Preferred Language
Articles
/
MxeEP48BVTCNdQwCLmYJ
A study on predicting crime rates through machine learning and data mining using text
...Show More Authors
Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based on the percentage of an accuracy measure of the previous work, are surveyed and introduced, with the aim of producing a concise review of using these algorithms in crime prediction. It is expected that this review study will be helpful for presenting such techniques to crime researchers in addition to supporting future research to develop these techniques for crime analysis by presenting some crime definition, prediction systems challenges and classifications with a comparative study. It was proved though literature, that supervised learning approaches were used in more studies for crime prediction than other approaches, and Logistic Regression is the most powerful method in predicting crime.</p>
Scopus Clarivate Crossref
View Publication
Publication Date
Mon Feb 13 2023
Journal Name
Journal Of Educational And Psychological Researches
A Blended Learning Program Based on the Next Generation Standards (NYS) to Develop the Teaching Performance of Middle School Mathematics Teachers and Some Students’ Future Thinking Skills
...Show More Authors

Abstract

The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical

... Show More
View Publication Preview PDF
Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Study of Gamma — irradiation effects on the Polymethylmethacrylate (PMMA) Using (PAL) Method
...Show More Authors

Gamma - irradiation effect on polymethylmethacrylate (PMMA) samples has been studied using Positron Annihilation Lifetime (PAL) method. The orthopositronium (o-Ps) lifetime τ3, hence the o-ps parameters, the volume hole size (Vh) and the free volume fraction (Ꞙh) in the irradiated samples were measured as a function of gamma-irradiation dose up to 28.05 kGy. It has been shown that τ 3, Vh, and Ꞙh, are increasing in general with increasing gamma-dose, to reach a maximum percentage increment of 22.42% in τ3, 60% in Vh and 29.5% in Ꞙh, at. 2.55 kGy, whereas τ2 reaches maximum increment of 119. 7% at 7.65 kGy. The results s

... Show More
View Publication Preview PDF
Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The Effectiveness Of the Poetic Text Between the Presence and Absence in Abu Firas al_Hamdani Romyate
...Show More Authors

Abu Firas al- Hamdani is one of the most prominent abbasid poets Who characterized their poetry with high artistic quality especially in his Romyate which blended the quality of feelings of grief, sorrow, longing and nostalgia that makes sensitive self conflict that stems with time from one hand and with place on the other hand. Because we are dealing with a poet lived west spatial coercive which it has been hurt him within a time conflict swinging between despair and some times patience and hope other times between the present and his painful reality also between the past and the beautiful times.
This researcher is to stand on this Romyat by monitoring effectiveness of the poetic text based on conflict between the presenc

... Show More
View Publication Preview PDF
Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters
...Show More Authors

      In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process,  where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Mar 01 2025
Journal Name
Results In Engineering
Advancing asphalt binder performance through nanomaterial and polymer modification: Experimental and statistical insights
...Show More Authors

View Publication
Scopus (9)
Crossref (9)
Scopus Clarivate Crossref
Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
...Show More Authors

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

... Show More
View Publication Preview PDF
Crossref (5)
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
...Show More Authors

View Publication Preview PDF
Scopus (11)
Crossref (10)
Scopus Crossref
Publication Date
Tue Oct 10 2023
Journal Name
2023 3rd International Conference On Emerging Smart Technologies And Applications (esmarta)
Perceived Trust of Stakeholders: Predicting the Use of COBIT 2019 to Reduce Information Asymmetry
...Show More Authors

Perceived Trust of Stakeholders: Predicting the Use of COBIT 2019 to Reduce Information Asymmetry

View Publication
Scopus (5)
Crossref (4)
Scopus Crossref
Publication Date
Thu Apr 06 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Impact of a Scenario-Based Learning Model in Mathematics Achievement and Mental Motivation for High School Students
...Show More Authors

Crossref (3)
Crossref
Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
...Show More Authors

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

... Show More
View Publication
Scopus (6)
Crossref (4)
Scopus Clarivate Crossref