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Using Retrieved Sources for Semantic and Lexical Plagiarism Detection

     Plagiarism is described as using someone else's ideas or work without their permission. Using lexical and semantic text similarity notions, this paper presents a plagiarism detection system for examining suspicious texts against available sources on the Web. The user can upload suspicious files in pdf or docx formats. The system will search three popular search engines for the source text (Google, Bing, and Yahoo) and try to identify the top five results for each search engine on the first retrieved page. The corpus is made up of the downloaded files and scraped web page text of the search engines' results. The corpus text and suspicious documents will then be encoded as vectors. For lexical plagiarism detection, the system will leverage Jaccard similarity and Term Frequency-Inverse Document Frequency (TFIDF) techniques, while for semantic plagiarism detection, Doc2Vec and Sentence Bidirectional Encoder Representations from Transformers (SBERT) intelligent text representation models will be used. Following that, the system compares the suspicious text to the corpus text. Finally, a generated plagiarism report will show the total plagiarism ratio, the plagiarism ratio from each source, and other details.

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
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Publication Date
Wed Apr 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Plagiarism on the Quality of Scientific Researches “Empirical Study”

The purpose of this research is to study the quality of scientific research at the University of Baghdad in light of scientific piracy and plagiarism of research and results and attribute it to others intentionally or unintentionally. Proactive writing such as stealing ideas or synthesizing the results of one another over others and its negative impact on the quality of scientific outputs and the reputation of educational organizations through an exploratory study in the faculties of the University of Baghdad, scientific and humanitarian. As for the aims of the study, it was determined by determining the negative impact of piracy on scientific research. A Likert five-point scale was used in this research. The research community c

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of The College Of Languages (jcl)
(comparative analysis of phraseological units in the lexical-semantic field "on the material of Arabic and Russian languages"): (сопоставительный анализ фразеологических единиц лексико-семантического поля " на материале арабского и русского языков")

Establishing the systemic character of vocabulary, its relationship with other language systems, their interdependence creates the possibility of a comprehensive scientific study and description of the lexical system of each language, as well as contrastive comparative studies of several languages, including their phraseological composition.

It is known that not all words-components of phraseological units are equivalent in their role in the formation of the semantic content of phraseological units. In this regard, it is necessary to introduce the concept of a lexical dominant. To this we include words, which are kind of centers around which the entire semantic complex of phraseological units, the entire set of its words-componen

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Root (GUM) and its derivatives between Lexical Sematics and Semantics Koranic

As the word can fluctuate between central and peripheral dlalten it represents the first lexical meaning and the second represents the meaning that gain by the context in which it appear so this research came to show signs that can be acquired the root ( GUM ) and its derivatives from the contexts in which it is mentioned in the Koran as well as siqnificant Lexical if this research is divided on two first is eating Lexical semantics , the second handled connotations in the Koran was based on what the commentators and concemed with the meanings of the Koran and the owners Almagamat in astatement that the semantic .

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Publication Date
Sun Mar 06 2022
Journal Name
Cogent Arts &humanities
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Molecular Detection of Enterotoxin Genes of Multiresistant Staphylococcus aureus Isolates from Different Sources of Food

Foodborne diseases are a major risk for human health. Millions of people become sick as a result of eating contaminated food with microorganisms that cause diseases. S.  aureus is considered as one of the most important pathogenic bacteria, having the ability to  activate certain genes that encode for heat stable enterotoxins and cause Staphylococcal food poisoning. Thus, this study aimed to determine the prevalence of multi resistant Staphylococcus aureus that produce enterotoxins in different sources of food . Forty nine isolates were identified as S.aureus, according to morphological and biochemical tests. They were isolated from 387 different food samples from several randomly covered restaurants

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Edge detection for Diabetic Retinopathy using fuzzy logic

Diabetic retinopathy is an eye disease, because of pressure in eye nerve fiber. It is a major cause of blindness in middle as well as older age groups; therefore it is essential to diagnose it earlier. Some of the challenges are in the diagnosis of the disease is detection edges of the image, may be some important edges are missed outcome the noise around the corners.
Wherefore, in order to reduce these effects in this paper, we proposed a new technique for edge detection using traditional operators in combination with fuzzy logic based on fuzzy inference system. The results show that the proposed fuzzy edge detection technique better than of traditional techniques, where vascular are markedly detected over the original.

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors

Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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