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  • 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

    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 communication cost through the collaborative… More >

  • Open Access

    ARTICLE

    Study of the Superficial Modification of Sisal Fibres with Lignin, and Its Use As a Reinforcement Agent in Cementitious Composites

    Plínio B. Mundim1, Rondinele A. R. Ferreira1, Leila A. C. Motta1, Mariana A. Henrique2, Daniel Pasquini2,*

    Journal of Renewable Materials, Vol.8, No.8, pp. 891-903, 2020, DOI:10.32604/jrm.2020.010655

    Abstract The objective of this work was to evaluate different superficial treatments of sisal fibres employing lignin, and their use as a reinforcement agent in cementitious composites. The treatments consisted of superficially impregnating sisal fibres (S) with organosolv lignin (LO), organosolv lignin and glutaraldehyde (LOG), Kraft lignin (LK) and Kraft lignin and glutaraldehyde (LKG). The fibre modifications were verified by FTIR-ATR and SEM analyzes, and the presence of lignin on the surface of the fibres was evidenced, confirming the effectiveness of the treatments. The mechanical, thermal (by TGA) and water absorption properties of the fibres before and after the modifications were… More >

  • Open Access

    ARTICLE

    A DRL-Based Container Placement Scheme with Auxiliary Tasks

    Ningcheng Yuan1, Chao Jia2, *, Jizhao Lu3, Shaoyong Guo1, Wencui Li3, Xuesong Qiu1, Lei Shi4

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1657-1671, 2020, DOI:10.32604/cmc.2020.09840

    Abstract Container is an emerging virtualization technology and widely adopted in the cloud to provide services because of its lightweight, flexible, isolated and highly portable properties. Cloud services are often instantiated as clusters of interconnected containers. Due to the stochastic service arrival and complicated cloud environment, it is challenging to achieve an optimal container placement (CP) scheme. We propose to leverage Deep Reinforcement Learning (DRL) for solving CP problem, which is able to learn from experience interacting with the environment and does not rely on mathematical model or prior knowledge. However, applying DRL method directly dose not lead to a satisfying… More >

  • Open Access

    ARTICLE

    Resource Allocation and Power Control Policy for Device-toDevice Communication Using Multi-Agent Reinforcement Learning

    Yifei Wei1, *, Yinxiang Qu1, Min Zhao1, Lianping Zhang2, F. Richard Yu3

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1515-1532, 2020, DOI:10.32604/cmc.2020.09130

    Abstract Device-to-Device (D2D) communication is a promising technology that can reduce the burden on cellular networks while increasing network capacity. In this paper, we focus on the channel resource allocation and power control to improve the system resource utilization and network throughput. Firstly, we treat each D2D pair as an independent agent. Each agent makes decisions based on the local channel states information observed by itself. The multi-agent Reinforcement Learning (RL) algorithm is proposed for our multi-user system. We assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected,… More >

  • Open Access

    ARTICLE

    Corrosion Performance of Stainless Steel Reinforcement in the Concrete Prepared with Seawater and Coral Waste and Its Ecological Effects

    Xingguo Feng1,2,3, Yiji Zhang1, Xiangyu Lu1,*, Yiwen Xu1, Leyuan Zhang1, Chao Zhu1, Tong Wu1, Yashi Yang4, Xuhui Zhao5

    Journal of Renewable Materials, Vol.8, No.5, pp. 513-534, 2020, DOI:10.32604/jrm.2020.09549

    Abstract Durability and ecological effects of the stainless steel reinforced coral waste concrete were compared with those of the carbon steel reinforced ordinary concrete. The results showed that the corrosion current densities of the stainless steel in the coral waste concrete were less than one-tenth of those of the carbon steel in the same grade ordinary concrete. The stainless steel in the seawater coral waste concrete maintained passivation even after more than two years of immersion in 3.5% NaCl solution, while the carbon steel counterparts in the ordinary concrete were seriously corroded under the same condition. Simultaneously, the corrosion current density… More >

  • Open Access

    ARTICLE

    Experimental Study on the Influence Mechanism of Carbon Fiber/Epoxy Composite Reinforcement and Matrix on Its Fire Performance

    Lei Zhang1, Haiyan Wang1,*, Junpeng Zhang1, Zhi Wang2, Zuohui Xu1, Xinyu Gao1

    Journal of Renewable Materials, Vol.8, No.3, pp. 219-237, 2020, DOI:10.32604/jrm.2020.09096

    Abstract The effects of the number of layers, the arrangement of carbon fiber (CF) tow and the epoxy resin (ER) matrix on the fire performance of carbon fiber/epoxy composites (CFEC) were studied by a variety of experimental methods. The results show that the number of layers of CF tow has influence on the combustion characteristics and fire propagation of the composites. The arrangement of CF tow has influence on flame propagation rate and high temperature mechanicalproperties. The mechanism of the influence of the number of layers of CF tow on the composite is mainly due to the different thermal capacity of… More >

  • Open Access

    REVIEW

    Wind Power Forecasting Methods Based on Deep Learning: A Survey

    Xing Deng1, 2, Haijian Shao1, *, Chunlong Hu1, Dengbiao Jiang1, Yingtao Jiang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 273-301, 2020, DOI:10.32604/cmes.2020.08768

    Abstract Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power grid. Aiming to provide reference strategies for relevant researchers as well as practical applications, this paper attempts to provide the literature investigation and methods analysis of deep learning, enforcement learning and transfer learning in wind speed and wind power forecasting modeling. Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of… More >

  • Open Access

    Pretreatment of Wheat Bran for Suitable Reinforcement in Biocomposites

    Atikur Rahman1,3, Chad A. Ulven2, Maren A. Johnson1, Cheyenne Durant1, Khwaja G. Hossain*,1

    Journal of Renewable Materials, Vol.5, Suppl.1, pp. 62-73, 2017, DOI:10.7569/JRM.2017.634133

    Abstract Wheat bran, abundant but underutilized, was investigated for its potential as a reinforcement in biocomposites through different pretreatment methods. Pretreatment methods included were dilute sodium hydroxide (NaOH), dilute sulfuric acid (H2SO4), liquid hot water (LHW), calcium hydroxide (CaOH), organosolv such as aqueous ethanol (EtOH), and methyl isobutyl ketone (MIBK). Changes in chemical composition and fiber characteristics of the treated bran were studied using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Cellulose content increased to 35.1% and 29.6% in brans treated with H2SO4 and NaOH, respectively. The SEM micrographs showed surface cleaning of treated bran while maintaining sufficient… More >

  • Open Access

    ARTICLE

    Experimental Investigations on the Glass Fabrics for Confinement of Concrete Specimens

    Smitha Gopinath1,2, A. Ramachandra Murthy1, Nagesh R. Iyer1

    Structural Durability & Health Monitoring, Vol.9, No.1, pp. 1-20, 2013, DOI:10.32604/sdhm.2013.009.001

    Abstract This paper deals with the performance of concrete specimens confined with different glass fabric reinforcement in organic binder consisting of resins. Three varieties of glass fabrics such as woven roving (WR), chopped strand mat (CSM), and textile reinforcement have been studied in the investigation. Experiments have been conducted on unconfined and confined concrete cylindrical specimens under compression. The effect of number of layers on confinement has been studied for specific cases. Specimens have been tested under displacement control. It is observed from the experiments that there is an increase in load carrying capacity as well as energy absorption capacity for… More >

  • Open Access

    ARTICLE

    Studies on Chloride Induced Corrosion of Reinforcement Steel in Cracked Concrete

    Sangoju Bhaskar1, Ravindra Gettu2, B.H. Bharatkumar1, M. Neelamegam1

    Structural Durability & Health Monitoring, Vol.7, No.4, pp. 231-252, 2011, DOI:10.3970/sdhm.2011.007.231

    Abstract The durability of reinforced concrete (RC) exposed to severe environments depends largely on its ability to resist the penetration of aggressive compounds. This paper deals with the corrosion of reinforcement bars (rebars) in cracked concrete exposed to chlorides. A simple U-shaped specimen was used in the study, with a high yield strength deformed bar of 12 mm diameter placed at with 20 mm clear cover. Concrete specimens with three water to cement ratios (w/c) and pre-cracks exposed to chlorides were studied for quality assessment and quantifying the corrosion damage in terms of gravimetric weight loss. Water absorption and rapid chloride… More >

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