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  • Open Access

    ARTICLE

    A Systematic Comparison of Discrete Cosine Transform-Based Approaches for Multi-Focus Image Fusion

    Muhammad Osama1, Sarwar Shah Khan2,*, Sajid Khan2, Muzammil Khan3, Mian Muhammad Danyal4, Reshma Khan1

    Digital Engineering and Digital Twin, Vol.3, pp. 17-34, 2025, DOI:10.32604/dedt.2025.066344 - 19 August 2025

    Abstract Image fusion is a technique used to combine essential information from two or more source images into a single, more informative output image. The resulting fused image contains more meaningful details than any individual source image. This study focuses on multi-focus image fusion, a crucial area in image processing. Due to the limited depth of field of optical lenses, it is often challenging to capture an image where all areas are in focus simultaneously. As a result, multi-focus image fusion plays a key role in integrating and extracting the necessary details from different focal regions.… More >

  • Open Access

    ARTICLE

    Impact of Dataset Size on Machine Learning Regression Accuracy in Solar Power Prediction

    S. M. Rezaul Karim1,2, Md. Shouquat Hossain1,3, Khadiza Akter1, Debasish Sarker4, Md. Moniul Kabir 2, Mamdouh Assad5,*

    Energy Engineering, Vol.122, No.8, pp. 3041-3054, 2025, DOI:10.32604/ee.2025.066867 - 24 July 2025

    Abstract Knowing the influence of the size of datasets for regression models can help in improving the accuracy of a solar power forecast and make the most out of renewable energy systems. This research explores the influence of dataset size on the accuracy and reliability of regression models for solar power prediction, contributing to better forecasting methods. The study analyzes data from two solar panels, aSiMicro03036 and aSiTandem72-46, over 7, 14, 17, 21, 28, and 38 days, with each dataset comprising five independent and one dependent parameter, and split 80–20 for training and testing. Results indicate… More > Graphic Abstract

    Impact of Dataset Size on Machine Learning Regression Accuracy in Solar Power Prediction

  • Open Access

    ARTICLE

    Arc Grounding Fault Identification Using Integrated Characteristics in the Power Grid

    Penghui Liu1,2,*, Yaning Zhang1, Yuxing Dai2, Yanzhou Sun1,3

    Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318 - 11 June 2024

    Abstract Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product,… More >

  • Open Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su1,*, Shuwen Shang1, Zhihui Xu2, Hong Qian1, Xiaolei Pan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957 - 17 November 2023

    Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs More > Graphic Abstract

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open Access

    ARTICLE

    An Efficient Cyber Security and Intrusion Detection System Using CRSR with PXORP-ECC and LTH-CNN

    Nouf Saeed Alotaibi*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2061-2078, 2023, DOI:10.32604/cmc.2023.039446 - 30 August 2023

    Abstract Intrusion Detection System (IDS) is a network security mechanism that analyses all users’ and applications’ traffic and detects malicious activities in real-time. The existing IDS methods suffer from lower accuracy and lack the required level of security to prevent sophisticated attacks. This problem can result in the system being vulnerable to attacks, which can lead to the loss of sensitive data and potential system failure. Therefore, this paper proposes an Intrusion Detection System using Logistic Tanh-based Convolutional Neural Network Classification (LTH-CNN). Here, the Correlation Coefficient based Mayfly Optimization (CC-MA) algorithm is used to extract the… More >

  • Open Access

    ARTICLE

    A Novel Compact Highly Isolated UWB MIMO Antenna with WLAN Notch

    Muhammad Awais1, Shahid Bashir1, Awais Khan1,2, Muhammad Asif2, Nasim Ullah3,*, Hend I. Alkhammash4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 669-681, 2023, DOI:10.32604/cmc.2022.033939 - 06 February 2023

    Abstract This paper presents a compact Multiple Input Multiple Output (MIMO) antenna with WLAN band notch for Ultra-Wideband (UWB) applications. The antenna is designed on 0.8 mm thick low-cost FR-4 substrate having a compact size of 22 mm × 30 mm. The proposed antenna comprises of two monopole patches on the top layer of substrate while having a shared ground on its bottom layer. The mutual coupling between adjacent patches has been reduced by using a novel stub with shared ground structure. The stub consists of complementary rectangular slots that disturb the surface current direction and… More >

  • Open Access

    ARTICLE

    Isolation Enhancement in a Compact Four-Element MIMO Antenna for Ultra-Wideband Applications

    Awais Khan1,2,*, Shahid Bashir1, Salman Ghafoor3, Hatem Rmili4,5, Jawad Mirza6, Ammar Ahmad1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 911-925, 2023, DOI:10.32604/cmc.2023.033866 - 06 February 2023

    Abstract Mutual coupling reduction or isolation enhancement in antenna arrays is an important area of research as it severely affects the performance of an antenna. In this paper, a new type of compact and highly isolated Multiple-Input-Multiple-Output (MIMO) antenna for ultra-wideband (UWB) applications is presented. The design consists of four radiators that are orthogonally positioned and confined to a compact 40 × 40 × 0.8 mm3 space. The final antenna design uses an inverted L shape partial ground to produce an acceptable reflection coefficient (S11 < −10 dB) in an entire UWB band (3.1–10.6) giga hertz (GHz).… More >

  • Open Access

    ARTICLE

    The Correlation Coefficient of Hesitancy Fuzzy Graphs in Decision Making

    N. Rajagopal Reddy, S. Sharief Basha*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 579-596, 2023, DOI:10.32604/csse.2023.034527 - 20 January 2023

    Abstract The hesitancy fuzzy graphs (HFGs), an extension of fuzzy graphs, are useful tools for dealing with ambiguity and uncertainty in issues involving decision-making (DM). This research implements a correlation coefficient measure (CCM) to assess the strength of the association between HFGs in this article since CCMs have a high capacity to process and interpret data. The CCM that is proposed between the HFGs has better qualities than the existing ones. It lowers restrictions on the hesitant fuzzy elements’ length and may be used to establish whether the HFGs are connected negatively or favorably. Additionally, a… More >

  • Open Access

    ARTICLE

    Rice (Oryza sativa L.) Breeding among Hassawi Landrace and Egyptian Genotypes for Stem Borer (Chilo agamemnon Bles.) Resistance and Related Quantitative Traits

    Mohammed I. Al-Daej1, Mohamed M. El-Malky2, Muhammad N. Sattar3, Adel A. Rezk1,4, Muhammad N. Naqqash5, Jameel M. Al-Khayri1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 1905-1922, 2022, DOI:10.32604/phyton.2022.020629 - 13 May 2022

    Abstract Rice stem borer (Chilo agamemnon Bles.) is a primary insect pest of rice and is a major limiting factor to rice production. Breeding for insect-resistant crop varieties has been an economic way of integrated pest management (IPM) as it offers a viable and ecologically acceptable approach. This study was aimed to evaluate rice genotypes for their resistance against rice stem borer. Seven parental genotypes with twenty one F1 crosses were evaluated for genotypic variation in field experiments. Analysis of variance revealed significant differences for the studied traits in almost all crosses and parents. In addition, the… More >

  • Open Access

    ARTICLE

    Improving Method of Anomaly Detection Performance for Industrial IoT Environment

    Junwon Kim1, Jiho Shin2, Ki-Woong Park3, Jung Taek Seo4,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5377-5394, 2022, DOI:10.32604/cmc.2022.026619 - 21 April 2022

    Abstract Industrial Control System (ICS), which is based on Industrial IoT (IIoT), has an intelligent mobile environment that supports various mobility, but there is a limit to relying only on the physical security of the ICS environment. Due to various threat factors that can disrupt the workflow of the IIoT, machine learning-based anomaly detection technologies are being presented; it is also essential to study for increasing detection performance to minimize model errors for promoting stable ICS operation. In this paper, we established the requirements for improving the anomaly detection performance in the IIoT-based ICS environment by… More >

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