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: "accelerometer based control of an industrial robotic arm"
  Abstract: Most of industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. In this paper is proposed an accelerometer-based system to control an industrial robot using two low-cost and small 3-axis wireless accelerometers. These accelerometers are attached to the human arms, capturing its behavior (gestures and postures). An Artificial Neural Network (ANN) trained with a back-propagation algorithm was used to recognize arm gestures and postures, which then will be used as input in the control of the robot. The aim is that the robot starts the movement almost at the same time as the user starts to perform a gesture or posture (low response time). The results show that the system allows the control of an industrial robot in an intuitive way. However, the achieved recognition rate of gestures and postures (92%) should be improved in future, keeping the compromise with the system response time (160 milliseconds). Finally, the results of some tests performed with an industrial robot are presented and discussed.

Connected through hyperedge HE-1 (induced by source paper "motion imitation based on sparsely sampled correspondence"):
  with members:
    - "high level programming and control for industrial robotics using a hand held accelerometer based input device for gesture and posture recognition"

Connected through hyperedge HE-2 (induced by source paper "real time and continuous hand gesture spotting an approach based on artificial neural networks"):
  with members:
    - "high level programming and control for industrial robotics using a hand held accelerometer based input device for gesture and posture recognition"

Connected through hyperedge HE-3 (induced by source paper "high level robot programming based on cad dealing with unpredictable environments"):
  with members:
    - "discretization and fitting of nominal data for autonomous robots"
    - "direct off line robot programming via a common cad package"
    - "an optimal fuzzy pi force motion controller to increase industrial robot autonomy"
    - "high level programming and control for industrial robotics using a hand held accelerometer based input device for gesture and posture recognition"

Connected through hyperedge HE-4 (induced by source paper "a low cost laser scanning solution for flexible robotic cells spray coating"):
  with members:
    - "high level programming and control for industrial robotics using a hand held accelerometer based input device for gesture and posture recognition"

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.RO(Robotics)