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This paper aims at evaluating the level of groundwater vulnerability to pollution in Wadi Al-Waleh wells and South Amman area based on SINTACS model. The Wadi AlWaleh Catchment (WWC) is considered to be one of the most important sub-basins in the middle part of Jordan. This study creates a map of groundwater vulnerability that shows areas with potential pollution. Areas are then classified into units with different levels of vulnerability based on anthropogenic and hydrogeological factors. The parameters of the SINTACS model are rated and evaluated by weight numerical indices. The vulnerability parameter is set upon fixed percentage interval of the sub-basin's area. SINTACS index values have been categorized into four groups of pollution: very low (green), low (yellow), medium (orange), and medium to high (red). The results reveal that the units with very low levels of vulnerability to pollution cover an area of 0.17 km 2 . In addition, units with low, medium, and medium to high levels of vulnerability to pollution cover areas of 44.13, 1102.37, and 654.97 km 2 , respectively. The vulnerability maps show that most of the sub-surface area of WWC is characterized by medium to high levels of vulnerability to pollution, while units with very low and low vulnerability to pollution cover small areas of the western part of WWC. As well, the vulnerability maps show that there is moderate-high risk of pollution in the middle to eastern parts of WWC sub-basin. The risk of pollution in WWC mainly stems from intensive agricultural activities in the area.

Students in universities do not follow the prescribed course plan guide, which affects the registration process. In this research, we present an approach to tackle the problem of guide for plan of course sequence (GPCS) since that sequence may not be suitable for all students due to various conditions. The Ant Colony Optimization (ACO) algorithm is anticipated to be a suitable approach to solving such problems. Data on sequence of the courses registered by students of the Computer Science Department at Al Al-Bayt University over four years were collected for this study. The fundamental task was to find the suitable pheromone evaporation rate in ACO that generates the optimal GPCS by conducting an Adaptive Ant Colony Optimization (AACO) on the model that used the collected data. We found that 17 courses out of 31 were placed in semesters differing from the semesters preset in the course plan.