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 "mate robots simplifying my work the benefits and socioethical implications"):
  Abstract: With the increasing complexity of modern industrial automatic and robotic systems, a burden is placed on system operators, who are required to supervise and interact with very complex systems, typically under difficult and stressful conditions. To overcome these challenges, it is necessary to adopt a responsible approach based on an anthropocentric design methodology so that machines adapt to human capabilities rather than vice versa. In this article, we consider an integrated methodological design approach, referred to as measure, adapt, and teach (MATE), which consists of devising complex automatic or robotic solutions that measure the current operator's status and adapting the interaction accordingly, while providing him or her with the necessary skills and expertise to improve the interaction. A MATE system, shown in Figure 1, endeavors to be usable for all users, thus meeting the principles of inclusive design. However, the use of such a MATE system calls to attention several ethical and social implications, which are discussed in this article. Additionally, a discussion about which factors in the organization of companies are critical with respect to the introduction of a MATE system is presented.

Includes members:
  Member "methodological approach for the design of a complex inclusive human machine system":
    also connected through other hyperedges:
      (none)
  Member "towards modern inclusive factories a methodology for the development of smart adaptive human machine interfaces":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "behavioral petri net mining and automated analysis for human computer interaction recommendations in multi application environments")

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)