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  • Open Access


    Overall Assessment of Heat Transfer for a Rarefied Flow in a Microchannel with Obstacles Using Lattice Boltzmann Method

    Siham Hammid1, Khatir Naima2, Omolayo M. Ikumapayi3, Cheikh Kezrane1, Abdelkrim Liazid4, Jihad Asad5, Mokdad Hayawi Rahman6, Farhan Lafta Rashid7, Naseer Ali Hussien8, Younes Menni2,9,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 273-299, 2024, DOI:10.32604/cmes.2023.028951

    Abstract The objective of this investigation is to assess the effect of obstacles on numerical heat transfer and fluid flow momentum in a rectangular microchannel (MC). Two distinct configurations were studied: one without obstacles and the other with alternating obstacles placed on the upper and lower walls. The research utilized the thermal lattice Boltzmann method (LBM), which solves the energy and momentum equations of fluids with the BGK approximation, implemented in a Python coding environment. Temperature jump and slip velocity conditions were utilized in the simulation for the MC and extended to all obstacle boundaries. The study aims to analyze the… More >

  • Open Access


    LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

    Xiaoli Li, Tongtong Jiao#, Jinfeng Ma, Dongxing Duan, Shengbin Liang#,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 595-617, 2024, DOI:10.32604/cmes.2023.029367

    Abstract In view of the complex marine environment of navigation, especially in the case of multiple static and dynamic obstacles, the traditional obstacle avoidance algorithms applied to unmanned surface vehicles (USV) are prone to fall into the trap of local optimization. Therefore, this paper proposes an improved artificial potential field (APF) algorithm, which uses 5G communication technology to communicate between the USV and the control center. The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios. Considering the various scenarios between the USV and other dynamic obstacles… More > Graphic Abstract

    LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

  • Open Access


    IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

    Ying Zhang1,*, Weiming Niu2, Leibing Yan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 885-902, 2024, DOI:10.32604/cmes.2023.029234

    Abstract In this paper, we consider mobile edge computing (MEC) networks against proactive eavesdropping. To maximize the transmission rate, IRS assisted UAV communications are applied. We take the joint design of the trajectory of UAV, the transmitting beamforming of users, and the phase shift matrix of IRS. The original problem is strong non-convex and difficult to solve. We first propose two basic modes of the proactive eavesdropper, and obtain the closed-form solution for the boundary conditions of the two modes. Then we transform the original problem into an equivalent one and propose an alternating optimization (AO) based method to obtain a… More >

  • Open Access


    Prediction of Cuttings-Induced Annular-Pressure Loss in Extended-Reach Wells

    Long Wang1, Qingyun Shen1, Gui Wang2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2877-2890, 2023, DOI:10.32604/fdmp.2023.029206

    Abstract Drill cuttings are broken bits of solid material removed from a borehole drilled by rotary, percussion, or auger methods and brought to the surface in the drilling mud. When these cuttings enter the annulus, they have an effect on the drilling fluid rheology and density, which is, in general, quite difficult to evaluate. By introducing an empirical correlation for the rheological properties of cuttings-laden drilling fluids, this study proposes a pressure-loss prediction method for an extended-reach well (ERW). After verifying the accuracy of this method, a case study is considered and a sensitivity analysis is conducted assuming a yield-power law… More >

  • Open Access


    Ion dynamics and Manipulation Under Extreme Confinement

    Yahui Xue1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09724

    Abstract Ion dynamics and precise control in nanochannels play key roles in biological systems, energy conversation, and environmental engineering. However, the mechanics behaviors of ions and their manipulation mechanism under extreme confinement remain largely unexplored. Biological ion channels acting as life’s transistors can gate simultaneously fast and selective ion transport through atomic-scale filters to maintain vital life functions. This biological inspiration motivates the quest for artificial structures with simultaneous functions of ion selectivity, fast transport and electrical gating at the atomic scale. Here, we experimentally investigate the ion dynamics and electrical manipulation in graphene channels of 3 angstrom size and report… More >

  • Open Access


    A Sensor Network Coverage Planning Based on Adjusted Single Candidate Optimizer

    Trong-The Nguyen1,2,3, Thi-Kien Dao1,2,3,*, Trinh-Dong Nguyen2,3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3213-3234, 2023, DOI:10.32604/iasc.2023.041356

    Abstract Wireless sensor networks (WSNs) are widely used for various practical applications due to their simplicity and versatility. The quality of service in WSNs is greatly influenced by the coverage, which directly affects the monitoring capacity of the target region. However, low WSN coverage and uneven distribution of nodes in random deployments pose significant challenges. This study proposes an optimal node planning strategy for network coverage based on an adjusted single candidate optimizer (ASCO) to address these issues. The single candidate optimizer (SCO) is a metaheuristic algorithm with stable implementation procedures. However, it has limitations in avoiding local optimum traps in… More >

  • Open Access


    Optimizing Power Allocation for D2D Communication with URLLC under Rician Fading Channel: A Learning-to-Optimize Approach

    Owais Muhammad1, Hong Jiang1,*, Mushtaq Muhammad Umer1, Bilal Muhammad2, Naeem Muhammad Ahtsam3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3193-3212, 2023, DOI:10.32604/iasc.2023.041232

    Abstract To meet the high-performance requirements of fifth-generation (5G) and sixth-generation (6G) wireless networks, in particular, ultra-reliable and low-latency communication (URLLC) is considered to be one of the most important communication scenarios in a wireless network. In this paper, we consider the effects of the Rician fading channel on the performance of cooperative device-to-device (D2D) communication with URLLC. For better performance, we maximize and examine the system’s minimal rate of D2D communication. Due to the interference in D2D communication, the problem of maximizing the minimum rate becomes non-convex and difficult to solve. To solve this problem, a learning-to-optimize-based algorithm is proposed… More >

  • Open Access


    Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

    Nitin Mittal1, Rohit Salgotra2,3, Abhishek Sharma4, Sandeep Kaur5, S. S. Askar6, Mohamed Abouhawwash7,8,*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3159-3177, 2023, DOI:10.32604/iasc.2023.041059

    Abstract The optimization of cognitive radio (CR) system using an enhanced firefly algorithm (EFA) is presented in this work. The Firefly algorithm (FA) is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies. It has already proved its competence in various optimization problems, but it suffers from slow convergence issues. To improve the convergence performance of FA, a new variant named EFA is proposed. The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions, and simulation results show its superior performance compared to biogeography-based optimization (BBO), bat algorithm, artificial bee colony, and FA. As an… More >

  • Open Access


    Aspect-Based Sentiment Classification Using Deep Learning and Hybrid of Word Embedding and Contextual Position

    Waqas Ahmad1, Hikmat Ullah Khan1,2,*, Fawaz Khaled Alarfaj3,*, Saqib Iqbal4, Abdullah Mohammad Alomair3, Naif Almusallam3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3101-3124, 2023, DOI:10.32604/iasc.2023.040614

    Abstract Aspect-based sentiment analysis aims to detect and classify the sentiment polarities as negative, positive, or neutral while associating them with their identified aspects from the corresponding context. In this regard, prior methodologies widely utilize either word embedding or tree-based representations. Meanwhile, the separate use of those deep features such as word embedding and tree-based dependencies has become a significant cause of information loss. Generally, word embedding preserves the syntactic and semantic relations between a couple of terms lying in a sentence. Besides, the tree-based structure conserves the grammatical and logical dependencies of context. In addition, the sentence-oriented word position describes… More >

  • Open Access


    A New Method for Image Tamper Detection Based on an Improved U-Net

    Jie Zhang, Jianxun Zhang*, Bowen Li, Jie Cao, Yifan Guo

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2883-2895, 2023, DOI:10.32604/iasc.2023.039805

    Abstract With the improvement of image editing technology, the threshold of image tampering technology decreases, which leads to a decrease in the authenticity of image content. This has also driven research on image forgery detection techniques. In this paper, a U-Net with multiple sensory field feature extraction (MSCU-Net) for image forgery detection is proposed. The proposed MSCU-Net is an end-to-end image essential attribute segmentation network that can perform image forgery detection without any pre-processing or post-processing. MSCU-Net replaces the single-scale convolution module in the original network with an improved multiple perceptual field convolution module so that the decoder can synthesize the… More >

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