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 "user driven intelligent interface on the basis of multimodal augmented reality and brain computer interaction for people with functional disabilities"):
  Abstract: The analysis of the current integration attempts of some modes and use cases of human-to-machine interaction is presented. The new concept of the user-driven intelligent interface for accessibility is proposed on the basis of multimodal augmented reality and brain-computer interaction for various applications: in disabilities studies, education, home care, health care, eHealth, etc. The several use cases of multimodal augmentation are presented. The perspectives of the better human comprehension by the immediate feedback through neurophysical channels by means of brain-computer interaction are outlined. It is shown that brain–computer interface (BCI) technology provides new strategies to overcome limits of the currently available user interfaces, especially for people with functional disabilities. The results of the previous studies of the low end consumer and open-source BCI-devices allow us to conclude that combination of machine learning (ML), multimodal interactions (visual, sound, tactile) with BCI will profit from the immediate feedback from the actual neurophysical reactions classified by ML methods. In general, BCI in combination with other modes of AR interaction can deliver much more information than these types of interaction themselves. Even in the current state the combined AR-BCI interfaces could provide the highly adaptable and personal services, especially for people with functional disabilities.

Includes members:
  Member "deep learning for fatigue estimation on the basis of multimodal human machine interactions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on deep learning based brain computer interface recent advances and new frontiers")
  Member "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "prediction of physical load level by machine learning analysis of heart activity after exercises")
  Member "automatized generation of alphabets of symbols":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance evaluation of deep learning networks for semantic segmentation of traffic stereo pair images")
  Member "generating and estimating nonverbal alphabets for situated and multimodal communications":
    also connected through other hyperedges:
      (none)
  Member "performance analysis of open source machine learning frameworks for various parameters in single threaded and multi threaded modes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "response transformation and profit decomposition for revenue uplift modeling")
  Member "multi parametric statistical method for estimation of accumulated fatigue by sensors in ordinary gadgets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm")
  Member "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prediction of physical load level by machine learning analysis of heart activity after exercises")

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.HC(Human-Computer Interaction)