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  • Open Access

    ARTICLE

    Design of Cybersecurity Threat Warning Model Based on Ant Colony Algorithm

    Weiwei Lin1,2,*, Reiko Haga3

    Journal on Big Data, Vol.3, No.4, pp. 147-153, 2021, DOI:10.32604/jbd.2021.017299

    Abstract In this paper, a cybersecurity threat warning model based on ant colony algorithm is designed to strengthen the accuracy of the cybersecurity threat warning model in the warning process and optimize its algorithm structure. Through the ant colony algorithm structure, the local global optimal solution is obtained; and the cybersecurity threat warning index system is established. Next, the above two steps are integrated to build the cybersecurity threat warning model based on ant colony algorithm, and comparative experiment is also designed. The experimental results show that, compared with the traditional qualitative differential game-based cybersecurity threat warning model, the cybersecurity threat… More >

  • Open Access

    ARTICLE

    Application of Quicksort Algorithm in Information Retrieval

    Jiajun Xie1, Zuyan Li1, Han Wu1, Linhan Li2, Bin Pan1, Peng Guo3,Guang Sun1,*

    Journal on Big Data, Vol.3, No.4, pp. 135-145, 2021, DOI:10.32604/jbd.2021.017017

    Abstract With the development and progress of today’s network information technology, a variety of large-scale network databases have emerged with the situation, such as Baidu Library and Weipu Database, the number of documents in the inventory has reached nearly one million. So how do you quickly and effectively retrieve the information you want in such a huge database? This requires finding efficient algorithms to reduce the computational complexity of the computer during Information Retrieval, improve retrieval efficiency, and adapt to the rapid expansion of document data. The Quicksort Algorithm gives different weights to each position of the document, and multiplies the… More >

  • Open Access

    ARTICLE

    A QR Data Hiding Method Based on Redundant Region and BCH

    Ying Zhou*, Weiwei Luo

    Journal on Big Data, Vol.3, No.3, pp. 127-133, 2021, DOI:10.32604/jbd.2021.019236

    Abstract In recent years, QR code has been widely used in the Internet and mobile devices. It is based on open standards and easy to generate a code, which lead to that anyone can generate their own QR code. Because the QR code does not have the ability of information hiding, any device can access the content in QR code. Thus, hiding the secret data in QR code becomes a hot topic. Previously, the information hiding methods based on QR code all use the way of information hiding based on image, mostly using digital watermarking technology, and not using the coding… More >

  • Open Access

    ARTICLE

    CTSF: An End-to-End Efficient Neural Network for Chinese Text with Skeleton Feature

    Hengyang Wang, Jin Liu*, Haoliang Ren

    Journal on Big Data, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jbd.2021.017184

    Abstract The past decade has seen the rapid development of text detection based on deep learning. However, current methods of Chinese character detection and recognition have proven to be poor. The accuracy of segmenting text boxes in natural scenes is not impressive. The reasons for this strait can be summarized into two points: the complexity of natural scenes and numerous types of Chinese characters. In response to these problems, we proposed a lightweight neural network architecture named CTSF. It consists of two modules, one is a text detection network that combines CTPN and the image feature extraction modules of PVANet, named… More >

  • Open Access

    ARTICLE

    WMA: A Multi-Scale Self-Attention Feature Extraction Network Based on Weight Sharing for VQA

    Yue Li, Jin Liu*, Shengjie Shang

    Journal on Big Data, Vol.3, No.3, pp. 111-118, 2021, DOI:10.32604/jbd.2021.017169

    Abstract Visual Question Answering (VQA) has attracted extensive research focus and has become a hot topic in deep learning recently. The development of computer vision and natural language processing technology has contributed to the advancement of this research area. Key solutions to improve the performance of VQA system exist in feature extraction, multimodal fusion, and answer prediction modules. There exists an unsolved issue in the popular VQA image feature extraction module that extracts the fine-grained features from objects of different scale difficultly. In this paper, a novel feature extraction network that combines multi-scale convolution and self-attention branches to solve the above… More >

  • Open Access

    ARTICLE

    Survey on Research of RNN-Based Spatio-Temporal Sequence Prediction Algorithms

    Wei Fang1,2,*, Yupeng Chen1, Qiongying Xue1

    Journal on Big Data, Vol.3, No.3, pp. 97-110, 2021, DOI:10.32604/jbd.2021.016993

    Abstract In the past few years, deep learning has developed rapidly, and many researchers try to combine their subjects with deep learning. The algorithm based on Recurrent Neural Network (RNN) has been successfully applied in the fields of weather forecasting, stock forecasting, action recognition, etc. because of its excellent performance in processing Spatio-temporal sequence data. Among them, algorithms based on LSTM and GRU have developed most rapidly because of their good design. This paper reviews the RNN-based Spatiotemporal sequence prediction algorithm, introduces the development history of RNN and the common application directions of the Spatio-temporal sequence prediction, and includes precipitation nowcasting… More >

  • Open Access

    RETRACTION

    Retraction Notice to: Recent Approaches for Text Summarization Using Machine Learning & LSTM0

    Neeraj Kumar Sirohi, Mamta Bansal, S. N. Rajan

    Journal on Big Data, Vol.3, No.2, pp. 97-97, 2021, DOI:10.32604/jbd.2021.041299

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    A Secure Visual Secret Sharing Scheme with Authentication Based on QR Code

    Xinwei Zhong*, Lizhi Xiong, Zhihua Xia

    Journal on Big Data, Vol.3, No.2, pp. 85-95, 2021, DOI:10.32604/jbd.2021.018618

    Abstract With the rise of the Internet of Things (IoT), various devices in life and industry are closely linked. Because of its high payload, stable error correction capability, and convenience in reading and writing, Quick Response (QR) code has been widely researched in IoT. However, the security of privacy data in IoT is also a very important issue. At the same time, because IoT is developing towards low-power devices in order to be applied to more fields, the technology protecting the security of private needs to have the characteristics of low computational complexity. Visual Secret Sharing (VSS), with its features of… More >

  • Open Access

    ARTICLE

    Encoder-Decoder Based Multi-Feature Fusion Model for Image Caption Generation

    Mingyang Duan, Jin Liu*, Shiqi Lv

    Journal on Big Data, Vol.3, No.2, pp. 77-83, 2021, DOI:10.32604/jbd.2021.016674

    Abstract Image caption generation is an essential task in computer vision and image understanding. Contemporary image caption generation models usually use the encoder-decoder model as the underlying network structure. However, in the traditional Encoder-Decoder architectures, only the global features of the images are extracted, while the local information of the images is not well utilized. This paper proposed an Encoder-Decoder model based on fused features and a novel mechanism for correcting the generated caption text. We use VGG16 and Faster R-CNN to extract global and local features in the encoder first. Then, we train the bidirectional LSTM network with the fused… More >

  • Open Access

    ARTICLE

    Grain Yield Predict Based on GRA-AdaBoost-SVR Model

    Diantao Hu, Cong Zhang*, Wenqi Cao, Xintao Lv, Songwu Xie

    Journal on Big Data, Vol.3, No.2, pp. 65-76, 2021, DOI:10.32604/jbd.2021.016317

    Abstract Grain yield security is a basic national policy of China, and changes in grain yield are influenced by a variety of factors, which often have a complex, non-linear relationship with each other. Therefore, this paper proposes a Grey Relational Analysis–Adaptive Boosting–Support Vector Regression (GRAAdaBoost-SVR) model, which can ensure the prediction accuracy of the model under small sample, improve the generalization ability, and enhance the prediction accuracy. SVR allows mapping to high-dimensional spaces using kernel functions, good for solving nonlinear problems. Grain yield datasets generally have small sample sizes and many features, making SVR a promising application for grain yield datasets.… More >

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