human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "trajectory based urban air mobility uam operations simulator tus"
  Abstract: Nowadays, the demand for optimized services in urban environments to provide better society wellness is increasing. In this sense, ground transportation in dense urban environments has been facing challenges for many years (e.g., congestion and resilience). One import outcome of the effort made toward the creation of new concepts for enhancing urban transportation is the Urban Air Mobility (UAM) concept. UAM aims at enhancing city transportation services using manned and unmanned vehicles. However, these operations bring many challenges to be faced, e.g., the interaction between the controller agent and autonomous vehicles. Furthermore, trajectory planning is not a simple task due to several factors. Firstly, the trajectories must consider a reduced minimum separation as eVTOL vehicle are expected to operate in complex urban environments. This leads the trajectory planning process to observe safety primitives more restrictively once the airspace is expected to comport many vehicles that follow small minimum separation standards. Thereupon, the main goal of the Trajectory-Based UAM Operations Simulator (TUS) is to simulate the Trajectory-Based UAM operations in urban environments considering the presence of both manned and unmanned eVTOL vehicles. For this, a Discrete Event Simulation (DES) approach is adopted, which considers an input (i.e., the eVTOL vehicles, their origin and destination, and their respective trajectories) and produces an output (which describes if the trajectories are safe and the elapsed operation time). The main contribution of this simulation tool is to provide a simulated environment for testing and measuring the effectiveness (e.g., flight duration) of trajectories planned for eVTOL vehicles.

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)