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bsj-6310
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or living in it to assist people in recognizing between a secured and an unsecured environment.  Geo-location, combined with new approaches and techniques, can be extremely useful in crime investigation. The aim is focused on comparative study between three supervised learning algorithms. Where learning used data sets to train and test it to get desired results on them. Various machine learning algorithms on the dataset of Boston city crime are Decision Tree, Naïve Bayes and Logistic Regression classifiers have been used here to predict the type of crime that happens in the area. The outputs of these methods are compared to each other to find the one model best fits this type of data with the best performance. From the results obtained, the Decision Tree demonstrated the highest result compared to Naïve Bayes and Logistic Regression.

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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Publication Date
Mon Aug 31 2015
Journal Name
Journal Of Theoretical And Applied Information Technology
EXAM QUESTIONS CLASSIFICATION BASED ON BLOOM’S TAXONOMY COGNITIVE LEVEL USING CLASSIFIERS COMBINATION
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Publication Date
Thu Dec 29 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Combinatorial Testing Approaches: A Systematic Review
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Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua

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Publication Date
Wed Oct 31 2018
Journal Name
Arab Science Heritage Journal
مناهج مناهج تحقيق المخطوطات دراسة مقارنة
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         لقد نشا علم التحقيق على ايدي المحدثين المسلمين الذين  وضعوا قواعد هذا  العلم  وظهرت مؤلفات  عدة في هذا المجال ، لكن ما قام به الاقدمون لم يشكل قواعد علم مستقل  بذاته ومنذ ظهور الطباعة بدأت حركة تحقيق المخطوطات ، وتعددت  مناهج التحقيق فكان للمستشرقين منهجهم الخاص وظهر منهج التحقيق والاخراج الفني والعلمي للمخطوط .

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
Analyzing the Literary Criticism Book Questions for High School Stage According to Bloom's Classification
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Abstract

 The current research aims to identify the analysis of the questions for the book of literary criticism for the preparatory stage according to Bloom's classification. The research community consists of (34) exercises and (45) questions. The researcher used the method of analyzing questions and prepared a preliminary list that includes criteria that are supposed to measure exercises, which were selected based on Bloom's classification and the extant literature related to the topic. The scales were exposed to a jury of experts and specialists in curricula and methods of teaching the Arabic language. The scales obtained a complete agreement. Thus, it was adapted to become a reliable instrument in this

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Publication Date
Thu Dec 15 2022
Journal Name
Arab World English Journal
Genre-Based Analysis of Selected Political Debates: A Discourse Analysis Study
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The researchers of the present study have conducted a genre analysis of two political debates between American presidential nominees in the 2016 and 2020 elections. The current study seeks to analyze the cognitive construction of political debates to evaluate the typical moves and strategies politicians use to express their communicative intentions and to reveal the language manifestations of those moves and strategies. To achieve the study’s aims, the researchers adopt Bhatia’s (1993) framework of cognitive construction supported by van Emeren’s (2010) pragma-dialectic framework. The study demonstrates that both presidents adhere to this genre structuring to further their political agendas. For a positive and promising image

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Publication Date
Tue Dec 01 2020
Journal Name
Gulf Economist
The Bayesian Estimation in Competing Risks Analysis for Discrete Survival Data under Dynamic Methodology with Application to Dialysis Patients in Basra/ Iraq
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Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

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