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 "through wall person localization using transceivers in motion"):
  Abstract: We develop novel methods for device-free localization (DFL) using transceivers in motion. Such localization technologies are useful in various cross-layer applications/protocols including those that are related to security situations where it is important to know the presence and position of an unauthorized person; in monitoring the daily activities of elderly or special needs individuals; or in emergency situations when police or firefighters can use the locations of people inside of a building in order to save lives. We propose that transceivers mounted on autonomous vehicles could be both quickly deployed and kept moving to ``sweep'' an area for changes in the channel that would indicate the location of moving people and objects. The challenge is that changes to channel measurements are introduced both by changes in the environment and from motion of the transceivers. In this paper, we demonstrate a method to detect human movement despite transceiver motion using ultra-wideband impulse radar (UWB-IR) transceivers. The measurements reliably detect a person's presence on a link line despite small-scale fading. We explore via multiple experiments the ability of mobile UWB-IR transceivers, moving outside of the walls of a room, to measure many lines crossing through the room and accurately locate a person inside within 0.25 m average error.

Includes members:
  Member "channel sounding for the masses low complexity gnu 802 11b channel impulse response estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "veni vidi dixi reliable wireless communication with depth images")
  Member "hidden markov estimation of bistatic range from cluttered ultra wideband impulse responses":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "never use labels signal strength based bayesian device free localization in changing environments")
  Member "nuzzer a large scale device free passive localization system for wireless environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an analysis of device free and device based wifi localization systems")

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.ET(Emerging Technologies)