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: "connectivity of confined 3d networks with anisotropically radiating nodes"
  Abstract: Nodes in ad hoc networks with randomly oriented directional antenna patterns typically have fewer short links and more long links which can bridge together otherwise isolated subnetworks. This network feature is known to improve overall connectivity in 2D random networks operating at low channel path loss. To this end, we advance recently established results to obtain analytic expressions for the mean degree of 3D networks for simple but practical anisotropic gain profiles, including those of patch, dipole and end-fire array antennas. Our analysis reveals that for homogeneous systems (i.e. neglecting boundary effects) directional radiation patterns are superior to the isotropic case only when the path loss exponent is less than the spatial dimension. Moreover, we establish that ad hoc networks utilizing directional transmit and isotropic receive antennas (or vice versa) are always sub-optimally connected regardless of the environment path loss. We extend our analysis to investigate boundary effects in inhomogeneous systems, and study the geometrical reasons why directional radiating nodes are at a disadvantage to isotropic ones. Finally, we discuss multi-directional gain patterns consisting of many equally spaced lobes which could be used to mitigate boundary effects and improve overall network connectivity.

Connected through hyperedge HE-1 (induced by source paper "spatial networks with wireless applications"):
  with members:
    - "boundaries as an enhancement technique for physical layer security"
    - "on the capacity of fractal wireless networks with direct social interactions"
    - "correlated interference from uncorrelated users in bounded ad hoc networks with blockage"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "on the capacity of wireless networks with fractal and hierarchical social communications"
    - "boundaries can enhance physical layer security at high data rates"
    - "temporal correlation of interference in bounded mobile ad hoc networks with blockage"
    - "interference functionals in poisson networks"

Connected through hyperedge HE-2 (induced by source paper "low power wide area network analysis can lora scale"):
  with members:
    - "low power wide area networks an overview"
    - "low power wide area networks a survey"
    - "connectivity scaling laws in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "counting geodesic paths in 1 d vanets"):
  with members:
    - "maximum likelihood based multihop localization in wireless sensor networks"
    - "betweenness centrality in dense random geometric networks"

Connected through hyperedge HE-4 (induced by source paper "connectivity of cooperative ad hoc networks"):
  with members:
    - "multihop connectivity of ad hoc networks with randomly oriented directional antennas"
    - "location location location border effects in interference limited ad hoc networks"
    - "connectivity scaling laws in wireless networks"
    - "network connectivity in non convex domains with reflections"
    - "more is less connectivity in fractal regions"

Connected through hyperedge HE-5 (induced by source paper "connectivity scaling laws in wireless networks"):
  with members:
    - "location location location border effects in interference limited ad hoc networks"
    - "towards a better understanding of large scale network models"
    - "extremal properties of three dimensional sensor networks with applications"

Connected through hyperedge HE-6 (induced by source paper "network connectivity in non convex domains with reflections"):
  with members:
    - "an approximation of the first order marcum q function with application to network connectivity analysis"
    - "towards a better understanding of large scale network models"

Connected through hyperedge HE-7 (induced by source paper "directional antennas improve the link connectivity of interference limited ad hoc networks"):
  with members:
    - "multihop connectivity of ad hoc networks with randomly oriented directional antennas"

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.IT(Information Theory)