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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
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effects of Long-Term Operation and High Temperature on Material Properties of Austenitic Stainless Steel Type 321H
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Changes in mechanical properties of material as a result of service in different conditions can be provided by mechanical testing to assist the estimation of current internal situation of these materials, or the degree of deterioration may exist in furnaces serviced at high temperature and exceed their design life. Because of the rarity works on austenitic stainless steel material type AISI 321H, in this work, ultimate tensile strength, yield strength, elongation, hardness, and absorbed energy by impact are evaluated based on experimental data obtained from mechanical testing. Samples of tubes are extracted from furnace belong to hydrotreaterunit, also samples from un-used tube material are used to make comparisons between these properti

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Star model –model of organization design and reflections of its variables and dimensions of health performance on-filed study in medical city hospital
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Abstract

      The goal of current research to describe and diagnose the level of attention of doctors to design and regulatory dimensions, (strategic vision, organizational structure, organizational processes, business systems, personnel), and the performance of hospitals and dimensions, in six hospitals in medicine and selected a sample for research, as well as identify organizational design effect in the performance of hospitals and dimensions (efficiency, the development of human resources, patient satisfaction, achieve financial results, quality of health care).

 Research has focused in part theoretical on key variables to look organizational des

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Investigating the Influence of Precursor Concentration on the Photodegradation of Methylene Blue using Biosynthesized ZnO from Pometia pinnata Leaf Extracts
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The ZnO nanoparticles were synthesized at various precursor concentrations i.e. 0.05, 0.1, and 0.5 M by biosynthesis method based on Pometia pinnata Leaf Extracts. Initial nanoparticle concentration influenced the optical bandgap, shape, and structure of nanoparticles. The photodegradation process was carried out under UV illumination. The efficiency of MB degradation was determined by measuring the decrease in MB concentration and by analyzing the optical absorption at 663 nm recorded by UV-Vis spectroscopy. Results showed that the biosynthesized ZnO nanoparticles exhibited efficient photodegradation of MB, with a maximum degradation rate of 80% after 90 minutes of exposure to UV-C light. The study highlights the potential of Pometia pi

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Instruction Program on Teachers’ Performance of Counseling for Primary School Pupils regarding Attention Deficit and Hyperactivity Disorder
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Objective(s): To evaluate teachers’ performance of counseling for pupils with Attention Deficit and Hyperactivity Disorder, to identify the relationship between Teachers’ Performance of Counselling for Pupils with Attention Deficit and Hyperactivity Disorder and their demographic.

Methodology: A quasi-experimental (pre-posttest) design was carried out to evaluate teachers’ performance of counseling for pupils with Attention Deficit and Hyperactivity Disorder, at Al-Firdous mixed primary School and to find out the association between teachers' performance about Attention Deficit and Hyperactivity Disorder and their socio-demographic characteristic. The study was started from 18th September 2

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Impact of the Lean Thinking on the Rationalization Costs & Achieving Customer Satisfaction: An applied Research at Ur State company Electrical Cables industries
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The research explored the impact of applying lean thinking With all that carries this term of goals, trends, principles, foundations and concepts, The possibility of applying it in institutions, including Ur public company, an industrial company, And the only one in Iraq specialized in the manufacture of cables, Electrical Wires and the aluminum industry ,Which has been applied to the curriculum of lean thinking , The problem of research is that the institutions, including the company (research sample), adopt and practice traditional administrative, financial and technical methods without relying on modern curricula and ideas, including the subject of our research, In order to achieve the research objectives, the research was divided int

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Assessing the Iraqi general budget in light of corruption and fluctuations in oil prices, and their repercussions on unemployment rates after 2003
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The researcher highlighted the general budget in Iraq for the period (2003-2018) facing the challenges of administrative and financial corruption, in addition to the fluctuations in oil prices, the repercussions and many problems suffered and will suffer the Iraqi government in the process of preparing the general budget of the state and weak contribution of the agricultural and industrial sectors and other economic sectors and neglect altogether, oil has become the main supplier in funding Iraq's budget after 2003, and the impact on the unemployment rates in Iraq, which recorded fluctuating rates and then increased during the period (2012-2018) to achieve this, an inductive method was adopted, using theoretical and descriptive a

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Publication Date
Tue Apr 04 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFET OF SOME ISOLATION FROM FUGI BAGHDAD HOSPITAL ON PHYSIOLOGY OF LIVER, KIDNEY AND TESTIS IN ALBINO MALE MICE.: EFFET OF SOME ISOLATION FROM FUGI BAGHDAD HOSPITAL ON PHYSIOLOGY OF LIVER, KIDNEY AND TESTIS IN ALBINO MALE MICE.
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Some types of the fungus Aspergillus were isolated from some hospitals in the city of Baghdad (Imam Ali Hospital and Sadr General Hospital). The samples were taken by Transport media at a rate of three replicates of each place isolated from samples from different places within the hospital (waste, baths, the sick beds, corridors and room floors) for the purpose of isolating and diagnosing the fungus on the Czapeck Dox Agar media. It was noticed that the spread rate of fungus Aspergillus was 70% compared to other species that have emerged during the isolation process of the Sabouraud's Dextrose Agar media. The species A.niger (56.25%) was considered the most common type of fungus visible during the isolation process of the Imam Ali Hospit

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