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: "a kinematic information theoretic transmission scheme for goal directed movements"
  Abstract: We build on the variability of human movements by focusing on how the stochastic variance of the limb position varies over time. This implies analyzing a whole set of trajectories rather than a single one. We show, using real data previously acquired by two independent studies, that two distinct phases appear. The first phase, where the positional variance increases steadily, is followed by a second phase where it decreases toward zero. During the second phase, the problem of aiming can be reduced to a Shannon-like communication problem where information is transmitted from a "source" (determined by the position at the end of the first phase), to a "destination" (the movement's endpoint) over a "channel" perturbed by Gaussian noise, with the presence of a noiseless feedback link. We take advantage of a scheme by Elias, which provides a simple yet optimal solution to this problem and show that the rate C of decrease of variance during the second component is at best exponential. This result is observed on real data and C is found to be constant across instructions and task parameters, resulting in the unambiguously defined throughput that characterizes goal-directed movements via a simple measure in bit/second. The well-know Fitts' law is also derived in the case where the second phase dominates movement time, obtained for movements that require high precision.

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)