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  • Open Access

    ARTICLE

    Classification of Adversarial Attacks Using Ensemble Clustering Approach

    Pongsakorn Tatongjai1, Tossapon Boongoen2,*, Natthakan Iam-On2, Nitin Naik3, Longzhi Yang4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2479-2498, 2023, DOI:10.32604/cmc.2023.024858 - 31 October 2022

    Abstract As more business transactions and information services have been implemented via communication networks, both personal and organization assets encounter a higher risk of attacks. To safeguard these, a perimeter defence like NIDS (network-based intrusion detection system) can be effective for known intrusions. There has been a great deal of attention within the joint community of security and data science to improve machine-learning based NIDS such that it becomes more accurate for adversarial attacks, where obfuscation techniques are applied to disguise patterns of intrusive traffics. The current research focuses on non-payload connections at the TCP (transmission… More >

  • Open Access

    ARTICLE

    A Big Data Based Dynamic Weight Approach for RFM Segmentation

    Lin Lang1, Shuang Zhou1, Minjuan Zhong1,*, Guang Sun1, Bin Pan1, Peng Guo1,2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3503-3513, 2023, DOI:10.32604/cmc.2023.023596 - 31 October 2022

    Abstract Using the RFM (Recency, Frequency, Monetary value) model can provide valuable insights about customer clusters which is the core of customer relationship management. Due to accurate customer segment coming from dynamic weighted applications, in-depth targeted marketing may also use type of dynamic weight of R, F and M as factors. In this paper, we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights. Our dynamic weight approach is a kind of Custom method in essential which roots in… More >

  • Open Access

    ARTICLE

    Vehicle Detection in Challenging Scenes Using CenterNet Based Approach

    Ayesha1, Muhammad Javed Iqbal1, Iftikhar Ahmad2,*, Madini O. Alassafi2, Ahmed S. Alfakeeh2, Ahmed Alhomoud3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3647-3661, 2023, DOI:10.32604/cmc.2023.020916 - 31 October 2022

    Abstract Contemporarily numerous analysts labored in the field of Vehicle detection which improves Intelligent Transport System (ITS) and reduces road accidents. The major obstacles in automatic detection of tiny vehicles are due to occlusion, environmental conditions, illumination, view angles and variation in size of objects. This research centers on tiny and partially occluded vehicle detection and identification in challenging scene specifically in crowed area. In this paper we present comprehensive methodology of tiny vehicle detection using Deep Neural Networks (DNN) namely CenterNet. Substantially DNN disregards objects that are small in size 5 pixels and more false… More >

  • Open Access

    ARTICLE

    Existence of Approximate Solutions to Nonlinear Lorenz System under Caputo-Fabrizio Derivative

    Khursheed J. Ansari1, Mustafa Inc2,3,4,*, K. H. Mahmoud5,*, Eiman6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1669-1684, 2023, DOI:10.32604/cmes.2022.022971 - 27 October 2022

    Abstract In this article, we developed sufficient conditions for the existence and uniqueness of an approximate solution to a nonlinear system of Lorenz equations under Caputo-Fabrizio fractional order derivative (CFFD). The required results about the existence and uniqueness of a solution are derived via the fixed point approach due to Banach and Krassnoselskii. Also, we enriched our work by establishing a stable result based on the Ulam-Hyers (U-H) concept. Also, the approximate solution is computed by using a hybrid method due to the Laplace transform and the Adomian decomposition method. We computed a few terms of… More >

  • Open Access

    ARTICLE

    Explicit Isogeometric Topology Optimization Method with Suitably Graded Truncated Hierarchical B-Spline

    Haoran Zhu, Xinhao Gao, Aodi Yang, Shuting Wang, Xianda Xie, Tifan Xiong*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1435-1456, 2023, DOI:10.32604/cmes.2022.023454 - 27 October 2022

    Abstract This work puts forward an explicit isogeometric topology optimization (ITO) method using moving morphable components (MMC), which takes the suitably graded truncated hierarchical B-Spline based isogeometric analysis as the solver of physical unknown (SGTHB-ITO-MMC). By applying properly basis graded constraints to the hierarchical mesh of truncated hierarchical B-splines (THB), the convergence and robustness of the SGTHB-ITOMMC are simultaneously improved and the tiny holes occurred in optimized structure are eliminated, due to the improved accuracy around the explicit structural boundaries. Moreover, an efficient computational method is developed for the topological description functions (TDF) of MMC under More > Graphic Abstract

    Explicit Isogeometric Topology Optimization Method with Suitably Graded Truncated Hierarchical B-Spline

  • Open Access

    ARTICLE

    Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances

    Li Ding, Yong Yao*, Rui Ma

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1539-1558, 2023, DOI:10.32604/cmes.2022.023003 - 27 October 2022

    Abstract With the increasing demand for interactive aerial operations, the application of aerial manipulators is becoming more promising. However, there are a few critical problems on how to improve the energetic efficiency and pose control of the aerial manipulator for practical application. In this paper, a novel cable-driven aerial manipulator used for remote water sampling is proposed and then its rigid-flexible coupling dynamics model is constructed which takes joint flexibility into account. To achieve high precision joint position tracking under lumped disturbances, a newly controller, which consists of three parts: linear extended state observer, adaptive super-twisting More >

  • Open Access

    REVIEW

    Challenges and Limitations in Speech Recognition Technology: A Critical Review of Speech Signal Processing Algorithms, Tools and Systems

    Sneha Basak1, Himanshi Agrawal1, Shreya Jena1, Shilpa Gite2,*, Mrinal Bachute2, Biswajeet Pradhan3,4,5,*, Mazen Assiri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2022.021755 - 27 October 2022

    Abstract Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various More >

  • Open Access

    ARTICLE

    A Deep Learning Approach to Mesh Segmentation

    Abubakar Sulaiman Gezawa1, Qicong Wang1,2, Haruna Chiroma3, Yunqi Lei1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1745-1763, 2023, DOI:10.32604/cmes.2022.021351 - 27 October 2022

    Abstract In the shape analysis community, decomposing a 3D shape into meaningful parts has become a topic of interest. 3D model segmentation is largely used in tasks such as shape deformation, shape partial matching, skeleton extraction, shape correspondence, shape annotation and texture mapping. Numerous approaches have attempted to provide better segmentation solutions; however, the majority of the previous techniques used handcrafted features, which are usually focused on a particular attribute of 3D objects and so are difficult to generalize. In this paper, we propose a three-stage approach for using Multi-view recurrent neural network to automatically segment… More > Graphic Abstract

    A Deep Learning Approach to Mesh Segmentation

  • Open Access

    ARTICLE

    Computational Modeling of Reaction-Diffusion COVID-19 Model Having Isolated Compartment

    Muhammad Shoaib Arif1,2,*, Kamaleldin Abodayeh1, Asad Ejaz2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1719-1743, 2023, DOI:10.32604/cmes.2022.022235 - 27 October 2022

    Abstract Cases of COVID-19 and its variant omicron are raised all across the world. The most lethal form and effect of COVID-19 are the omicron version, which has been reported in tens of thousands of cases daily in numerous nations. Following WHO (World health organization) records on 30 December 2021, the cases of COVID-19 were found to be maximum for which boarding individuals were found 1,524,266, active, recovered, and discharge were found to be 82,402 and 34,258,778, respectively. While there were 160,989 active cases, 33,614,434 cured cases, 456,386 total deaths, and 605,885,769 total samples tested. So… More >

  • Open Access

    ARTICLE

    A Weighted Average Finite Difference Scheme for the Numerical Solution of Stochastic Parabolic Partial Differential Equations

    Dumitru Baleanu1,2,3, Mehran Namjoo4, Ali Mohebbian4, Amin Jajarmi5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1147-1163, 2023, DOI:10.32604/cmes.2022.022403 - 27 October 2022

    Abstract In the present paper, the numerical solution of Itô type stochastic parabolic equation with a time white noise process is imparted based on a stochastic finite difference scheme. At the beginning, an implicit stochastic finite difference scheme is presented for this equation. Some mathematical analyses of the scheme are then discussed. Lastly, to ascertain the efficacy and accuracy of the suggested technique, the numerical results are discussed and compared with the exact solution. More >

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