human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "prediction of physical load level by machine learning analysis of heart activity after exercises"):
  with members:
    - "parallel statistical and machine learning methods for estimation of physical load"
    - "dnn driven speaker independent audio visual mask estimation for speech separation"
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale"

Connected through hyperedge HE-2 (induced by source paper "performance evaluation of deep learning networks for semantic segmentation of traffic stereo pair images"):
  with members:
    - "automatized generation of alphabets of symbols"
    - "icnet for real time semantic segmentation on high resolution images"
    - "enet a deep neural network architecture for real time semantic segmentation"
    - "a review on deep learning techniques applied to semantic segmentation"
    - "rethinking atrous convolution for semantic image segmentation"
    - "the cityscapes dataset for semantic urban scene understanding"
    - "pyramid scene parsing network"
    - "wider or deeper revisiting the resnet model for visual recognition"

Connected through hyperedge HE-3 (induced by source paper "open source dataset and machine learning techniques for automatic recognition of historical graffiti"):
  with members:
    - "capsule deep neural network for recognition of historical graffiti handwriting"
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "offline handwritten signature verification literature review"
    - "dynamic routing between capsules"
    - "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale"

Connected through hyperedge HE-4 (induced by source paper "gamification for education of the digitally native generation by means of virtual reality augmented reality machine learning and brain computing interfaces in museums"):
  with members:
    - "deep learning for fatigue estimation on the basis of multimodal human machine interactions"
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "automatized generation of alphabets of symbols"
    - "music transcription by deep learning with data and artificial semantic augmentation"
    - "performance analysis of open source machine learning frameworks for various parameters in single threaded and multi threaded modes"

Connected through hyperedge HE-5 (induced by source paper "deep learning for fatigue estimation on the basis of multimodal human machine interactions"):
  with members:
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "comparative performance analysis of neural networks architectures on h2o platform for various activation functions"
    - "comparative analysis of open source frameworks for machine learning with use case in single threaded and multi threaded modes"
    - "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale"

Connected through hyperedge HE-6 (induced by source paper "parallel statistical and machine learning methods for estimation of physical load"):
  with members:
    - "deep learning for fatigue estimation on the basis of multimodal human machine interactions"
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale"

Connected through hyperedge HE-7 (induced by source paper "music transcription by deep learning with data and artificial semantic augmentation"):
  with members:
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "an experimental analysis of the entanglement problem in neural network based music transcription systems"
    - "automatized generation of alphabets of symbols"
    - "comparative performance analysis of neural networks architectures on h2o platform for various activation functions"
    - "slice to volume medical image registration a survey"
    - "comparative analysis of open source frameworks for machine learning with use case in single threaded and multi threaded modes"

Connected through hyperedge HE-8 (induced by source paper "performance analysis of open source machine learning frameworks for various parameters in single threaded and multi threaded modes"):
  with members:
    - "deep learning for fatigue estimation on the basis of multimodal human machine interactions"
    - "augmented coaching ecosystem for non obtrusive adaptive personalized elderly care on the basis of cloud fog dew computing paradigm"
    - "automatized generation of alphabets of symbols"
    - "comparative performance analysis of neural networks architectures on h2o platform for various activation functions"
    - "comparative analysis of open source frameworks for machine learning with use case in single threaded and multi threaded modes"
    - "tensorflow a system for large scale machine learning"

Question: Please tell me which class the center node 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)