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 "a survey on acoustic sensing"):
  Abstract: The rise of Internet-of-Things (IoT) has brought many new sensing mechanisms. Among these mechanisms, acoustic sensing attracts much attention in recent years. Acoustic sensing exploits acoustic sensors beyond their primary uses, namely recording and playing, to enable interesting applications and new user experience. In this paper, we present the first survey of recent advances in acoustic sensing using commodity hardware. We propose a general framework that categorizes main building blocks of acoustic sensing systems. This framework consists of three layers, i.e., the physical layer, processing layer, and application layer. We highlight different sensing approaches in the processing layer and fundamental design considerations in the physical layer. Many existing and potential applications including context-aware applications, human-computer interface, and aerial acoustic communications are presented in depth. Challenges and future research trends are also discussed.

Includes members:
  Member "dolphinattack inaudible voice commands":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ghostimage perception domain attacks against vision based object classification systems")
  Member "going deeper into first person activity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "symbiotic attention with privileged information for egocentric action recognition")
  Member "p cnn pose based cnn features for action recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on 3d skeleton based action recognition using learning method")
  Member "wigest a ubiquitous wifi based gesture recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "solargest ubiquitous and battery free gesture recognition using solar cells")
  Member "very deep convolutional networks for large scale image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "discrimination aware network pruning for deep model compression")

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.SD(Sound)