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: "it s the human that matters accurate user orientation estimation for mobile computing applications"
  Abstract: Ubiquity of Internet-connected and sensor-equipped portable devices sparked a new set of mobile computing applications that leverage the proliferating sensing capabilities of smart-phones. For many of these applications, accurate estimation of the user heading, as compared to the phone heading, is of paramount importance. This is of special importance for many crowd-sensing applications, where the phone can be carried in arbitrary positions and orientations relative to the user body. Current state-of-the-art focus mainly on estimating the phone orientation, require the phone to be placed in a particular position, require user intervention, and/or do not work accurately indoors; which limits their ubiquitous usability in different applications. In this paper we present Humaine, a novel system to reliably and accurately estimate the user orientation relative to the Earth coordinate system. #R##N#Humaine requires no prior-configuration nor user intervention and works accurately indoors and outdoors for arbitrary cell phone positions and orientations relative to the user body. The system applies statistical analysis techniques to the inertial sensors widely available on today's cell phones to estimate both the phone and user orientation. Implementation of the system on different Android devices with 170 experiments performed at different indoor and outdoor testbeds shows that Humaine significantly outperforms the state-of-the-art in diverse scenarios, achieving a median accuracy of $15^\circ$ averaged over a wide variety of phone positions. This is $558\%$ better than the-state-of-the-art. The accuracy is bounded by the error in the inertial sensors readings and can be enhanced with more accurate sensors and sensor fusion.

Connected through hyperedge HE-1 (induced by source paper "security properties of gait for mobile device pairing"):
  with members:
    - "demo of bandana body area network device to device authentication using natural gait"
    - "vnect real time 3d human pose estimation with a single rgb camera"

Connected through hyperedge HE-2 (induced by source paper "transitlabel a crowd sensing system for automatic labeling of transit stations semantics"):
  with members:
    - "a robust zero calibration rf based localization system for realistic environments"
    - "the diversity and scale matter ubiquitous transportation mode detection using single cell tower information"
    - "ubibreathe a ubiquitous non invasive wifi based breathing estimator"
    - "map a crowd sensing system for automatic map semantics identification"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "crowdinside automatic construction of indoor floorplans"
    - "a hidden markov model for localization using low end gsm cell phones"

Connected through hyperedge HE-3 (induced by source paper "a robust zero calibration rf based localization system for realistic environments"):
  with members:
    - "transitlabel a crowd sensing system for automatic labeling of transit stations semantics"
    - "lanequest an accurate and energy efficient lane detection system"
    - "map a crowd sensing system for automatic map semantics identification"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "crowdinside automatic construction of indoor floorplans"
    - "a hidden markov model for localization using low end gsm cell phones"

Connected through hyperedge HE-4 (induced by source paper "semmatch road semantics based accurate map matching for challenging positioning data"):
  with members:
    - "lanequest an accurate and energy efficient lane detection system"
    - "map a crowd sensing system for automatic map semantics identification"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"
    - "cellsense a probabilistic rssi based gsm positioning system"
    - "gac energy efficient hybrid gps accelerometer compass gsm localization"
    - "a hidden markov model for localization using low end gsm cell phones"
    - "on line viterbi algorithm for analysis of long biological sequences"

Connected through hyperedge HE-5 (induced by source paper "lanequest an accurate and energy efficient lane detection system"):
  with members:
    - "map a crowd sensing system for automatic map semantics identification"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"
    - "cellsense a probabilistic rssi based gsm positioning system"
    - "a hidden markov model for localization using low end gsm cell phones"
    - "markov localization for mobile robots in dynamic environments"

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.CY(Computers and Society)