Capture The Flag competitions and games have been employed in cybersecurity in addition to formal education. The goal of this study is to examine students’ browsing activities in completing CTF challenges. To achieve the goal, we developed a student observatory that allows us to monitor their activities. We can use students’ browsing activities to understand students’ learning process for CTF challenges while completing them and, therefore, bring insights into Computer Security education. The student observatory developed in the study is a Chrome Extension, CTF browsing monitor, that collects the URLs visited, the percentages of webpages viewed by participants, and the time stamps on each visit. There will also be a short survey containing three questions about the webpage just viewed for non-search engine URLs to further gain participants’ perspectives on the webpage they just view.

Mobile crowd sensing (MCS) is a promising sensing paradigm that effectively gathers and evaluates data collected from the real world. With a large number of users and tasks, one of the fundamental problems is how to allocate these tasks to each user with the consideration of distance traveled by all users, maximum distance traveled by each user, the number of total users recruited, and time sensitivity for each task. Thus, this study investigates the task allocation in task-abundant MCS. In particular, there are two scenarios studied: one-to-one mapping (each user can only fulfill one task) and one-to multiple mapping (each user can fulfill multiple tasks) between users and tasks. This research uses real-world data from the D4D dataset, containing 50,000 users’ phone call records and cell phone tower locations. The algorithms used to match tasks to users are bipartite matching through repeated augmenting paths and maximum flow (one-to-one mapping) and greedy algorithms (one-to-multiple mapping). The results show that 1. bipartite matching algorithms (one-to-one) present lower task completeness rates but better (smaller) distance/user value; 2. there is a trade-off existing between distance traveled and user participation in one-to-multiple mapping; 3. selecting the minimum distance algorithm may lead to smaller loss compared to the minimum user algorithm, given the same weighting for 1 km traveled and one user recruited.

Oil spillage has caused serious environmental issues around the world. Therefore, interests in hydrophobic material have raised among scientists to separate oil/water as it can only allow oil to pass through but not water. An interest has been drawn to a stainless-steel wire net supported FAU zeolite membrane for oil/water separation. However, FAU zeolite membrane is a hydrophilic material. In order to change FAU zeolite membrane from hydrophilic to hydrophobic, post-synthesis may be a feasible solution. Perfluorooctyltriethoxysilane (POTS) is a chemical compound that is largely used to modify the surface of a material to gain a hydrophobic property, thus it may be able to modify the FAU zeolite membrane through post-synthesis to achieve a hydrophobic property without changing FAU crystalline structure. The hydrophobic property can therefore allow FAU membrane to separate oil/water, hopefully remains the advantages of FAU membrane and stainless-steel wire net.