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  • Open Access

    ARTICLE

    Survey on the Application of Deep Reinforcement Learning in Image Processing

    Wei Fang1, 2, 3, ∗, Lin Pang1, Weinan Yi1

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 39-58, 2020, DOI:10.32604/jai.2020.09789 - 15 July 2020

    Abstract In recent years, with the rapid development of human society, more and more complex tasks have emerged that require deep learning to automatically extract abstract feature representations from a large amount of data, and use reinforcement learning to learn the best strategy to complete the task. Through the combination of deep learning and reinforcement learning, end-to-end input and output can be achieved, and substantial breakthroughs have been made in many planning and decision-making systems with infinite states, such as games, in particular, AlphaGo, robotics, natural language processing, dialogue systems, machine translation, and computer vision. In More >

  • Open Access

    ARTICLE

    A Method of Text Extremum Region Extraction Based on JointChannels

    Xueming Qiao1, Yingxue Xia1, Weiyi Zhu2, Dongjie Zhu3, *, Liang Kong1, Chunxu Lin3, Zhenhao Guo3, Yiheng Sun3

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 29-37, 2020, DOI:10.32604/jai.2020.09955 - 15 July 2020

    Abstract Natural scene recognition has important significance and value in the fields of image retrieval, autonomous navigation, human-computer interaction and industrial automation. Firstly, the natural scene image non-text content takes up relatively high proportion; secondly, the natural scene images have a cluttered background and complex lighting conditions, angle, font and color. Therefore, how to extract text extreme regions efficiently from complex and varied natural scene images plays an important role in natural scene image text recognition. In this paper, a Text extremum region Extraction algorithm based on Joint-Channels (TEJC) is proposed. On the one hand, it More >

  • Open Access

    ARTICLE

    Sentiment Analysis Using Deep Learning Approach

    Peng Cen1, Kexin Zhang1, Desheng Zheng1, *

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 17-27, 2020, DOI:10.32604/jai.2020.010132 - 15 July 2020

    Abstract Deep learning has made a great breakthrough in the field of speech and image recognition. Mature deep learning neural network has completely changed the field of nat ural language processing (NLP). Due to the enormous amount of data and opinions being produced, shared and transferred everyday across the Internet and other media, sentiment analysis has become one of the most active research fields in natural language processing. This paper introduces three deep learning networks applied in IMDB movie reviews sent iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews. Recurrent Neural More >

  • Open Access

    ARTICLE

    Classification Algorithm Optimization Based on Triple-GAN

    Kun Fang1, 2, Jianquan Ouyang1, *

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 1-15, 2020, DOI:10.32604/jai.2020.09738 - 15 July 2020

    Abstract Generating an Adversarial network (GAN) has shown great development prospects in image generation and semi-supervised learning and has evolved into TripleGAN. However, there are still two problems that need to be solved in Triple-GAN: based on the KL divergence distribution structure, gradients are easy to disappear and training instability occurs. Since Triple-GAN tags the samples manually, the manual marking workload is too large. Marked uneven and so on. This article builds on this improved Triple-GAN model (Improved Triple-GAN), which uses Random Forests to classify real samples, automate tagging of leaf nodes, and use Least Squares More >

  • Open Access

    ARTICLE

    A Food Traceability Framework Based on Permissioned Blockchain

    Jiuliang Liu1,*, Xingming Sun1, Ke Song2

    Journal of Cyber Security, Vol.2, No.2, pp. 107-113, 2020, DOI:10.32604/jcs.2020.011222 - 14 July 2020

    Abstract In recent years, food safety problems have become increasingly serious. The traditional supply chain traceability solution faces some serious problems, such as centralization, data tampering, and high communication costs. To solve these problems, this paper proposes a food traceability framework based on permissioned blockchain. The proposed framework is decentralized, and the supply chain data of the framework cannot be tampered with. The framework divides supply chain entities into five organizations, and each organization deploys its own chaincode onto the blockchain. The chaincode specifies the query permission of each organization, which can effectively protect the user’s More >

  • Open Access

    ARTICLE

    Data Security Defense and Algorithm for Edge Computing Based on Mean Field Game

    Chengshan Qian1,2, Xue Li1,*, Ning Sun2, Yuqing Tian1

    Journal of Cyber Security, Vol.2, No.2, pp. 97-106, 2020, DOI:10.32604/jcs.2020.010548 - 14 July 2020

    Abstract With the development of the Internet of Things, the edge devices are increasing. Cyber security issues in edge computing have also emerged and caused great concern. We propose a defense strategy based on Mean field game to solve the security issues of edge user data during edge computing. Firstly, an individual cost function is formulated to build an edge user data security defense model. Secondly, we research the More >

  • Open Access

    ARTICLE

    A Multi-Agent System for Environmental Monitoring Using Boolean Networks and Reinforcement Learning

    Hanzhong Zheng1, Dejie Shi2,*

    Journal of Cyber Security, Vol.2, No.2, pp. 85-96, 2020, DOI:10.32604/jcs.2020.010086 - 14 July 2020

    Abstract Distributed wireless sensor networks have been shown to be effective for environmental monitoring tasks, in which multiple sensors are deployed in a wide range of the environments to collect information or monitor a particular event, Wireless sensor networks, consisting of a large number of interacting sensors, have been successful in a variety of applications where they are able to share information using different transmission protocols through the communication network. However, the irregular and dynamic environment requires traditional wireless sensor networks to have frequent communications to exchange the most recent information, which can easily generate high… More >

  • Open Access

    REVIEW

    Review of PLC Security Issues in Industrial Control System

    Xiaojun Pan, Zhuoran Wang, Yanbin Sun*

    Journal of Cyber Security, Vol.2, No.2, pp. 69-83, 2020, DOI:10.32604/jcs.2020.010045 - 14 July 2020

    Abstract Programmable Logic Controllers (PLC), core of industrial control systems, is widely used in industrial control systems. The security of PLC is the key to the security of industrial control systems. Nowadays, a large number of industrial control systems are connected to the Internet which exposes the PLC equipment to the Internet, and thus raising security concerns. First of all, we introduce the basic principle of PLC in this paper. Then we analyze the PLC code security, firmware security, network security, virus vulnerability and Modbus communication protocol by reviewing the previous related work. Finally, we make More >

  • Open Access

    ARTICLE

    Preserving the Efficiency and Quality of Contributed Data in MCS via User and Task Profiling

    Dingwen Wang, Ming Zhao*

    Journal of Cyber Security, Vol.2, No.2, pp. 63-68, 2020, DOI:10.32604/jcs.2020.07229 - 14 July 2020

    Abstract Mobile crowdsensing is a new paradigm with powerful performance for data collection through a large number of smart devices. It is essential to obtain high quality data in crowdsensing campaign. Most of the existing specs ignore users’ diversity, focus on solving complicated optimization problem, and consider devices as instances of intelligent software agents which can make reasonable choices on behalf of users. Thus, the efficiency and quality of contributed data cannot be preserved simultaneously. In this paper, we propose a new scheme for improving the quality of contributed data, which recommends tasks to users based More >

  • Open Access

    ARTICLE

    An Energy Efficiency Improvement Method for Manufacturing Process Based on ECRSR

    Haiming Sun1,3, Quande Dong2,*, Cuixia Zhang2, Jianqing Chen3,4

    Energy Engineering, Vol.117, No.3, pp. 153-164, 2020, DOI:10.32604/EE.2020.010706 - 10 July 2020

    Abstract The improvement of energy efficiency is considered as one of the keys to the sustainable development of manufacturing enterprises. This paper proposes an energy efficiency improvement method for the manufacturing process. Based on the analysis of the characteristics of energy consumption in the manufacturing process, a necessary energy consumption model, an assistant energy consumption model and an ineffective energy consumption model are constructed for identifying the energy consumption attributes of the manufacturing process. Then, the relationship model of energy consumption is built, and the energy efficiency improvement method for the manufacturing process is proposed based More >

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