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  • Open Access

    ARTICLE

    Fake News Detection Based on Text-Modal Dominance and Fusing Multiple Multi-Model Clues

    Lifang Fu1, Huanxin Peng2,*, Changjin Ma2, Yuhan Liu2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4399-4416, 2024, DOI:10.32604/cmc.2024.047053

    Abstract In recent years, how to efficiently and accurately identify multi-model fake news has become more challenging. First, multi-model data provides more evidence but not all are equally important. Secondly, social structure information has proven to be effective in fake news detection and how to combine it while reducing the noise information is critical. Unfortunately, existing approaches fail to handle these problems. This paper proposes a multi-model fake news detection framework based on Tex-modal Dominance and fusing Multiple Multi-model Cues (TD-MMC), which utilizes three valuable multi-model clues: text-model importance, text-image complementary, and text-image inconsistency. TD-MMC is dominated by textural content and… More >

  • Open Access

    ARTICLE

    A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

    Fauziyah1, Zhaoshun Wang1,*, Mujahid Tabassum2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4417-4452, 2024, DOI:10.32604/cmc.2024.046797

    Abstract In an era characterized by digital pervasiveness and rapidly expanding datasets, ensuring the integrity and reliability of information is paramount. As cyber threats evolve in complexity, traditional cryptographic methods face increasingly sophisticated challenges. This article initiates an exploration into these challenges, focusing on key exchanges (encompassing their variety and subtleties), scalability, and the time metrics associated with various cryptographic processes. We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering. Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity, foundational pillars of information security. Our method employs a phased strategy, beginning… More >

  • Open Access

    ARTICLE

    A Cover-Independent Deep Image Hiding Method Based on Domain Attention Mechanism

    Nannan Wu1, Xianyi Chen1,*, James Msughter Adeke2, Junjie Zhao2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3001-3019, 2024, DOI:10.32604/cmc.2023.045311

    Abstract Recently, deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding. However, these approaches have some limitations. For example, a cover image lacks self-adaptability, information leakage, or weak concealment. To address these issues, this study proposes a universal and adaptable image-hiding method. First, a domain attention mechanism is designed by combining the Atrous convolution, which makes better use of the relationship between the secret image domain and the cover image domain. Second, to improve perceived human similarity, perceptual loss is incorporated into the training process. The experimental results are promising, with the proposed method achieving an… More >

  • Open Access

    ARTICLE

    Intelligent Fault Diagnosis Method of Rolling Bearings Based on Transfer Residual Swin Transformer with Shifted Windows

    Haomiao Wang1, Jinxi Wang2, Qingmei Sui2,*, Faye Zhang2, Yibin Li1, Mingshun Jiang2, Phanasindh Paitekul3

    Structural Durability & Health Monitoring, Vol.18, No.2, pp. 91-110, 2024, DOI:10.32604/sdhm.2023.041522

    Abstract Due to their robust learning and expression ability for complex features, the deep learning (DL) model plays a vital role in bearing fault diagnosis. However, since there are fewer labeled samples in fault diagnosis, the depth of DL models in fault diagnosis is generally shallower than that of DL models in other fields, which limits the diagnostic performance. To solve this problem, a novel transfer residual Swin Transformer (RST) is proposed for rolling bearings in this paper. RST has 24 residual self-attention layers, which use the hierarchical design and the shifted window-based residual self-attention. Combined with transfer learning techniques, the… More >

  • Open Access

    ARTICLE

    MECHANISMS AND APPLICATIONS OF CATALYTIC COMBUSTION OF NATURAL GAS*

    Shihong Zhang#, Ning Li, Zhihua Wang

    Frontiers in Heat and Mass Transfer, Vol.2, No.3, pp. 1-5, 2011, DOI:10.5098/hmt.v2.3.3004

    Abstract This article discussed the thermal efficiency, stability and pollutant emissions characteristics of the combustion of lean natural gas-air mixtures in Pd metal based honeycomb monoliths by means of experiments on a practical burner V. The chemistry at work in the monoliths was then investigated by the stagnation point flow reactor( SPFR), a fundamental experimental reactor. It was found that catalytic combustion inhibited the extent of gas-phase oxidation and increased the surface temperature of homogeneous ignition. According to the applications of catalytic combustion in the condenser boiler, the data of catalytic combustion condenser boiler V were measured at atmospheric temperature and… More >

  • Open Access

    REVIEW

    Exploring the molecular mechanisms and potential therapeutic strategies of ferroptosis in ovarian cancer

    LISHA MA1,#, WANQI SHAO1,#, WEILI ZHU2,*

    BIOCELL, Vol.48, No.3, pp. 379-386, 2024, DOI:10.32604/biocell.2024.047812

    Abstract The morbidity rate of ovarian cancer, a malignant tumour in gynaecological tumours, is rising, and it is considered to be the most lethal cancer. The majority of patients are typically diagnosed during the advanced stages of the illness due to the elusive characteristics of ovarian cancer and an absence of highly sensitive and specific diagnostic indicators. Surgical excision of the lesions, along with chemotherapy, is the conventional treatment for ovarian cancer; however, resistance to platinum-based chemotherapeutic drugs and molecular targeted therapies frequently arises. Improving the survival rate and prognosis of patients with end-stage or recurring ovarian cancer requires the identification… More >

  • Open Access

    REVIEW

    MicroRNAs modulation in lung cancer: exploring dual mechanisms and clinical prospects

    SHAHID HUSSAIN1,*, HABIB BOKHARI1, XINGXING FAN2, SHAUKAT IQBAL MALIK3, SUNDAS IJAZ1, MUHAMMAD ADNAN SHEREEN4, AIMAN FATIMA3

    BIOCELL, Vol.48, No.3, pp. 403-413, 2024, DOI:10.32604/biocell.2024.044801

    Abstract The global incidence of lung cancer is marked by a considerably elevated mortality rate. MicroRNAs (miRNAs) exert pivotal influence in the intricate orchestration of gene regulation, and their dysregulation can precipitate dire consequences, notably cancer. Within this context, miRNAs encapsulated in exosomes manifest a diversified impact on the landscape of lung cancer, wherein their actions may either foster angiogenesis, cell proliferation, and metastasis, or counteract these processes. This comprehensive review article discerns potential targets for the prospective development of therapeutic agents tailored for lung cancer. Tumor-suppressive miRNAs, such as miR-204, miR-192, miR-30a, miR-34a, miR-34b, miR-203, and miR-212, exhibit heightened expression… More >

  • Open Access

    ARTICLE

    Research on the Generation Mechanism and Suppression Method of Aerodynamic Noise in Expansion Cavity Based on Hybrid Method

    Haitao Liu1,2,*, Jiaming Wang1, Xiuliang Zhang1, Yanji Jiang2, Qian Xiao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2747-2772, 2024, DOI:10.32604/cmes.2024.047129

    Abstract The expansion chamber serves as the primary silencing structure within the exhaust pipeline. However, it can also act as a sound-emitting structure when subjected to airflow. This article presents a hybrid method for numerically simulating and analyzing the unsteady flow and aerodynamic noise in an expansion chamber under the influence of airflow. A fluid simulation model is established, utilizing the Large Eddy Simulation (LES) method to calculate the unsteady flow within the expansion chamber. The simulation results effectively capture the development and changes of the unsteady flow and vorticity inside the cavity, exhibiting a high level of consistency with experimental… More > Graphic Abstract

    Research on the Generation Mechanism and Suppression Method of Aerodynamic Noise in Expansion Cavity Based on Hybrid Method

  • Open Access

    ARTICLE

    A Simplified Method for the Stress Analysis of Underground Transfer Structures Crossing Multiple Subway Tunnels

    Shen Yan1, Dajiang Geng2,*, Ning Dai3, Mingjian Long2, Zhicheng Bai2

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2893-2915, 2024, DOI:10.32604/cmes.2024.046931

    Abstract According to the design specifications, the construction of extended piles involves traversing the tunnel’s upper region and extending to the underlying rock layer. To address this challenge, a subterranean transfer structure spanning multiple subway tunnels was proposed. Deliberating on the function of piles in the transfer structure as springs with axial and bending stiffness, and taking into account the force balance and deformation coordination conditions of beams and plates within the transfer structure, we established a simplified mechanical model that incorporates soil stratification by combining it with the Winkler elastic foundation beam model. The resolved established simplified mechanical model employed… More >

  • Open Access

    ARTICLE

    CAW-YOLO: Cross-Layer Fusion and Weighted Receptive Field-Based YOLO for Small Object Detection in Remote Sensing

    Weiya Shi1,*, Shaowen Zhang2, Shiqiang Zhang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3209-3231, 2024, DOI:10.32604/cmes.2023.044863

    Abstract In recent years, there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural networks. Despite these efforts, the detection of small objects in remote sensing remains a formidable challenge. The deep network structure will bring about the loss of object features, resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep layers. Additionally, the features of small objects are susceptible to interference from background features contained within the image, leading to a decline in detection accuracy. Moreover, the sensitivity of small… More >

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