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 "smartear smartwatch based unsupervised learning for multi modal signal analysis in opportunistic sensing framework"):
  Abstract: Wrist-bands such as smartwatches have become an unobtrusive interface for collecting physiological and contextual data from users. Smartwatches are being used for smart healthcare, telecare, and wellness monitoring. In this paper, we used data collected from the AnEAR framework leveraging smartwatches to gather and store physiological data from patients in naturalistic settings. This data included temperature, galvanic skin response (GSR), acceleration, and heart rate (HR). In particular, we focused on HR and acceleration, as these two modalities are often correlated. Since the data was unlabeled we relied on unsupervised learning for multi-modal signal analysis. We propose using k-means clustering, GMM clustering, and Self-Organizing maps based on Neural Networks for group the multi-modal data into homogeneous clusters. This strategy helped in discovering latent structures in our data.

Includes members:
  Member "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "healthfog an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments")
  Member "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "soa fog secure service oriented edge computing architecture for smart health big data analytics")
  Member "soa fog secure service oriented edge computing architecture for smart health big data analytics":
    also connected through other hyperedges:
      (none)
  Member "fog computing in medical internet of things architecture implementation and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "embedded deep learning in ophthalmology making ophthalmic imaging smarter")
  Member "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things")
  Member "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey of fog computing and communication current researches and future directions")
  Member "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things")

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.CY(Computers and Society)