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: "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
  Abstract: Today, wearable internet-of-things (wIoT) devices continuously flood the cloud data centers at an enormous rate. This increases a demand to deploy an edge infrastructure for computing, intelligence, and storage close to the users. The emerging paradigm of fog computing could play an important role to make wIoT more efficient and affordable. Fog computing is known as the cloud on the ground. This paper presents an end-to-end architecture that performs data conditioning and intelligent filtering for generating smart analytics from wearable data. In wIoT, wearable sensor devices serve on one end while the cloud backend offers services on the other end. We developed a prototype of smart fog gateway (a middle layer) using Intel Edison and Raspberry Pi. We discussed the role of the smart fog gateway in orchestrating the process of data conditioning, intelligent filtering, smart analytics, and selective transfer to the cloud for long-term storage and temporal variability monitoring. We benchmarked the performance of developed prototypes on real-world data from smart e-textile gloves. Results demonstrated the usability and potential of proposed architecture for converting the real-world data into useful analytics while making use of knowledge-based models. In this way, the smart fog gateway enhances the end-to-end interaction between wearables (sensor devices) and the cloud.

Connected through hyperedge HE-1 (induced by source paper "healthfog an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments"):
  with members:
    - "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"
    - "scalable and accurate deep learning for electronic health records"
    - "fogbus a blockchain based lightweight framework for edge and fog computing"
    - "foglearn leveraging fog based machine learning for smart system big data analytics"
    - "gram graph based attention model for healthcare representation learning"
    - "aneka a software platform for net based cloud computing"

Connected through hyperedge HE-2 (induced by source paper "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"):
  with members:
    - "salient object detection a survey"
    - "yolov3 an incremental improvement"
    - "fogbus a blockchain based lightweight framework for edge and fog computing"
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "you only look once unified real time object detection"
    - "aneka a software platform for net based cloud computing"

Connected through hyperedge HE-3 (induced by source paper "fog computing survey of trends architectures requirements and research directions"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "fog computing for sustainable smart cities a survey"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "fog computing principles architectures and applications"
    - "fog data enhancing telehealth big data through fog computing"
    - "big data computing and clouds"

Connected through hyperedge HE-4 (induced by source paper "smartear smartwatch based unsupervised learning for multi modal signal analysis in opportunistic sensing framework"):
  with members:
    - "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things"
    - "soa fog secure service oriented edge computing architecture for smart health big data analytics"
    - "fog computing in medical internet of things architecture implementation and applications"
    - "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"

Connected through hyperedge HE-5 (induced by source paper "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things"):
  with members:
    - "fog computing in medical internet of things architecture implementation and applications"
    - "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data"
    - "harmonic sum based method for heart rate estimation using ppg signals affected with motion artifacts"
    - "fit a fog computing device for speech teletreatments"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-6 (induced by source paper "fog computing in medical internet of things architecture implementation and applications"):
  with members:
    - "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data"
    - "harmonic sum based method for heart rate estimation using ppg signals affected with motion artifacts"
    - "foggis fog computing for geospatial big data analytics"
    - "fit a fog computing device for speech teletreatments"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-7 (induced by source paper "fog computing based sdi framework for mineral resources information infrastructure management in india"):
  with members:
    - "fog computing in medical internet of things architecture implementation and applications"
    - "foggis fog computing for geospatial big data analytics"
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fit a fog computing device for speech teletreatments"
    - "fog computing principles architectures and applications"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-8 (induced by source paper "soa fog secure service oriented edge computing architecture for smart health big data analytics"):
  with members:
    - "fog computing for sustainable smart cities a survey"
    - "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things"
    - "fog computing in medical internet of things architecture implementation and applications"
    - "foggis fog computing for geospatial big data analytics"
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fog data enhancing telehealth big data through fog computing"

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.DC(Distributed, Parallel, and Cluster Computing)