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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 Mar 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system

Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Technical and Economic Evaluation of Electricity Generation and Storage Using Renewable Energy Sources on Socotra Island, Yemen

     Renewable energy sources are a promising hope for avoiding many environmental and economic problems such as the problems of climate change and environmental pollution resulting from fossil fuels combustion, in addition to the problems of oil derivatives high prices and their absence in many countries, which in turn affected the rise in electricity prices. Yemen is considered one of the countries most affected by electricity prices rise due to lack of oil derivatives as a result of the ongoing wars in Yemen. This paper presents a technical and economic study of renewable energy sources for producing and storing electricity. It gives a clear scientific and economic vision for implementation of these projects in one of the Yemeni i

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Publication Date
Sat May 08 2021
Journal Name
Iraqi Journal Of Science
EEG Signals Analysis for Epileptic Seizure Detection Using DWT Method with SVM and KNN Classifiers

Epilepsy is a critical neurological disorder with critical influences on the way of living of its victims and prominent features such as persistent convulsion periods followed by unconsciousness. Electroencephalogram (EEG) is one of the commonly used devices for seizure recognition and epilepsy detection. Recognition of convulsions using EEG waves takes a relatively long time because it is conducted physically by epileptologists. The EEG signals are analyzed and categorized, after being captured, into two types, which are normal or abnormal (indicating an epileptic seizure).  This study relies on EEG signals which are provided by Arrhythmia Database. Thus, this work is a step beyond the traditional database mission of delivering use

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Skin Detection using Improved ID3 Algorithm

Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
A Proposed Background Modeling Algorithm for Moving Object Detection Using Statistical Measures

Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach.

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Publication Date
Wed Jul 24 2024
Journal Name
Journal Of Plant Protection Research
Developing smart sprayer for weed control using an object detection algorithm (yolov5)

Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Development of Low-Temperature Atmospheric Plasma Jet Sources for Biological Applications

     The research aims to develop and build a plasma jet system operating under atmospheric pressure.for biological purposes. The advanced plasma system consists of a power supply and a plasma torch. The source of the development of the system is a previous laboratory system that was developed by changing the voltage and frequency of the power supply, as the power provider equips the system with a voltage in the form of a sine wave whose value is fixed at about (7.5kV) peak to peak and its frequency is about (28 kHz). The plasma torch consists of a teflon tube with of width of (10 m ) located at (10mm)  from the end of the tube. The current waveform and voltage wave were measured using a current and voltage sensor and an oscilloscop

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Detection a New Antiseptic Resistant Variant of qac Gene in Some Multi Drug Resistant Staphylococcus aureus Isolated from Different Clinical Sources

The increasing use of antiseptic compounds creates selective pressure cause emergence of antiseptic resistance among Staphylococcus aureus .Resistance mechanism of antiseptic is driven mainly by multi drug resistant (MDR) efflux protein.Sixty five isolates of S.aureuswere collected from different clinical sources and subjected to 11 antibiotics most of them are recognized by efflux systems as extruded substrates. Range of efflux activity was estimated using cartwheel method. Simultaneous discrimination of antiseptic coding genes (qacA/B, smr and norA)as well as nuc and mecA genes among multidrug resistantS.aureus(MRSA) isolates was preformed using multiplex PCR assay

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Plants Leaf Diseases Detection Using Deep Learning

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

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