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PLAGIARISM DETECTION SYSTEM IN SCIENTIFIC PUBLICATION USING LSTM NETWORKS

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Publication Date
Sun Jul 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The Impact of the Constructive Scientific Stations Strategy on Achievement and Mind Habits for The Fourth Scientific students in biology

The study aimed at ideutifying the impact of scieutific skills in strategy and liabits of mind amony stueuts in tenth grade . The study demanded to choose a sampie that coutaiun (42) student of the fourth grade of the secondary school who were dirided into tow groups , the first is experimental studied according to scieutific skill strategy , and the other controlling , studied according to the  usualway . An achievement test  has been taken that adopted  staudard for mind skills as research tools that are applid after ascertaining  sincerity proved at the end of the experiment .The study has reached to the conclusion that there are statistically significant differnces in farour of the experiment group in both

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Medical Image Classification for Coronavirus Disease (COVID-19) Using Convolutional Neural Networks

     The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

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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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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection of Human Remain Using GPR Technique

    In this work, animal bones with different shapes and sizes were used to study the characteristics of the ground penetrating Radar system wares reflected by these bones. These bones were buried underground in different depths and surrounding media. The resulting data showed that the detection of buried bones with the GPR technology is highly dependent upon the surrounding media that the bones were buried in. Humidity is the main source of signal loss in such application because humidity results in low signal-to-noise ratio which leads to inability to distinguish between the signal reflected by bones from that reflected by the dopes  in the media such as rock .

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Copy Move Forgery Detection Using Forensic Images

     Digital images are open to several manipulations and dropped cost of compact  cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image  by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple

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Publication Date
Tue Dec 01 2009
Journal Name
2009 7th International Conference On Information, Communications And Signal Processing (icics)
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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Energy Consumption Analyzing in Single hop Transmission and Multi-hop Transmission for using Wireless Sensor Networks

Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem

 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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