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: "realistic indoor path loss modeling for regular wifi operations in india"
  Abstract: Indoor wireless communication using Wireless Fidelity (WiFi) is becoming a major need for the success of Internet of Things (IoT) and cloud robotics in both developed and developing countries. With different operating conditions, interference, obstacles and type of building materials used, it is difficult to predict the path loss components in an indoor environment, which are crucial for the network design. It has been observed that the indoor path loss models proposed for western countries cannot be directly used in Indian scenarios due to variations in building materials utilized, floor plans, etc. In this paper, we have proposed a non-deterministic statistical indoor path loss model- Tata Indoor Path Loss Model (T-IPLM) which can be used for the 2.4 - 2.5 GHz, Industrial Scientific and Medical (ISM) band. To propose and validate, we have conducted several drive tests with different conditions such as busy office premise with obstacles, open office premise, corridor, canteen, and multi-storey office locations, etc. We have also compared T-IPLM with popular path loss models such as ITU-R and Log-distance; T-IPLM matches closely with the drive test results as compared to other models. We believe that T-IPLM model can be used extensively to design accurate indoor communication networks required for regular WiFi communications and deployment and operations of IoT and cloud robotics.

Connected through hyperedge HE-1 (induced by source paper "802 11g signal strength evaluation in an industrial environment"):
  with members:
    - "achieving data dissemination with security using fiware and intel software guard extensions sgx"
    - "agri info cloud based autonomic system for delivering agriculture as a service"

Connected through hyperedge HE-2 (induced by source paper "measurement characterization and modeling of lora technology in multi floor buildings"):
  with members:
    - "lorawan in the wild measurements from the things network"
    - "in building wideband partition loss measurements at 2 5 and 60 ghz"

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)