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: "full wafer redistribution and wafer embedding as key technologies for a multi scale neuromorphic hardware cluster"
  Abstract: Together with the Kirchhoff-Institute for Physics(KIP) the Fraunhofer IZM has developed a full wafer redistribution and embedding technology as base for a large-scale neuromorphic hardware system. The paper will give an overview of the neuromorphic computing platform at the KIP and the associated hardware requirements which drove the described technological developments. In the first phase of the project standard redistribution technologies from wafer level packaging were adapted to enable a high density reticle-to-reticle routing on 200mm CMOS wafers. Neighboring reticles were interconnected across the scribe lines with an 8{\mu}m pitch routing based on semi-additive copper metallization. Passivation by photo sensitive benzocyclobutene was used to enable a second intra-reticle routing layer. Final IO pads with flash gold were generated on top of each reticle. With that concept neuromorphic systems based on full wafers could be assembled and tested. The fabricated high density inter-reticle routing revealed a very high yield of larger than 99.9%. In order to allow an upscaling of the system size to a large number of wafers with feasible effort a full wafer embedding concept for printed circuit boards was developed and proven in the second phase of the project. The wafers were thinned to 250{\mu}m and laminated with additional prepreg layers and copper foils into a core material. After lamination of the PCB panel the reticle IOs of the embedded wafer were accessed by micro via drilling, copper electroplating, lithography and subtractive etching of the PCB wiring structure. The created wiring with 50um line width enabled an access of the reticle IOs on the embedded wafer as well as a board level routing. The panels with the embedded wafers were subsequently stressed with up to 1000 thermal cycles between 0C and 100C and have shown no severe failure formation over the cycle time.

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.ET(Emerging Technologies)