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: "opportunistic and context aware affect sensing on smartphones the concept challenges and opportunities"
  Abstract: Opportunistic affect sensing offers unprecedented potential for capturing spontaneous affect, eliminating biases inherent in the controlled setting. Facial expression and voice are two major affective displays, but most affect sensing systems on smartphones avoid them due to extensive power requirements. Encouragingly, due to the recent advent of low-power DSP coprocessor and GPU technology, audio and video sensing are becoming more feasible on smartphones. To utilize opportunistically captured facial expressions and voice, gathering contextual information about the dynamic audiovisual stimuli is also important. This article discusses recent advances in affect sensing on smartphones and identifies the key barriers and potential solutions for implementing opportunistic and context-aware affect sensing on smartphone platforms. In addition to exploring the technical challenges (privacy, battery life, and robust algorithms), the authors also consider the challenges of recruiting and retaining mental health patients. Experimentation with mental health patients is difficult but crucial to showcase the importance and effectiveness of smartphone-centered affect sensing technology.

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)