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: "on advisability of designing short length qc ldpc codes using perfect difference families"
  Abstract: A simple and general definition of quasi cyclic low density parity check (QC LDPC) codes which are constructed based on circulant permutation matrices (CPM) is proposed. As an special case of this definition, we first represent one type of so called combinatorially designed multiple edge protograph codes. The code construction is mainly based on perfect difference families (PDF) and is called Construction 1. Secondly, using the proposed Construction 1 along with a technique named as column dispersion technique (CDT), we design several types of multiple-edge CPM QC LDPC codes (codes with Construction 2) in a wide range of rates, lengths, girths and minimum distances. Parameters of some of these codes are reported in tables. Also included in this paper are the multiplicities of short simple cycles of length up to 10 in Tanner graph of our constructed codes. Our experimental results for short to moderate length codes show that although minimum distances of codes play an important role in waterfall region, the higher the number of short simple cycles is, the better (sharper) the waterfall is. The performances of many codes such as WiMAX, PEG, array, MacKay, algebraic and combinatorial, and also, symmetrical codes have compared with our constructed codes. Based on our numerical results and regardless of how a code is constructed, those with higher number of short simple cycles and higher minimum distances, have better waterfalls.

Connected through hyperedge HE-1 (induced by source paper "design and analysis of time invariant sc ldpc convolutional codes with small constraint length"):
  with members:
    - "spatially coupled ldpc codes constructed from protographs"
    - "construction of high rate regular quasi cyclic ldpc codes based on cyclic difference families"
    - "quasi cyclic ldpc codes influence of proto and tanner graph structure on minimum hamming distance upper bounds"
    - "progressive differences convolutional low density parity check codes"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "deriving good ldpc convolutional codes from ldpc block codes"
    - "terminated ldpc convolutional codes with thresholds close to capacity"

Connected through hyperedge HE-2 (induced by source paper "design and analysis of time invariant sc ldpc codes with small constraint length"):
  with members:
    - "spatially coupled ldpc codes constructed from protographs"
    - "hierarchical and high girth qc ldpc codes"
    - "construction of high rate regular quasi cyclic ldpc codes based on cyclic difference families"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "searching for voltage graph based ldpc tailbiting codes with large girth"
    - "progressive differences convolutional low density parity check codes"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "deriving good ldpc convolutional codes from ldpc block codes"

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)