Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classifier overperforms other classifiers that were examined in this research paper.
One of the most significant environmental issues facing the planet today is air pollution. Due to development in industry and population density, air pollution has lately gotten worse. Like many developing nations, Iraq suffers from air pollution, particularly in its urban areas with heavy industry. Our research was carried out in Baghdad's Al-Nahrawan neighbourhood. Recently, ground surveys and remote sensing were used to study the monitoring of air pollution. In order to extract different gaseous and particle data, Earth Data source, Google Earth Engine (GEE), and Geographic Information Systems (GIS) software were all employed. The findings demonstrated that there is a significant positive connection between data collected by ground-ba
... Show Morethis study aimed to study the effect of Cordia myxa extract on the growth and activities of the following types of bacteria : Escherichia coli , Pseudomonas aeruginosa, Proteus Spp., Klebsiella pneumoniae , Staphylococcus aureus, Streptococcus pyogenes , Bacillus subtilus, and the yeast Candida albicans .the results showed an inhibitory effect of the methanol extract on both the growth and activity of the tested microbes .this was reflected by the minimum inhibitory concentration ( MIC ) of different type of bacteria and the yeast.