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: "non invasive induction link model for implantable biomedical microsystems pacemaker to monitor arrhythmic patients in body area networks"
  Abstract: In this paper, a non-invasive inductive link model for an Implantable Biomedical Microsystems (IBMs) such as, a pacemaker to monitor Arrhythmic Patients (APs) in Body Area Networks (BANs) is proposed. The model acts as a driving source to keep the batteries charged, inside a device called, pacemaker. The device monitors any drift from natural human heart beats, a condition of arrythmia and also in turn, produces electrical pulses that create forced rhythms that, matches with the original normal heart rhythms. It constantly sends a medical report to the health center to keep the medical personnel aware of the patient's conditions and let them handle any critical condition, before it actually happens. Two equivalent models are compared by carrying the simulations, based on the parameters of voltage gain and link efficiency. Results depict that the series tuned primary and parallel tuned secondary circuit achieves the best results for both the parameters, keeping in view the constraint of coupling co-efficient (k), which should be less than a value 0.45 as, desirable for the safety of body tissues.

Connected through hyperedge HE-1 (induced by source paper "experimentally based cross layer optimization for distributed wireless body to body networks"):
  with members:
    - "cooperative communications for sleep monitoring in wireless body area networks"

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.NI(Networking and Internet Architecture)