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: "analytical survey of wearable sensors"
  Abstract: Wearable sensors in Wireless Body Area Networks (WBANs) provide health and physical activity monitoring. Modern communication systems have extended this monitoring remotely. In this survey, various types of wearable sensors discussed, their medical applications like ECG, EEG, blood pressure, detection of blood glucose level, pulse rate, respiration rate and non medical applications like daily exercise monitoring and motion detection of different body parts. Different types of noise removing filters also discussed at the end that are helpful in to remove noise from ECG signals. Main purpose of this survey is to provide a platform for researchers in wearable sensors for WBANs.

Connected through hyperedge HE-1 (induced by source paper "distance aware relaying energy efficient dare to monitor patients in multi hop body area sensor networks"):
  with members:
    - "eddeec enhanced developed distributed energy efficient clustering for heterogeneous wireless sensor networks"
    - "ubiquitous healthcare in wireless body area networks a survey"
    - "energy efficient mac protocols in wireless body area sensor networks a survey"
    - "on modeling geometric joint sink mobility with delay tolerant cluster less wireless sensor networks"
    - "analyzing delay in wireless multi hop heterogeneous body area networks"
    - "srp ms a new routing protocol for delay tolerant wireless sensor networks"
    - "adaptive reliable medium access control protocol for wireless body area networks"
    - "analysis and modeling experiment performance parameters of routing protocols in manets and vanets"

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.SY(Systems and Control)