human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "iot technologies for augmented human a survey"):
  Abstract: Internet of Things (IoT) technology has delivered new enablers for improving human abilities. These enablers promise an enhanced quality of life and professional efficiency; however, the synthesis of IoT and human augmentation technologies has also extended IoT-related challenges far beyond the current scope. These potential challenges associated with IoT-empowered Augmented Human (AH) have so far not been well-investigated. Thus, this article attempts to introduce readers to AH concept as well as summarize notable research challenges raised by such systems, in order to facilitate reader's further interest in this topic. The article considers emerging IoT applications for human augmentation, devices and design principles, connectivity demands, and security aspects.

Includes members:
  Member "residual energy based cluster head selection in wsns for iot application":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid heterogeneous routing scheme for improved network performance in wsns for animal tracking")
  Member "security and protocol exploit analysis of the 5g specifications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the current state of affairs in 5g security and the main remaining security challenges")
  Member "analysis of millimeter wave networked wearables in crowded environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "enclosed mmwave wearable networks feasibility and performance")
  Member "an overview of ieee 802 15 6 standard":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cross layer optimized routing with low duty cycle tdma across multiple wireless body area networks")

Question: Please tell me which class the source paper 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)