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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
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
Effect of Carbon Nanoparticles on the Performance Efficiency of a Solar Water Heater
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Carbon nanoparticles are prepared by sonication using carbon black powder. The surface morphology of carbon black (CB) and carbon nanoparticles (CNPs) is investigated using scanning electron microscopy (SEM). The particles size ranges from 100 nm to 400 nm for CB and from 10 nm to 100 nm for CNPs. CNPs and CB are mixed with silicon glue of different ratios of 0.025, 0.2, 0.05, and 0.1 to synthesis films. The optical properties of the prepared films are investigated through reflectance and absorbance analyses. The ratio of 0.05 for CNPs and CB is the best for solar paint because of its higher solar water heater efficiency and is then added to the silicon glue . Temperature of cold water and temperature of hot water in storage tank were ta

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Effect of Gas Mixture on the Output Characteristics of a CW CO2 Laser
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In this work, the effect of partial amounts of gases in gas mixture of a CW CO2 laser on the output power was investigated. Also their effect on the condition determining the glow-discharge self-sustaining required for pumping the active medium was studied. Two fit relations were derived to predict the output laser power and the electric field to unit pressure ratio as functions to the partial amounts of gases. Results presented in this work could be used fruitfully to determine some of the optimum operational conditions of glow-discharge low-power CW CO2 lasers.

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Publication Date
Wed Feb 15 2023
Journal Name
Remote Sensing
Combining Remote Sensing Approaches for Detecting Marks of Archaeological and Demolished Constructions in Cahokia’s Grand Plaza, Southwestern Illinois
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Remote sensing data are increasingly being used in digital archaeology for the potential non-invasive detection of archaeological remains. The purpose of this research is to evaluate the capability of standalone (LiDAR and aerial photogrammetry) and integration/fusion remote sensing approaches in improving the prospecting and interpretation of archaeological remains in Cahokia’s Grand Plaza. Cahokia Mounds is an ancient area; it was the largest settlement of the Mississippian culture located in southwestern Illinois, USA. There are a limited number of studies combining LiDAR and aerial photogrammetry to extract archaeological features. This article, therefore, combines LiDAR with photogrammetric data to create new datasets and inv

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Publication Date
Tue Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization
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This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Tapered Splicing Points SMF-PCF-SMF Structure based on Mach-Zehnder interferometer for Enhanced Refractive Index Sensing
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Photonic crystal fiber interferometers (PCFIs) are widely used for sensing applications. This work presented solid core-PCFs based on Mach-Zehnder modal interferometer for sensing refractive index. The general structure of sensor was applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28).To apply modal interferometer theory collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). A high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted wavelength. This work studied a Mach-Zahnder interferometer refractive index sensor based on splicing point tapered SMF-PCF-SMF. Relation between refractive index sensitivity and tape

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Computer-based plagiarism detection techniques: A comparative study
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Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and

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Publication Date
Sat Oct 01 2022
Journal Name
Therapeutic Delivery
Particles-based Medicated Wound Dressings: A Comprehensive Review
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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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Publication Date
Sun Oct 01 2017
Journal Name
2017 47th European Microwave Conference (eumc)
A semiconductor based millimeter-wave waveguide junction circulator
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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
The effectiveness of the constructivist learning model in acquiring the Institute of Fine Arts' students of artistic analysis skills: اخلاص عبد القادر طاهر
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The constructivist learning model is one of the models of constructivist theory in learning, as it generally emphasizes the active role of the learner during learning, in addition to that the intellectual and actual participation in the various activities to help students gain the skills of analyzing artistic works. The current research aims to know the effectiveness of the constructivist learning model in the acquisition of the skills of the Institute of Fine Arts for the skills of (technical work analysis). To achieve the goal, the researcher formulated the following hypothesis: There are no statistically significant differences between the average scores of the experimental group students in the skill test for analyzing artworks befor

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