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Mining Deviations in Document Writing Style through Vector Dissimilarity
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     Doubts arise about the originality of a document when noticing a change in its writing style. This evidence to plagiarism has made the intrinsic approach for detecting plagiarism uncover the plagiarized passages through the analysis of the writing style for the suspicious document where a reference corpus to compare with is absent.      The proposed work aims at discovering the deviations in document writing style through applying several steps: Firstly, the entire document is segmented into disjointed segments wherein each corresponds to a paragraph in the original document. For the entire document and for each segment, center vectors comprising average  weight of their word  are constructed. Second, the degree of closeness is calculated through applying Cosine similarity to measure for each segment, the deviation of its center vector from the center vector of the entire document. Additionally, word n-gram length will be investigated to show its effect on the proposed system performance wherein, center vectors are computed considering word n-grams for different values of n (n= 1, 2, and 3). Performance evaluation of the proposed method was accomplished through the use of Precision, Recall, F-measure, Granularity, and Plagdet as evaluation measures. Moreover, PAN-PC-09 and PAN-PC-11 were used for detecting intrinsic plagiarism as evaluation corpora. It is shown that the proposed approach has achieved results that are comparable to the state-of-the-art methods. Positive impact was observed through discovering deviations in document writing style by computing weight vectors dissimilarity rather than calculating the difference between the word n-grams that exist in segments and their corresponding word n-grams in the suspicious document. Furthermore, when considering the length of word n-gram, better results were recorded for system performance when word bi-grams was used compared to word uni-grams and word tri-grams.

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Publication Date
Mon Jan 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Assessing Landsat Processing Levels and Support Vector Machine Classification
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The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
Pre-Writing Skills of Kindergarten Children Preparation
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The study aimed to design a test of pre-writing skills for public kindergartens in Baghdad city. The test consisted of (25) items applied on a sample of (150) kindergarteners to identify these skills as well as to identify the significant difference between male and female children and if there is a difference between pre-school children and kindergarteners. The results showed the presence of pre-writing skills with a high degree in kindergarten children. The differences were clear in these skills between male and female children and those in pre-school than those in kindergartens. The researcher suggested a number of recommendations and proposals.

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Publication Date
Sat Oct 12 2019
Journal Name
Journal Of The College Of Education For Women
The Style of combining Contradictions in Bany Ahmar Poetry
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This research deals with the technical configuration of the beautiful visions among Bany Ahmar poets reflected through the incarnation of beautiful artistic images that manifests itself clearly in the combination of two contradictories  simultaneously.

      The main conclusion is, the Andalusian poets try to use those fictional visions in search of aesthetic pleasure and values,  through forming an image from water and fire as two prominent contradicted elements to express the impact of the heat of wine which soon vanishes when it is mixed with water. By this, they show the beautiful side of nature that suggests joy and splendor.

     

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Brain Storming Style and its Singnificance in teaching geography
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                     The current research aims to know the method and strategy of rainstorming for students to open the door towards innovation and creativity in the field of teaching the subject of geography and the importance of brainstorming method and the studies that touched on it. The study also dealt with the steps of teaching the method of brainstorming and the most important (traditional and modern), and the difficulties of using the method of brainstorming in the teaching process, as well as explained the guidance to improve teaching using the method of brainstorming in the teaching p

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Publication Date
Tue Jun 17 2025
Journal Name
Research In Social Sciences
Using Chatbot and ChatGPT as Useful Tools in Scientific Academic Writing
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This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Mon Oct 10 2016
Journal Name
Iraqi Journal Of Science
Satellite image classification using KL-transformation and modified vector quantization
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In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Optimized Kalman filters for sensorless vector control induction motor drives
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<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
A Fuzzy Logic Controller Based Vector Control of IPMSM Drives
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This paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated

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