This study aims to identify changes in vegetation cover and its impact on the climate of Mosul City. The analytical method of the study relies on changes in Land Use/Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST); GIS technology was used to measure these statistics. Landsat (5,8) imagery was used to detect the change in vegetation cover change and land surface temperature during the study period from 2010 to 2022, where the unsupervised classification technique was used to determine LU variations. The results revealed significant changes among the LU classes during the study period, primarily due to human activities. The most prominent change in LU was the urban expansion of agricultural

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

The topic area of that’s research dealing with values which adopted by Iraqi people since 1980, many changes and variables which make many situations and skills which the life is suitable in war and conflicts times. That’s values like traditional and ordering, traditionalism mean the conservation about values s and tradition which society adopted its. The Iraqi society suffering from many changes since 1980-2003, the consequently of that’s changes make Iraqi citizen more interested about luxury needs like clothes, while decreasing the interested about liberty of thought, beauty, show evidence of identity, and openness of mind. The processing of values changes associated with political behavior of Iraqi people which lead to weaken o

The research aims to determine optimal urban planning and design indicators of the urban clusters form in hot arid zones through studying of three urban areas in Baghdad, analyzing their urban indicators which include floor area ratio (FAR), urban clusters height, building density or land coverage, green areas, paved areas, shading ratio and how they affect urban temperature. The research reached the conclusion that air outdoor temperature on urban areas affected primarily by shadows casted on the ground, the effect of shaded area equals (5) times the effect of paved areas and (3.7) times the effect of green areas, this means that increasing urban clusters height in hot arid zones could minimize air outdoor temperature, building