Umapathi Krishnamoorthy^1,*, Shanmugam Jagan², Mohammed Zakariah³, Abdulaziz S. Almazyad^4,*, K. Gurunathan⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3903-3926, 2024, DOI:10.32604/cmc.2024.055910 - 19 December 2024

Abstract Brain signal analysis from electroencephalogram (EEG) recordings is the gold standard for diagnosing various neural disorders especially epileptic seizure. Seizure signals are highly chaotic compared to normal brain signals and thus can be identified from EEG recordings. In the current seizure detection and classification landscape, most models primarily focus on binary classification—distinguishing between seizure and non-seizure states. While effective for basic detection, these models fail to address the nuanced stages of seizures and the intervals between them. Accurate identification of per-seizure or interictal stages and the timing between seizures is crucial for an effective seizure… More >

Taha Yacine Trad^1,*, Kheireddine Choutri¹, Mohand Lagha¹, Souham Meshoul², Fouad Khenfri³, Raouf Fareh⁴, Hadil Shaiba⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4757-4786, 2024, DOI:10.32604/cmc.2024.055634 - 19 December 2024

Abstract The popularity of quadrotor Unmanned Aerial Vehicles (UAVs) stems from their simple propulsion systems and structural design. However, their complex and nonlinear dynamic behavior presents a significant challenge for control, necessitating sophisticated algorithms to ensure stability and accuracy in flight. Various strategies have been explored by researchers and control engineers, with learning-based methods like reinforcement learning, deep learning, and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control systems. This paper investigates a Reinforcement Learning (RL) approach for both high and low-level quadrotor control systems, focusing on attitude stabilization and position… More >

Jiaming Zhan^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.011189

Abstract Calcium fluoride (CaF₂) exhibits excellent optical properties, making it a promising candidate for preparing optical components. The actual applications underscore the importance of enhancing the ductile machining of such a difficult-to-machine material. This study starts by investigating the influence of thermal gradient fields on the mechanical behaviors of CaF₂ single crystal experimentally and theoretically, revealing the potential deformation mechanisms under various thermal additions. On this basis, a novel laser-assisted machining (LAM) scheme was proposed to enhance the deformability and machinability of CaF₂ single crystal by tailoring local thermal fields. The laser heating spot within the work material… More >

Valentina Salomoni^1,*, Gianluca Mazzucco¹, Giovanna Xotta¹, Riccardo Fincato¹, Beatrice Pomaro¹, Nico De Marchi¹, Jiangkun Zhang¹, Caterina Biscaro¹, Alberto Antonini¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.012130

Abstract Building materials such as concrete cement or concrete asphalt are highly heterogeneous composite materials that are often addressed as homogeneous media when a sufficiently large Representative Elementary Volume (REV) definition of the compound is accepted. Adopting a homogenous approach in the material behaviour modeling typically fails to elucidate the interaction between the various material phases. Recently, a meso-scale approach has emerged, enabling the study of composite/conglomerate materials within the REV volume, thereby making the principal material components explicit. At this scale, local interactions between inclusions and matrix are captured, revealing the presence of complex triaxial… More >

Qiuxia Fan^1,*, Jianyu Li¹, Xinqi Zhang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012048

Abstract In this paper, a series of smoothed finite element methods for the electromagnetic field distribution of non-contact LVDT are proposed. Firstly, the problem domain is discretized into a set of four-node tetrahedral elements, and the linear shape function is used to interpolate the domain variables. Then, the smooth region is further constructed by combining the nodes, edges and surfaces of the unit. Gradient smoothing technique is used to smooth the magnetic vector potential and scalar potential on each smooth domain. Based on the generalized smooth Galerkin weak form, the discretization system expression is derived and More >

Yifan Zhu^1,2, Fengxiang Xu^1,2,*, Zhen Zou^1,2, Xiaoqiang Niu^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.011085

Abstract Functionally graded lattice structures have garnered significant interest in impact research in recent years as novel structures because of the exceptional properties, including lightweight, high specific strength, and high specific stiffness. Aiming at the problem that the current functionally graded lattice structure incorporates gradient characteristics in the longitudinal or transverse direction, with no research on the diagonal gradient characteristics, this paper proposes a diagonal gradient lattice structure (DGLS) based on the body centered cubic (BCC) lattice structure. The quasi-static compression experiments were carried out on the resin samples manufactured through the photocuring molding technique. Besides,… More >

Li Wang^1,*, Xiaoyong Wang²

Energy Engineering, Vol.121, No.12, pp. 3953-3979, 2024, DOI:10.32604/ee.2024.056705 - 22 November 2024

Abstract Plug-in Hybrid Electric Vehicles (PHEVs) represent an innovative breed of transportation, harnessing diverse power sources for enhanced performance. Energy management strategies (EMSs) that coordinate and control different energy sources is a critical component of PHEV control technology, directly impacting overall vehicle performance. This study proposes an improved deep reinforcement learning (DRL)-based EMS that optimizes real-time energy allocation and coordinates the operation of multiple power sources. Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces. They often fail to strike an optimal balance between exploration and exploitation, and… More >

Yuhong Zhao^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012951

Abstract For a long time, the phase-field method has been considered as a mesoscale phenomenological method lacking physical accuracy and unable to be associated with the mechanical/functional properties of materials, etc. Some misunderstandings existing in these viewpoints need to be clarified. Therefore, it is necessary to propose or adopt the perspective of “unified or unifying phase-field modeling (UPFM)” to address these issues, which means that phase-field modeling has multiple unifications. Specifically, the phase-field method is the perfect unity of thermodynamics and kinetics, the unity of multi-scale models from micro- to meso- and then to macroscopic scale, More >

Qingrong Zeng, Xiaochen Liu, Xuefeng Zhu^*, Xiangkui Zhang, Ping Hu

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2065-2085, 2024, DOI:10.32604/cmes.2024.052620 - 31 October 2024

Abstract Traditional topology optimization methods often suffer from the “dimension curse” problem, wherein the computation time increases exponentially with the degrees of freedom in the background grid. Overcoming this challenge, we introduce a real-time topology optimization approach leveraging Conditional Generative Adversarial Networks with Gradient Penalty (CGAN-GP). This innovative method allows for nearly instantaneous prediction of optimized structures. Given a specific boundary condition, the network can produce a unique optimized structure in a one-to-one manner. The process begins by establishing a dataset using simulation data generated through the Solid Isotropic Material with Penalization (SIMP) method. Subsequently, we More >

Fujian Zhang¹, Ziyang Wang¹, Xiang Gao¹, Zhongqiang Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011736

Abstract Spontaneous droplet transport has broad application prospects in fields such as water collection and microfluidic chips. Despite extensive research in this area, droplet self-transport is still limited by issues such as slow transport velocity, short distance, and poor integrity. Here, a novel cross-hatch textured cone (CHTC) with multistage microchannels and circular grooves is proposed to realize ultrafast directional long-distance self-transport of multi-scale droplets. The CHTC triggers two modes of fluid transport: Droplet transport by Laplace pressure difference and capillary suction pressure-induced fluid transfer in microchannels on cone surfaces. By leveraging the coupling effect of the… More >