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.
En el contexto de la disponibilidad léxica, Esta investigación surge de la necesidad de enseñar, a los estudiantes extranjeros de comunicación que cursan sus estudios en nuestra universidad, el español especializado que realmente necesitan. La metodología disponibilidad léxica ofrece una oportunidad en cuanto a la elaboración de los manuales.
Abstract
This article presents the lexical availability as a practical tool, this research can be exploited didactically in the teaching of vocabulary as a foreign languages LE.
SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023
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To assess cultural competence among nursing students from nine countries to provide an international perspective on cultural competence.
A descriptive, cross‐sectional design.
A convenience sample of 2,163 nursing students from nine countries was surveyed using the Cultural Capacity Scale from April to November 2016.
The study found a moderate range of cultural competence among the students. The ability to teach and guide other nursing colleagues to displ
Soils that cause effective damages to engineer structures (such as pavement and foundation) are called problematic or difficult soils (include collapsible soil, expansive soil, etc.). These damages occur due to poor or unfavorited engineering properties, such as low shear strength, high compressibility, high volume changes, etc. In the case of expansive soil, the problem of the shrink-swell phenomenon, when the soil reacts with water, is more pronounced. To overcome such problems, soils can be treated or stabilized with many stabilization ways (mechanical, chemical, etc.). Such ways can amend the unfavorited soil properties. In this review, the pozzolanic materials have been selected to be presented and discussed as chem
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