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: "optimal detection for diffusion based molecular timing channels"
  Abstract: This work studies optimal detection for communication over diffusion-based molecular timing (DBMT) channels. The transmitter simultaneously releases multiple information particles, where the information is encoded in the time of release. The receiver decodes the transmitted information based on the random time of arrival of the information particles, which is modeled as an additive noise channel. For a DBMT channel without flow, this noise follows the L\'evy distribution. Under this channel model, the maximum-likelihood (ML) detector is derived and shown to have high computational complexity. It is also shown that under ML detection, releasing multiple particles improves performance, while for any additive channel with $\alpha$-stable noise where $\alpha<1$ (such as the DBMT channel), under linear processing at the receiver, releasing multiple particles degrades performance relative to releasing a single particle. Hence, a new low-complexity detector, which is based on the first arrival (FA) among all the transmitted particles, is proposed. It is shown that for a small number of released particles, the performance of the FA detector is very close to that of the ML detector. On the other hand, error exponent analysis shows that the performance of the two detectors differ when the number of released particles is large.

Connected through hyperedge HE-1 (induced by source paper "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques"):
  with members:
    - "magnetic nanoparticle based molecular communication in microfluidic environments"
    - "diffusion based molecular communication with limited molecule production rate"
    - "stochastic channel modeling for diffusive mobile molecular communication systems"
    - "exploiting diversity in molecular timing channels via order statistics"
    - "experimental molecular communication testbed based on magnetic nanoparticles in duct flow"
    - "diversity gain of one shot communication over molecular timing channels"
    - "a novel experimental platform for in vessel multi chemical molecular communications"
    - "on the design of matched filters for molecule counting receivers"

Connected through hyperedge HE-2 (induced by source paper "a novel time based modulation scheme in time asynchronous channels for molecular communications"):
  with members:
    - "spatial modulation for molecular communication"
    - "exploiting diversity in molecular timing channels via order statistics"
    - "channel modeling for diffusive molecular communication a tutorial review"
    - "diversity gain of one shot communication over molecular timing channels"
    - "on the capacity of diffusion based molecular timing channels"
    - "on the impact of time synchronization in molecular timing channels"
    - "a molecular communications model for drug delivery"
    - "tcp like molecular communications"

Connected through hyperedge HE-3 (induced by source paper "on the impact of time synchronization in molecular timing channels"):
  with members:
    - "a comprehensive survey of recent advancements in molecular communication"
    - "stable distributions as noise models for molecular communication"
    - "improving receiver performance of diffusive molecular communication with enzymes"
    - "tcp like molecular communications"
    - "tabletop molecular communication text messages through chemical signals"
    - "novel modulation techniques using isomers as messenger molecules for nano communication networks via diffusion"

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.IT(Information Theory)