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.
Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.
Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are
... Show MoreThe present paper aims at investigating the linguistic image portrayed by UNICEF reports on the Iraqi child from a critical discourse analysis perspective during Covid19 pandemic (2020). The paper attempts to fill a gap in research literature concerning the linguistic construction of the Iraqi child by the UNICEF reports during the critical health crisis of Covid19. Van Leeuwen’s (2008) approach of social actor representation has been adopted for this purpose. From Van Leeuwen’s approach, the category of determination (single determination and overdetermination) has been selected to be the main analytical tool for its high compatibility with the set of objectives put forward to figure out how such a globally effective and
... Show Morehave suffered from deteriorating residential neighborhoods, poor economic, social and urban living conditions of the population and deteriorating the infrastructural and superior services. These problems were the secretions of these cities' rapid urbanization. Based on the principles of sustainable urban planning and in order to achieve adequate opportunities for the lives of the population and provide them with sustainable livelihoods, policies have emerged to upgrade along the lines of community participation and programmes to reform and develop those neighbourhoods, raise their efficiency and make them livable. Thus, the problem of research was identified "The absence of a comprehensive cognitive perception of the most prominent facto
... Show MoreThis study aims to derive a sustainable human development index for the Arab countries by using the principal components analysis, which can help in reducing the number of data in the case of multiple variables. This can be relied upon in the interpretation and tracking sustainable human development in the Arab countries in the view of the multiplicity of sustainable human development indicators and its huge data, beside the heterogeneity of countries in a range of characteristics associated with indicators of sustainable human development such as area, population, and economic activity. The study attempted to use the available data to the selected Arab countries for the recent years. This study concluded that a single inde
... Show MoreThe current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:
There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group
... Show MoreThis research aims to identify the reality of teaching political science research methods curriculum, to observe practices, and differences in teaching and learning between the Arab and Western universities. Moreover, it focuses on the difficulties that face students' acquisition of the course skills. The research uses the course model of some Western and Arab universities as case study.
This research shows that the curriculum do not reach yet the final form as other political science curriculums, and its upcoming changes will reflect the needs of stakeholders. The best method to teach this curriculum is to use applied learning in groups, learning by doing, and finally problem-based learning approach. Using optimal assessment deep
... Show MoreContinuous turbidimetric analysis (CTA) for a distinctive analytical application by employing a homemade analyser (NAG Dual & Solo 0-180°) which contained two consecutive detection zones (measuring cells 1 & 2) is described. The analyser works based on light-emitting diodes as a light source and a set of solar cells as a light detector for turbidity measurements without needing further fibres or lenses. Formation of a turbid precipitated product with yellow colour due to the reaction between the warfarin and the precipitation reagent (Potassium dichromate) is what the developed method is based on. The CTA method was applied to determine the warfarin in pure form and pharmaceu