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  • Open Access

    ARTICLE

    A Hybrid Feature Selection Method for Advanced Persistent Threat Detection

    Adam Khalid1, Anazida Zainal1, Fuad A. Ghaleb2, Bander Ali Saleh Al-rimy3, Yussuf Ahmed2,*

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5665-5691, 2025, DOI:10.32604/cmc.2025.063451 - 30 July 2025

    Abstract Advanced Persistent Threats (APTs) represent one of the most complex and dangerous categories of cyber-attacks characterised by their stealthy behaviour, long-term persistence, and ability to bypass traditional detection systems. The complexity of real-world network data poses significant challenges in detection. Machine learning models have shown promise in detecting APTs; however, their performance often suffers when trained on large datasets with redundant or irrelevant features. This study presents a novel, hybrid feature selection method designed to improve APT detection by reducing dimensionality while preserving the informative characteristics of the data. It combines Mutual Information (MI), Symmetric… More >

  • Open Access

    ARTICLE

    FS-MSFormer: Image Dehazing Based on Frequency Selection and Multi-Branch Efficient Transformer

    Chunming Tang*, Yu Wang

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5115-5128, 2025, DOI:10.32604/cmc.2025.062328 - 19 May 2025

    Abstract Image dehazing aims to generate clear images critical for subsequent visual tasks. CNNs have made significant progress in the field of image dehazing. However, due to the inherent limitations of convolution operations, it is challenging to effectively model global context and long-range spatial dependencies effectively. Although the Transformer can address this issue, it faces the challenge of excessive computational requirements. Therefore, we propose the FS-MSFormer network, an asymmetric encoder-decoder architecture that combines the advantages of CNNs and Transformers to improve dehazing performance. Specifically, the encoding process employs two branches for multi-scale feature extraction. One branch… More >

  • Open Access

    ARTICLE

    Improved Resilience of Image Encryption Based on Hybrid TEA and RSA Techniques

    Muath AlShaikh1,*, Ahmed Manea Alkhalifah2, Sultan Alamri3

    Computer Systems Science and Engineering, Vol.49, pp. 353-376, 2025, DOI:10.32604/csse.2025.062433 - 21 March 2025

    Abstract Data security is crucial for improving the confidentiality, integrity, and authenticity of the image content. Maintaining these security factors poses significant challenges, particularly in healthcare, business, and social media sectors, where information security and personal privacy are paramount. The cryptography concept introduces a solution to these challenges. This paper proposes an innovative hybrid image encryption algorithm capable of encrypting several types of images. The technique merges the Tiny Encryption Algorithm (TEA) and Rivest-Shamir-Adleman (RSA) algorithms called (TEA-RSA). The performance of this algorithm is promising in terms of cost and complexity, an encryption time which is… More >

  • Open Access

    ARTICLE

    A Heavy Tailed Model Based on Power XLindley Distribution with Actuarial Data Applications

    Mohammed Elgarhy1, Amal S. Hassan2, Najwan Alsadat3, Oluwafemi Samson Balogun4, Ahmed W. Shawki5, Ibrahim E. Ragab6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2547-2583, 2025, DOI:10.32604/cmes.2025.058362 - 03 March 2025

    Abstract Accurately modeling heavy-tailed data is critical across applied sciences, particularly in finance, medicine, and actuarial analysis. This work presents the heavy-tailed power XLindley distribution (HTPXLD), a unique heavy-tailed distribution. Adding one more parameter to the power XLindley distribution improves this new distribution, especially when modeling leptokurtic lifetime data. The suggested density provides greater flexibility with asymmetric forms and different degrees of peakedness. Its statistical features, like the quantile function, moments, extropy measures, incomplete moments, stochastic ordering, and stress-strength parameters, are explored. We further investigate its use in actuarial science through the computation of pertinent metrics,… More >

  • Open Access

    ARTICLE

    Construction Monitoring and Analysis of Asymmetric Prestressed Concrete Bridge Crossing Multiple-Line Railways

    Yi Wang1, Bing Wang2, Changwen Li2, Feng Zheng1, Yong Liu2, Shaohua He3,*

    Structural Durability & Health Monitoring, Vol.19, No.2, pp. 385-398, 2025, DOI:10.32604/sdhm.2024.054761 - 15 January 2025

    Abstract Complex bridge structures designed and constructed by humans often necessitate extensive on-site execution, which carries inherent risks. Consequently, a variety of engineering practices are employed to monitor bridge construction. This paper presents a case study of a large-span prestressed concrete (PC) variable-section continuous girder bridge in China, proposing a feedback system for construction monitoring and establishing a finite element (FE) analysis model for the entire bridge. The alignment of the completed bridge adheres to the initial design expectations, with maximum displacement and pre-arch differences from the ideal state measuring 6.39 and 17.7 mm, respectively, which More >

  • Open Access

    PROCEEDINGS

    Analytical Modeling for Asymmetric Four-Point Bend End-Notched Flexure Delamination Testing of Composite Laminates Considering Friction

    Kaixin Xia1, Yu Gong2,*, Xinxin Qi3,4, Libin Zhao3,4,*, Linjuan Wang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011650

    Abstract The crack tip of the asymmetric four-point bend end-notched flexure (4AENF) delamination testing under shear loading often exhibits a proportion of mode I component, making it a typical mixed-mode I/II problem. Characterizing the total fracture toughness in 4AENF laminates is crucial for understanding the delamination phenomenon in composites. In this study, 4AENF tests were conducted on carbon fiber-reinforced epoxy asymmetric laminates to evaluate the total interlaminar fracture toughness under shear loading conditions. Additionally, the variation of interlaminar fracture toughness in asymmetric laminates with different fiber orientation angles was considered. Theoretical modelling was performed using an More >

  • Open Access

    ARTICLE

    Study of a Hydraulic Jump in an Asymmetric Trapezoidal Channel with Different Sluice Gates

    Bouthaina Debabeche1,2,*, Sonia Cherhabil3

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1499-1516, 2024, DOI:10.32604/fdmp.2024.047403 - 23 July 2024

    Abstract In this study, the main properties of the hydraulic jump in an asymmetric trapezoidal flume are analyzed experimentally, including the so-called sequent depths, characteristic lengths, and efficiency. In particular, an asymmetric trapezoidal flume with a length of 7 m and a width of 0.304 m is considered, with the bottom of the flume transversely inclined at an angle of m = 0.296 and vertical lateral sides. The corresponding inflow Froude number is allowed to range in the interval (1.40 < F1 < 6.11). The properties of this jump are compared to those of hydraulic jumps More >

  • Open Access

    ARTICLE

    Oscillatory Dynamics of a Spherical Solid in a Liquid in an Axisymmetric Variable Cross Section Channel

    Ivan Karpunin*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1219-1232, 2024, DOI:10.32604/fdmp.2024.051062 - 27 June 2024

    Abstract The dynamics of a solid spherical body in an oscillating liquid flow in a vertical axisymmetric channel of variable cross section is experimentally studied. It is shown that the oscillating liquid leads to the generation of intense averaged flows in each of the channel segments. The intensity and direction of these flows depend on the dimensionless oscillating frequency. In the region of studied frequencies, the dynamics of the considered body is examined when the primary vortices emerging in the flow occupy the whole region in each segment. For a fixed frequency, an increase in the… More >

  • Open Access

    ARTICLE

    Numerical Exploration of Asymmetrical Impact Dynamics: Unveiling Nonlinearities in Collision Problems and Resilience of Reinforced Concrete Structures

    AL-Bukhaiti Khalil1, Yanhui Liu1,*, Shichun Zhao1, Daguang Han2

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 223-254, 2024, DOI:10.32604/sdhm.2024.044751 - 15 May 2024

    Abstract This study provides a comprehensive analysis of collision and impact problems’ numerical solutions, focusing on geometric, contact, and material nonlinearities, all essential in solving large deformation problems during a collision. The initial discussion revolves around the stress and strain of large deformation during a collision, followed by explanations of the fundamental finite element solution method for addressing such issues. The hourglass mode’s control methods, such as single-point reduced integration and contact-collision algorithms are detailed and implemented within the finite element framework. The paper further investigates the dynamic response and failure modes of Reinforced Concrete (RC)… More >

  • Open Access

    ARTICLE

    Causality-Driven Common and Label-Specific Features Learning

    Yuting Xu1,*, Deqing Zhang1, Huaibei Guo2, Mengyue Wang1

    Journal on Artificial Intelligence, Vol.6, pp. 53-69, 2024, DOI:10.32604/jai.2024.049083 - 05 April 2024

    Abstract In multi-label learning, the label-specific features learning framework can effectively solve the dimensional catastrophe problem brought by high-dimensional data. The classification performance and robustness of the model are effectively improved. Most existing label-specific features learning utilizes the cosine similarity method to measure label correlation. It is well known that the correlation between labels is asymmetric. However, existing label-specific features learning only considers the private features of labels in classification and does not take into account the common features of labels. Based on this, this paper proposes a Causality-driven Common and Label-specific Features Learning, named CCSF More >

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