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  • Open Access

    ARTICLE

    Intelligent Deep Learning Enabled Wild Forest Fire Detection System

    Ahmed S. Almasoud*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1485-1498, 2023, DOI:10.32604/csse.2023.025190

    Abstract The latest advancements in computer vision and deep learning (DL) techniques pave the way to design novel tools for the detection and monitoring of forest fires. In this view, this paper presents an intelligent wild forest fire detection and alarming system using deep learning (IWFFDA-DL) model. The proposed IWFFDA-DL technique aims to identify forest fires at earlier stages through integrated sensors. The proposed IWFFDA-DL system includes an Integrated sensor system (ISS) combining an array of sensors that acts as the major input source that helps to forecast the fire. Then, the attention based convolution neural network with bidirectional long short… More >

  • Open Access

    ARTICLE

    Facile Synthesis of a Novel Bio-Based P-N Containing Flame Retardant for Effectively Reducing the Fire Hazards of Epoxy Resin

    Meixian Li1, Xin Hu1, Jie Yang1, Hongyu Yang1,3,*, Yao Yuan2,*

    Journal of Renewable Materials, Vol.10, No.10, pp. 2639-2654, 2022, DOI:10.32604/jrm.2022.019491

    Abstract In this work, a bio-based flame retardant (Cy-HEDP) was synthesized from cytosine and HEDP through a facile salt-forming reaction and embedded into epoxy matrix to improve the flame retardancy and smoke suppression performance. The product Cy-HEDP was well characterized by FTIR, 1 H and 31P NMR and SEM tests. On the basis of the results, by adding 15 wt% Cy-HEDP, the EP15 can pass UL-94 V-0 rating, and the total smoke production (TSP) as well as total heat release (THR) can be decreased by 61.05% (from 22.61 to 8.7 m2 /m2 ) and 39.44% (from 103.19 to 62.50 MJ/m2 )… More > Graphic Abstract

    Facile Synthesis of a Novel Bio-Based P-N Containing Flame Retardant for Effectively Reducing the Fire Hazards of Epoxy Resin

  • Open Access

    ARTICLE

    Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

    M. Rajakani1,*, R. J. Kavitha2, A. Ramachandran3

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 265-280, 2023, DOI:10.32604/csse.2023.024994

    Abstract Feature extraction is the most critical step in classification of multispectral image. The classification accuracy is mainly influenced by the feature sets that are selected to classify the image. In the past, handcrafted feature sets are used which are not adaptive for different image domains. To overcome this, an evolutionary learning method is developed to automatically learn the spatial-spectral features for classification. A modified Firefly Algorithm (FA) which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose. For extracting the most efficient features from the data set,… More >

  • Open Access

    ARTICLE

    Bio-inspired Hybrid Feature Selection Model for Intrusion Detection

    Adel Hamdan Mohammad1,*, Tariq Alwada’n2, Omar Almomani3, Sami Smadi3, Nidhal ElOmari4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 133-150, 2022, DOI:10.32604/cmc.2022.027475

    Abstract Intrusion detection is a serious and complex problem. Undoubtedly due to a large number of attacks around the world, the concept of intrusion detection has become very important. This research proposes a multilayer bio-inspired feature selection model for intrusion detection using an optimized genetic algorithm. Furthermore, the proposed multilayer model consists of two layers (layers 1 and 2). At layer 1, three algorithms are used for the feature selection. The algorithms used are Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Firefly Optimization Algorithm (FFA). At the end of layer 1, a priority value will be assigned for each… More >

  • Open Access

    ARTICLE

    Hybrid Renewable Energy System Using Cuckoo Firefly Optimization

    M. E. Shajini Sheeba1,*, P. Jagatheeswari2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1141-1156, 2022, DOI:10.32604/iasc.2022.024549

    Abstract With abundant and non-polluting benefits in nature, sources of renewable energy have reached vast concentrations. This paper first discusses the number of MPPT (Maximum Power Point Tracking) techniques utilized by wind and photovoltaic (PV) to create hybrid systems for generating wind-PV energy. This hybrid system complements each other day and night to enable continuous power output. Then, a new MPPT technique was proposed to extract maximum power using a newly developed hybrid optimization algorithm, namely the Cukoo Fire Fly method (CFF). The CFF algorithm is derived from the integration of the cuckoo search (CS) algorithm and the Firefly (FF) optimization… More >

  • Open Access

    ARTICLE

    Preparation and Characterization of Sandwich Structured Materials with Interesting Insulation and Fire Resistance

    Haizhu Wu1,#, Jinxing Li1,#, Shouhu Bao1, Fuxian Yang1, Jun Zhang1, Hisham Essawy2,*, Guanben Du1, Xiaojian Zhou1,*

    Journal of Renewable Materials, Vol.10, No.8, pp. 2029-2039, 2022, DOI:10.32604/jrm.2022.019834

    Abstract A cellular material in the form of 3-layered sandwich structure material was prepared via sole use of mechanical stirring without any use of a foaming agent, while Tween-80 was employed as a foam stabilizer via a developed in-situ mold casting. The resulting structure displayed a good appearance with no visual defects. The 3-layered composition of the sandwish structure, “nonporous resin layer-porous foam layer-nonporous resin layer”, was examined in terms of the microstructure, density & density distribution, pulverization ratio, mechanical strength, insulation and flame retardant performance. It was indicated from the results that the bonding between the resin layer and foam… More > Graphic Abstract

    Preparation and Characterization of Sandwich Structured Materials with Interesting Insulation and Fire Resistance

  • Open Access

    ARTICLE

    Optimized Deep Learning Model for Fire Semantic Segmentation

    Songbin Li1,*, Peng Liu1, Qiandong Yan1, Ruiling Qian2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4999-5013, 2022, DOI:10.32604/cmc.2022.026498

    Abstract Recent convolutional neural networks (CNNs) based deep learning has significantly promoted fire detection. Existing fire detection methods can efficiently recognize and locate the fire. However, the accurate flame boundary and shape information is hard to obtain by them, which makes it difficult to conduct automated fire region analysis, prediction, and early warning. To this end, we propose a fire semantic segmentation method based on Global Position Guidance (GPG) and Multi-path explicit Edge information Interaction (MEI). Specifically, to solve the problem of local segmentation errors in low-level feature space, a top-down global position guidance module is used to restrain the offset… More >

  • Open Access

    ARTICLE

    Discrete Firefly Algorithm for Optimizing Topology Generation and Core Mapping of Network-on-Chip

    S. Parvathi*, S. Umamaheswari

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 15-32, 2022, DOI:10.32604/iasc.2022.025290

    Abstract Network-on-chip (NoC) proves to be the best alternative to replace the traditional bus-based interconnection in Multi-Processor System on a Chip (MPSoCs). Irregular NoC topologies are highly recommended and utilised in various applications as they are application specific. Optimized mapping of the cores in a NoC plays a major role in its performance. Firefly algorithm is a bio-inspired meta-heuristic approach. Discretized firefly algorithm is used in our proposed work. In this work, two optimization algorithms are proposed: Topology Generation using Discrete Firefly Algorithm (TGDFA) and Core Mapping using Discrete Firefly Algorithm (CMDFA) for multimedia benchmark applications, Video Object Plane Decoder (VOPD),… More >

  • Open Access

    ARTICLE

    Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

    Harsh Goud1, Prakash Chandra Sharma2, Kashif Nisar3,7,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Narendra Singh Yadav2, Pankaj Swarnkar5, Manoj Gupta6, Laxmi Chand6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3481-3492, 2022, DOI:10.32604/cmc.2022.019764

    Abstract Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set… More >

  • Open Access

    ARTICLE

    A New Color Model for Fire Pixels Detection in PJF Color Space

    Amal Ben Hamida1,*, Chokri Ben Amar2, Yasser Albagory2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1607-1621, 2022, DOI:10.32604/iasc.2022.024939

    Abstract Since the number of fires in the world is rising rapidly, automatic fire detection is getting more and more interest in computer vision community. Instead of the usual inefficient sensors, captured videos by video surveillance cameras can be analyzed to quickly detect fires and prevent damages. This paper presents an early fire-alarm raising method based on image processing. The developed work is able to discriminate fire and non-fire pixels. Fire pixels are identified thanks to a rule-based color model built in the PJF color space. PJF is a newly designed color space that enables to better reflect the structure of… More >

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