Papers by Abdus Salam Azad
A Web-Based System for Efficient Contact Tracing Query in a Large Spatio-Temporal Database
Proceedings of the 28th International Conference on Advances in Geographic Information Systems, 2020
In this demonstration, we present a web based system for the novel contact tracing query (CTQ) th... more In this demonstration, we present a web based system for the novel contact tracing query (CTQ) that finds users who have come into direct contact with the query user or indirect contact via the already contacted users from a large spatio-temporal database. The CTQ is of paramount importance in the era of new COVID-19 pandemic world for identifying people who came into close spatial and temporal proximity with persons carrying an infectious disease. We demonstrate a multi-level index named QzR-tree, that considers the space coverage and the co-visiting patterns of the trajectories to group users who are likely to meet. More specifically, we use a quadtree to partition user movement traces along with a linear ordering and use the space-time mapping to group users with an R-tree. We develop a web-based demo system to show the effectiveness of the QzR-tree for the CTQ. The web-based system essentially uses a PostgreSQL database to store user trajectories, and indexes these trajectories ...
IEEE Transactions on Cybernetics, 2017
and Technology, has been accepted as satisfactory in partial fulfillment of the requirements for ... more and Technology, has been accepted as satisfactory in partial fulfillment of the requirements for tlle degree of Master of Science in Computer Science and Engineering and approved as to its style and contents. Examination held on January 14, 2017.
The capability of reinforcement learning (RL) agent directly depends on the diversity of learning... more The capability of reinforcement learning (RL) agent directly depends on the diversity of learning scenarios the environment generates and how closely it captures real-world situations. However, existing environments/simulators lack the support to systematically model distributions over initial states and transition dynamics. Furthermore, in complex domains such as soccer, the space of possible scenarios is infinite, which makes it impossible for one research group to provide a comprehensive set of scenarios to train, test, and benchmark RL algorithms. To address this issue, for the first time, we adopt an existing formal scenario specification language, SCENIC, to intuitively model and generate interactive scenarios. We interfaced SCENIC to Google Research Soccer environment to create a platform called SCENIC4RL. Using this platform, we provide a dataset consisting of 36 scenario programs encoded in SCENIC and demonstration data generated from a subset of them. We share our experime...
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Papers by Abdus Salam Azad