothers Based on the Picture Exchange Commination System to Confront Some of Basic Disorders for these Children
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Abstract

The current research aims to examine the effectiveness of a training program for children with autism and their mothers based on the Picture Exchange Communication System to confront some basic disorders in a sample of children with autism. The study sample was (16) children with autism and their mothers in the different centers in Taif city and Tabuk city. The researcher used the quasi-experimental approach, in which two groups were employed: an experimental group and a control group. Children aged ranged from (6-9) years old. In addition, it was used the following tools: a list of estimation of basic disorders for a child with autism between (6-9) years, and a training program for children with autism

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of The College Of Languages (jcl)
Theoretical asp ects of trans lation of a lite rary text in the fram ework of lingu istic and cult ural analysis: Теоретические асп екты перевода художес твенного текста в рам ках лингвокультурологического ана лиза
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          The present art icle discusses the prob lems of understanding and translating the lingu istic and cult ural aspect of a foreign lite rary text. The article considers the trans lation process through the pr ism of cult ural orientation. In the process of transl ation, the nati onal cultural iden tity should be expressed to the max imum extent, through all me ans of expre ssion that include imagery and inton ation. In addi tion to the author's sty le, special atte ntion should al so be pa id to tro pes, phraseological uni ts, colloquial wo rds and dial&n

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Hybrid Transform Based Denoising with Block Thresholding
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A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

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