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A great opportunity for students that would like to major in or currently majoring in computer science, computer engineering, management information systems, information technology, or any IT related subjects to demonstrate and sharpen their problem solving and computing skills in addition to a chance to meet fellow students from other universities. Moreover, such a contest will allow students to participate in regional and world programming contest. In this contest, problems must be solved using C, C++, or JAVA.
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A contest that will put teams from different institutions around the UAE against each other.  The main objective of the competition is for students to work as a group to develop a secure website, exploit the vulnerabilities in each other's websites, and eventually harden their developed websites. An example of possible security threats and attacks: URL manipulation, SQL injection, and Cross Site Scripting.
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There is an ever increasing global interest in integrating renewable generation (especially wind and Photovoltaic (PV)) into power systems to meet the continuously increasing demand for electrical energy, at a time of diminishing fossil fuel reserves, and a rising awareness of their environmental hazards. In addition, developments in the electric vehicle market have created a ready application for hydrogen-based fuel cells and these are expected to play an important role in powering the car of the future. In this competition, students will gain knowledge of how electrical energy can be generated from different types of renewable energy resources, namely wind, solar, and fuel cells. Participants will compete to use their gained knowledge and problem solving skills in building a renewable based microgrid system (a small electrical network with renewable sources and electric loads) in a number of challenging scenarios.
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During this contest, students are required to utilize machine learning algorithms to construct usable models to identify and classify objects from real image datasets. Students are expected to be able to handle image datasets and extract relevant images and features to appropriately train their constructed models. In addition, they are expected to use and fine-tune existing machine learning algorithms such as Support Vector Machine (SVM), decision trees (Random Forest), K-nearest neighbor algorithm, deep neural networks and others. The constructed models should hold high classification accuracy, precision, recall, sensitivity, and specificity for mass deployment.Download PDF