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: "crowdsourcing real time viral disease and pest information a case of nation wide cassava disease surveillance in a developing country"
  Abstract: In most developing countries, a huge proportion of the national food basket is supported by small subsistence agricultural systems. A major challenge to these systems is disease and pest attacks which have a devastating effect on the smallholder farmers that depend on these systems for their livelihoods. A key component of any proposed solution is a good disease surveillance network. However, current surveillance efforts are unable to provide sufficient data for monitoring such phenomena over a vast geographic area efficiently and effectively due to limited resources, both human and financial. Crowdsourcing with farmer crowds that have access to mobile phones offers a viable option to provide all year round real-time surveillance data on viral disease and pest incidence and severity. This work presents a mobile ad hoc surveillance system for monitoring viral diseases and pests in cassava. We present results from a pilot in Uganda where this system was deployed for 76 weeks. We discuss the participation behaviours of the crowds with mobile smartphones as well as the effects of several incentives applied.

Connected through hyperedge HE-1 (induced by source paper "keyword spotter model for crop pest and disease monitoring from community radio data"):
  with members:
    - "mobile community sensing with smallholder farmers in a developing nation a scaled pilot for crop health monitoring"
    - "efficient keyword spotting using dilated convolutions and gating"
    - "deep residual learning for small footprint keyword spotting"

Connected through hyperedge HE-2 (induced by source paper "mechanism design for social good"):
  with members:
    - "using search queries to understand health information needs in africa"
    - "fairness at equilibrium in the labor market"

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)