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  • Open Access

    ARTICLE

    Fire Detection Algorithm Based on an Improved Strategy of YOLOv5 and Flame Threshold Segmentation

    Yuchen Zhao, Shulei Wu*, Yaoru Wang, Huandong Chen*, Xianyao Zhang, Hongwei Zhao

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5639-5657, 2023, DOI:10.32604/cmc.2023.037829 - 29 April 2023

    Abstract Due to the rapid growth and spread of fire, it poses a major threat to human life and property. Timely use of fire detection technology can reduce disaster losses. The traditional threshold segmentation method is unstable, and the flame recognition methods of deep learning require a large amount of labeled data for training. In order to solve these problems, this paper proposes a new method combining You Only Look Once version 5 (YOLOv5) network model and improved flame segmentation algorithm. On the basis of the traditional color space threshold segmentation method, the original segmentation threshold… More >

  • Open Access

    ARTICLE

    Study of the Seepage Mechanism in Thick Heterogeneous Gas Reservoirs

    Xin Huang1,*, Yunpeng Jiang1, Daowu Huang1, Xianke He1, Xianguo Zhang2, Ping Guo3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1679-1691, 2023, DOI:10.32604/fdmp.2023.025312 - 30 January 2023

    Abstract

    The seepage mechanism plays a crucial role in low-permeability gas reservoirs. Compared with conventional gas reservoirs, low-permeability sandstone gas reservoirs are characterized by low porosity, low permeability, strong heterogeneity, and high water saturation. Moreover, their percolation mechanisms are more complex. The present work describes a series of experiments conducted considering low-permeability sandstone cores under pressure-depletion conditions (from the Xihu Depression in the East China Sea Basin). It is shown that the threshold pressure gradient of a low-permeability gas reservoir in thick layers is positively correlated with water saturation and negatively correlated with permeability and porosity. The

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  • Open Access

    ARTICLE

    Efficient Crack Severity Level Classification Using Bilayer Detection for Building Structures

    M. J. Anitha1,*, R. Hemalatha2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1183-1200, 2023, DOI:10.32604/csse.2023.031888 - 20 January 2023

    Abstract Detection of cracks at the early stage is considered as very constructive since precautionary steps need to be taken to avoid the damage to the civil structures. Moreover, identifying and classifying the severity level of cracks is inevitable in order to find the stability of buildings. Hence, this paper proposes an efficient strategy to classify the cracks into fine, medium, and thick using a novel bilayer crack detection algorithm. The bilayer crack detection algorithm helps in extracting the requisite features from the crack for efficient classification. The proposed algorithm works well in the dark background… More >

  • Open Access

    ARTICLE

    An Automatic Threshold Selection Using ALO for Healthcare Duplicate Record Detection with Reciprocal Neuro-Fuzzy Inference System

    Ala Saleh Alluhaidan1,*, Pushparaj2, Anitha Subbappa3, Ved Prakash Mishra4, P. V. Chandrika5, Anurika Vaish6, Sarthak Sengupta6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5821-5836, 2023, DOI:10.32604/cmc.2023.033995 - 28 December 2022

    Abstract ESystems based on EHRs (Electronic health records) have been in use for many years and their amplified realizations have been felt recently. They still have been pioneering collections of massive volumes of health data. Duplicate detections involve discovering records referring to the same practical components, indicating tasks, which are generally dependent on several input parameters that experts yield. Record linkage specifies the issue of finding identical records across various data sources. The similarity existing between two records is characterized based on domain-based similarity functions over different features. De-duplication of one dataset or the linkage of… More >

  • Open Access

    ARTICLE

    Salp Swarm Algorithm with Multilevel Thresholding Based Brain Tumor Segmentation Model

    Hanan T. Halawani*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6775-6788, 2023, DOI:10.32604/cmc.2023.030814 - 28 December 2022

    Abstract Biomedical image processing acts as an essential part of several medical applications in supporting computer aided disease diagnosis. Magnetic Resonance Image (MRI) is a commonly utilized imaging tool used to save glioma for clinical examination. Biomedical image segmentation plays a vital role in healthcare decision making process which also helps to identify the affected regions in the MRI. Though numerous segmentation models are available in the literature, it is still needed to develop effective segmentation models for BT. This study develops a salp swarm algorithm with multi-level thresholding based brain tumor segmentation (SSAMLT-BTS) model. The… More >

  • Open Access

    ARTICLE

    Developing a Secure Framework Using Feature Selection and Attack Detection Technique

    Mahima Dahiya*, Nitin Nitin

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4183-4201, 2023, DOI:10.32604/cmc.2023.032430 - 31 October 2022

    Abstract Intrusion detection is critical to guaranteeing the safety of the data in the network. Even though, since Internet commerce has grown at a breakneck pace, network traffic kinds are rising daily, and network behavior characteristics are becoming increasingly complicated, posing significant hurdles to intrusion detection. The challenges in terms of false positives, false negatives, low detection accuracy, high running time, adversarial attacks, uncertain attacks, etc. lead to insecure Intrusion Detection System (IDS). To offset the existing challenge, the work has developed a secure Data Mining Intrusion detection system (DataMIDS) framework using Functional Perturbation (FP) feature… More >

  • Open Access

    ARTICLE

    Transformer Internal and Inrush Current Fault Detection Using Machine Learning

    R. Vidhya1,*, P. Vanaja Ranjan2, N. R. Shanker3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 153-168, 2023, DOI:10.32604/iasc.2023.031942 - 29 September 2022

    Abstract Preventive maintenance in the transformer is performed through a differential relay protection system, and it protects the transformer from internal and external faults. However, the Current Transformer (CT) in the differential protection system mal-operates during inrush currents. CT saturates due to magnetizing inrush currents and causes false tripping of the differential relays. Moreover, identification of tripping in protection relay either due to inrush current or internal faults needs to be diagnosed. For the above problem, continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the tripping in relay due to inrush More >

  • Open Access

    ARTICLE

    Brain Tumor Classification Using Image Fusion and EFPA-SVM Classifier

    P. P. Fathimathul Rajeena1,*, R. Sivakumar2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2837-2855, 2023, DOI:10.32604/iasc.2023.030144 - 17 August 2022

    Abstract An accurate and early diagnosis of brain tumors based on medical imaging modalities is of great interest because brain tumors are a harmful threat to a person’s health worldwide. Several medical imaging techniques have been used to analyze brain tumors, including computed tomography (CT) and magnetic resonance imaging (MRI). CT provides information about dense tissues, whereas MRI gives information about soft tissues. However, the fusion of CT and MRI images has little effect on enhancing the accuracy of the diagnosis of brain tumors. Therefore, machine learning methods have been adopted to diagnose brain tumors in… More >

  • Open Access

    ARTICLE

    A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

    Nada M. Elfatih1, Elmustafa Sayed Ali1,5, Maha Abdelhaq2, Raed Alsaqour3,*, Rashid A. Saeed4

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 329-342, 2023, DOI:10.32604/csse.2023.028528 - 16 August 2022

    Abstract

    In cognitive radio networks (CoR), the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability. Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection. However, these methods do not take into account the effect of sample size and its effect on improving CoR performance. In general, a large sample size results in more reliable detection, but takes longer sensing time and increases complexity. Thus, the locally sensed sample size is an optimization problem. Therefore, optimizing the local

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  • Open Access

    ARTICLE

    A Novel Segment White Matter Hyperintensities Approach for Detecting Alzheimer

    Antonitta Eileen Pious1,*, U. K. Sridevi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2715-2726, 2023, DOI:10.32604/csse.2023.026582 - 01 August 2022

    Abstract Segmentation has been an effective step that needs to be done before the classification or detection of an anomaly like Alzheimer’s on a brain scan. Segmentation helps detect pixels of the same intensity or volume and group them together as one class or region, where in that particular region of interest (ROI) can be concentrated on, rather than focusing on the entire image. In this paper White Matter Hyperintensities (WMH) is taken as a strong biomarker that supports and determines the presence of Alzheimer’s. As the first step a proper segmentation of the lesions has… More >

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