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: "kerman a hybrid lightweight tracking algorithm to enable smart surveillance as an edge service"
  Abstract: Edge computing pushes the cloud computing boundaries beyond uncertain network resource by leveraging computational processes close to the source and target of data. Time-sensitive and data-intensive video surveillance applications benefit from on-site or near-site data mining. In recent years, many smart video surveillance approaches are proposed for object detection and tracking by using Artificial Intelligence (AI) and Machine Learning (ML) algorithms. However, it is still hard to migrate those computing and data-intensive tasks from Cloud to Edge due to the high computational requirement. In this paper, we envision to achieve intelligent surveillance as an edge service by proposing a hybrid lightweight tracking algorithm named Kerman (Kernelized Kalman filter). Kerman is a decision tree based hybrid Kernelized Correlation Filter (KCF) algorithm proposed for human object tracking, which is coupled with a lightweight Convolutional Neural Network (L-CNN) for high performance. The proposed Kerman algorithm has been implemented on a couple of single board computers (SBC) as edge devices and validated using real-world surveillance video streams. The experimental results are promising that the Kerman algorithm is able to track the object of interest with a decent accuracy at a resource consumption affordable by edge devices.

Connected through hyperedge HE-1 (induced by source paper "i vise interactive video surveillance as an edge service using unsupervised feature queries"):
  with members:
    - "decentralized smart surveillance through microservices platform"
    - "a lightweight blockchain based privacy protection for smart surveillance at the edge"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "a microservice enabled architecture for smart surveillance using blockchain technology"
    - "real time index authentication for event oriented surveillance video query using blockchain"
    - "discovery of shared semantic spaces for multiscene video query and summarization"
    - "compositional human pose regression"
    - "cascaded pyramid network for multi person pose estimation"

Connected through hyperedge HE-2 (induced by source paper "i safe instant suspicious activity identification at the edge using fuzzy decision making"):
  with members:
    - "decentralized smart surveillance through microservices platform"
    - "blendmas a blockchain enabled decentralized microservices architecture for smart public safety"
    - "vstore a data store for analytics on large videos"
    - "real world anomaly detection in surveillance videos"
    - "focus querying large video datasets with low latency and low cost"
    - "real time index authentication for event oriented surveillance video query using blockchain"
    - "real time human detection as an edge service enabled by a lightweight cnn"
    - "posetrack a benchmark for human pose estimation and tracking"

Connected through hyperedge HE-3 (induced by source paper "decentralized smart surveillance through microservices platform"):
  with members:
    - "a study on smart online frame forging attacks against video surveillance system"
    - "blendmas a blockchain enabled decentralized microservices architecture for smart public safety"
    - "fog computing a taxonomy survey and future directions"
    - "a microservice enabled architecture for smart surveillance using blockchain technology"
    - "an exploration of blockchain enabled decentralized capability based access control strategy for space situation awareness"
    - "smart surveillance as an edge network service from harr cascade svm to a lightweight cnn"
    - "constructing trustworthy and safe communities on a blockchain enabled social credits system"
    - "real time index authentication for event oriented surveillance video query using blockchain"

Connected through hyperedge HE-4 (induced by source paper "blockchain methods for trusted avionics systems"):
  with members:
    - "decentralized smart surveillance through microservices platform"
    - "a microservice enabled architecture for smart surveillance using blockchain technology"
    - "smart surveillance as an edge network service from harr cascade svm to a lightweight cnn"
    - "constructing trustworthy and safe communities on a blockchain enabled social credits system"
    - "real time index authentication for event oriented surveillance video query using blockchain"
    - "real time human detection as an edge service enabled by a lightweight cnn"
    - "eiqis toward an event oriented indexable and queryable intelligent surveillance system"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"

Connected through hyperedge HE-5 (induced by source paper "blendmas a blockchain enabled decentralized microservices architecture for smart public safety"):
  with members:
    - "decentralized smart surveillance through microservices platform"
    - "a microservice enabled architecture for smart surveillance using blockchain technology"
    - "smart surveillance as an edge network service from harr cascade svm to a lightweight cnn"
    - "constructing trustworthy and safe communities on a blockchain enabled social credits system"
    - "real time index authentication for event oriented surveillance video query using blockchain"
    - "real time human detection as an edge service enabled by a lightweight cnn"
    - "eiqis toward an event oriented indexable and queryable intelligent surveillance system"

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)