Home / Journals / JQC / Vol.4, No.1, 2022
  • Open Access

    ARTICLE

    Online News Sentiment Classification Using DistilBERT

    Samuel Kofi Akpatsa1,*, Hang Lei1, Xiaoyu Li1, Victor-Hillary Kofi Setornyo Obeng1, Ezekiel Mensah Martey1, Prince Clement Addo2, Duncan Dodzi Fiawoo3
    Journal of Quantum Computing, Vol.4, No.1, pp. 1-11, 2022, DOI:10.32604/jqc.2022.026658
    Abstract The ability of pre-trained BERT model to achieve outstanding performances on many Natural Language Processing (NLP) tasks has attracted the attention of researchers in recent times. However, the huge computational and memory requirements have hampered its widespread deployment on devices with limited resources. The concept of knowledge distillation has shown to produce smaller and faster distilled models with less trainable parameters and intended for resource-constrained environments. The distilled models can be fine-tuned with great performance on a wider range of tasks, such as sentiment classification. This paper evaluates the performance of DistilBERT model and other pre-canned text classifiers on a… More >

  • Open Access

    ARTICLE

    A Top-down Method of Extraction Entity Relationship Triples and Obtaining Annotated Data

    Zhiqiang Hu1, Zheng Ma1, Jun Shi1, Zhipeng Li1, Xun Shao1,2, Yangzhao Yang1,*, Yong Liao1, Zhenyuan Gao1, Jie Zhang1
    Journal of Quantum Computing, Vol.4, No.1, pp. 13-22, 2022, DOI:10.32604/jqc.2022.026785
    Abstract The extraction of entity relationship triples is very important to build a knowledge graph (KG), meanwhile, various entity relationship extraction algorithms are mostly based on data-driven, especially for the current popular deep learning algorithms. Therefore, obtaining a large number of accurate triples is the key to build a good KG as well as train a good entity relationship extraction algorithm. Because of business requirements, this KG’s application field is determined and the experts’ opinions also must be satisfied. Considering these factors we adopt the top-down method which refers to determining the data schema firstly, then filling the specific data according… More >

  • Open Access

    ARTICLE

    Research on Rainfall Estimation Based on Improved Kalman Filter Algorithm

    Wen Zhang1,2, Wei Fang1,3,*, Xuelei Jia1,2, Victor S. Sheng4
    Journal of Quantum Computing, Vol.4, No.1, pp. 23-37, 2022, DOI:10.32604/jqc.2022.026975
    Abstract In order to solve the rainfall estimation error caused by various noise factors such as clutter, super refraction, and raindrops during the detection process of Doppler weather radar. This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter. After data preprocessing, the radar data should be classified according to the precipitation intensity. And then, they are respectively substituted into the improved filter for calibration. The state noise variance and the measurement noise variance can be adaptively calculated and updated according to the input observation data during this process. Then… More >

  • Open Access

    ARTICLE

    Research on Service Function Chain Orchestrating Algorithm Based on SDN and NFV

    Yuning Jia*, Yu Gong, Yifei Wei
    Journal of Quantum Computing, Vol.4, No.1, pp. 39-52, 2022, DOI:10.32604/jqc.2022.027560
    Abstract Software defined network (SDN) and network function virtualization (NFV) have become a new paradigm of a new generation of network architecture. SDN and NFV can effectively improve the flexibility of deploying and managing service function chains (SFCs). By combining SDN and NFV and applying them to the resource orchestration problem of SFC deployment, the three-tier architecture consisting of SDN controller, network function virtualization and physical underlying computing resource layer in the process of heterogeneous network resource mapping is considered. And an optimization algorithm for active control resources based on SDN and NFV is proposed. Firstly, the user’s utility is modeled… More >

  • Open Access

    ARTICLE

    Study on Quantum Finance Algorithm: Quantum Monte Carlo Algorithm based on European Option Pricing

    Jian-Guo Hu1,*, Shao-Yi Wu1,*, Yi Yang1, Qin-Sheng Zhu1, Xiao-Yu Li1, Shan Yang2
    Journal of Quantum Computing, Vol.4, No.1, pp. 53-61, 2022, DOI:10.32604/jqc.2022.027683
    Abstract As one of the major methods for the simulation of option pricing, Monte Carlo method assumes random fluctuations in the distribution of asset prices. Under certain uncertainties process, different evolution paths could be simulated so as to finally yield the expectation value of the asset price, which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations. In order to solve the above computational problem, quantum Monte Carlo (QMC) has been established and applied in the relevant systems such as European call options. In this work, both MC and QM methods are adopted to simulate… More >

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