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 the effects of battery imperfections in an energy harvesting device"
  Abstract: Energy Harvesting allows the devices in a Wireless Sensor Network to recharge their batteries through environmental energy sources. While in the literature the main focus is on devices with ideal batteries, in reality several inefficiencies have to be considered to correctly design the operating regimes of an Energy Harvesting Device (EHD). In this work we describe how the throughput optimization problem changes under \emph{real battery} constraints in an EHD. In particular, we consider imperfect knowledge of the state of charge of the battery and storage inefficiencies, \emph{i.e.}, part of the harvested energy is wasted in the battery recharging process. We formulate the problem as a Markov Decision Process, basing our model on some realistic observations about transmission, consumption and harvesting power. We find the performance upper bound with a real battery and numerically discuss the novelty introduced by the real battery effects. We show that using the \emph{old} policies obtained without considering the real battery effects is strongly sub-optimal and may even result in zero throughput.

Connected through hyperedge HE-1 (induced by source paper "rf energy harvesting sensor networks for healthcare of animals opportunities and challenges"):
  with members:
    - "energy harvesting wireless communications a review of recent advances"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

Connected through hyperedge HE-2 (induced by source paper "battery recharge time of a stochastic linear and non linear energy harvesting system"):
  with members:
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "optimal energy allocation for wireless communications with energy harvesting constraints"
    - "transmission with energy harvesting nodes in fading wireless channels optimal policies"
    - "optimum transmission policies for battery limited energy harvesting nodes"
    - "optimal packet scheduling in an energy harvesting communication system"

Connected through hyperedge HE-3 (induced by source paper "battery powered devices in wpcns"):
  with members:
    - "optimal energy and data routing in networks with energy cooperation"
    - "wireless power meets energy harvesting a joint energy allocation approach in ofdm based system"
    - "decentralized transmission policies for energy harvesting devices"
    - "achievable secrecy rates of an energy harvesting device"
    - "wireless powered communication opportunities and challenges"
    - "optimal adaptive random multiaccess in energy harvesting wireless sensor networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "energy harvesting networks with energy cooperation procrastinating policies"

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)