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: "deep learning for fatigue estimation on the basis of multimodal human machine interactions"
  Abstract: The new method is proposed to monitor the level of current physical load and accumulated fatigue by several objective and subjective characteristics. It was applied to the dataset targeted to estimate the physical load and fatigue by several statistical and machine learning methods. The data from peripheral sensors (accelerometer, GPS, gyroscope, magnetometer) and brain-computing interface (electroencephalography) were collected, integrated, and analyzed by several statistical and machine learning methods (moment analysis, cluster analysis, principal component analysis, etc.). The hypothesis 1 was presented and proved that physical activity can be classified not only by objective parameters, but by subjective parameters also. The hypothesis 2 (experienced physical load and subsequent restoration as fatigue level can be estimated quantitatively and distinctive patterns can be recognized) was presented and some ways to prove it were demonstrated. Several "physical load" and "fatigue" metrics were proposed. The results presented allow to extend application of the machine learning methods for characterization of complex human activity patterns (for example, to estimate their actual physical load and fatigue, and give cautions and advice).

Connected through hyperedge HE-1 (induced by source paper "a survey on deep learning based brain computer interface recent advances and new frontiers"):
  with members:
    - "deep learning based electroencephalography analysis a systematic review"
    - "adversarial variational embedding for robust semi supervised learning"
    - "spatial temporal recurrent neural network for emotion recognition"
    - "an automated system for epilepsy detection using eeg brain signals based on deep learning approach"
    - "on the classification of ssvep based dry eeg signals via convolutional neural networks"
    - "eegnet a compact convolutional neural network for eeg based brain computer interfaces"
    - "compact convolutional neural networks for classification of asynchronous steady state visual evoked potentials"
    - "hierarchical internal representation of spectral features in deep convolutional networks trained for eeg decoding"

Connected through hyperedge HE-2 (induced by source paper "responsible and representative multimodal data acquisition and analysis on auditability benchmarking confidence data reliance explainability"):
  with members:
    - "gatekeeping algorithms with human ethical bias the ethics of algorithms in archives libraries and society"
    - "multimodal machine learning a survey and taxonomy"
    - "explainable artificial intelligence understanding visualizing and interpreting deep learning models"
    - "a community s perspective on the status and future of peer review in software engineering"
    - "a survey on measuring indirect discrimination in machine learning"

Connected through hyperedge HE-3 (induced by source paper "chest x ray analysis of tuberculosis by deep learning with segmentation and augmentation"):
  with members:
    - "deep learning with lung segmentation and bone shadow exclusion techniques for chest x ray analysis of lung cancer"
    - "dimensionality reduction in deep learning for chest x ray analysis of lung cancer"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "comparative performance analysis of neural networks architectures on h2o platform for various activation functions"
    - "chestx ray8 hospital scale chest x ray database and benchmarks on weakly supervised classification and localization of common thorax diseases"
    - "comparative analysis of open source frameworks for machine learning with use case in single threaded and multi threaded modes"
    - "performance analysis of open source machine learning frameworks for various parameters 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-4 (induced by source paper "dimensionality reduction in deep learning for chest x ray analysis of lung cancer"):
  with members:
    - "deep learning with lung segmentation and bone shadow exclusion techniques for chest x ray analysis of lung cancer"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "comparative performance analysis of neural networks architectures on h2o platform for various activation functions"
    - "chestx ray8 hospital scale chest x ray database and benchmarks on weakly supervised classification and localization of common thorax diseases"
    - "comparative analysis of open source frameworks for machine learning with use case in single threaded and multi threaded modes"
    - "performance analysis of open source machine learning frameworks for various parameters 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"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"

Connected through hyperedge HE-5 (induced by source paper "deep learning with lung segmentation and bone shadow exclusion techniques for chest x ray analysis of lung cancer"):
  with members:
    - "dimensionality reduction in deep learning for chest x ray analysis of lung cancer"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "chestx ray8 hospital scale chest x ray database and benchmarks on weakly supervised classification and localization of common thorax diseases"
    - "performance analysis of open source machine learning frameworks for various parameters 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"
    - "u net convolutional networks for biomedical image segmentation"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"

Connected through hyperedge HE-6 (induced by source paper "user driven intelligent interface on the basis of multimodal augmented reality and brain computer interaction for people with functional disabilities"):
  with members:
    - "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"
    - "generating and estimating nonverbal alphabets for situated and multimodal communications"
    - "performance analysis of open source machine learning frameworks for various parameters in single threaded and multi threaded modes"
    - "multi parametric statistical method for estimation of accumulated fatigue by sensors in ordinary gadgets"
    - "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 "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:
    - "user driven intelligent interface on the basis of multimodal augmented reality and brain computer interaction for people with functional disabilities"
    - "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-8 (induced by source paper "parallel statistical and machine learning methods for estimation of physical load"):
  with members:
    - "user driven intelligent interface on the basis of multimodal augmented reality and brain computer interaction for people with functional disabilities"
    - "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"

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.CY(Computers and Society)