Shaocheng Wu¹, Honghao Liang¹, Xiaowei Chen¹, Tao Liu¹, Junpeng Ru^2,3, Qianhong Gong^2,3, Jin Li^2,3,*

Journal on Big Data, Vol.5, pp. 57-67, 2023, DOI:10.32604/jbd.2023.044257

Abstract Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model’s evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of the scheme proposed in this… More >

Yue Zhu, Tao Zhao^*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1139-1158, 2024, DOI:10.32604/cmes.2023.030178

Abstract The optimization of the rule base of a fuzzy logic system (FLS) based on evolutionary algorithm has achieved notable results. However, due to the diversity of the deep structure in the hierarchical fuzzy system (HFS) and the correlation of each sub fuzzy system, the uncertainty of the HFS's deep structure increases. For the HFS, a large number of studies mainly use fixed structures, which cannot be selected automatically. To solve this problem, this paper proposes a novel approach for constructing the incremental HFS. During system design, the deep structure and the rule base of the HFS are encoded separately. Subsequently,… More >

Xinzheng Wang^1,2,*, Bing Guo¹, Yan Shen³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1183-1206, 2024, DOI:10.32604/cmes.2023.029552

Abstract Predicting students’ academic achievements is an essential issue in education, which can benefit many stakeholders, for instance, students, teachers, managers, etc. Compared with online courses such as MOOCs, students’ academic-related data in the face-to-face physical teaching environment is usually sparsity, and the sample size is relatively small. It makes building models to predict students’ performance accurately in such an environment even more challenging. This paper proposes a Two-Way Neural Network (TWNN) model based on the bidirectional recurrent neural network and graph neural network to predict students’ next semester’s course performance using only their previous course achievements. Extensive experiments on a… More > Graphic Abstract

Ali Ahmadi Shahrakht¹, Parisa Hajirahimi², Omid Rostami³, Diego Martín^4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3059-3081, 2023, DOI:10.32604/iasc.2023.040502

Abstract As the internet of things (IoT) continues to expand rapidly, the significance of its security concerns has grown in recent years. To address these concerns, physical unclonable functions (PUFs) have emerged as valuable tools for enhancing IoT security. PUFs leverage the inherent randomness found in the embedded hardware of IoT devices. However, it has been shown that some PUFs can be modeled by attackers using machine-learning-based approaches. In this paper, a new deep learning (DL)-based modeling attack is introduced to break the resistance of complex XAPUFs. Because training DL models is a problem that falls under the category of NP-hard… More >

Yong Zhang^1,*, Jie Wang^2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09368

Abstract Ferroelectric materials have been widely used in various electromechanical devices such as sensors, actuators, transducers and energy storage devices due to their distinguished electromechanical coupling properties. Ferroelectric materials usually bear large mechanical loads and high electric fields in order to give full play to their potential. The interaction between fracture and dielectric breakdown is able to occur since the filler inside a crack will change the dielectric behaviors around it and dielectric breakdown can change the local mechanical properties of dielectric materials because of its weakening of chemical bonds. Therefore, a comprehensive and in-depth understanding of the fracture and dielectric… More >

Liang Wang^1,*, Haibo Su¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09107

Abstract This work proposes a novel multi-phase-field formulation to characterize the distinct damage mechanisms and quasi-brittle fracture behaviors in FRC. The phase field driving forces for each failure mechanisms are first defined based on an anisotropic energy split scheme. Then, the PF degradation functions pertinent to each failure mode are properly defined with corresponding material fracture quantities, which enables the derivation of embedded Hashin failure criteria for fiber- and matrix failures respectively. Furthermore, the material damaged stiffness is redefined within the anisotropic CDM framework, and a linear CZM is mathematically derived for each of the typical failure mechanisms. Finally, the model… More >

Shichao Luo¹, Yinan Cui^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010223

Abstract The responses of metals subjected to super high rates of deformation (> 10!/�), as shocking loading, is an area of active research. At such extreme loading rates, subsonic, transonic, and even supersonic dislocation (compared with the shear wave speed in metals) play a crucial role in plastic deformation. The behavior of high-speed dislocations is much more complex than that of quasi-static dislocations under static loads, as their self-force is history-dependent, and their evolution of density is rate-relevant. However, the fundamental questions regarding the self-force and evolution of high-speed dislocations in impacted materials is largely unknown. To address this gap, this… More >

Cho Mar Aye¹, Kittinan Wansaseub², Sumit Kumar³, Ghanshyam G. Tejani⁴, Sujin Bureerat¹, Ali R. Yildiz⁵, Nantiwat Pholdee^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2111-2128, 2023, DOI:10.32604/cmes.2023.028632

Abstract This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted optimization for airfoil shape optimization. The optimization problem is posed to maximize the lift and drag coefficient ratio subject to airfoil geometry constraints. Computational Fluid Dynamic (CFD) and XFoil tools are used for high and low-fidelity simulations of the airfoil to find the real objective function value. A special multi-objective sub-optimization problem is proposed for multiple points infill sampling exploration to improve the surrogate model constructed. To validate and further assess the proposed methods, a conventional surrogate-assisted optimization method and an infill sampling surrogate-assisted optimization criterion are applied with multi-fidelity simulation, while their… More > Graphic Abstract

O. K. Koriko, I. L. Animasaun^*

Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-13, 2017, DOI:10.5098/hmt.8.26

Abstract The motion of air (i.e fluid) in which tiny particle rotates past a pointed surface of a rocket (as in space science), over a bonnet of a car and past a pointed surface of an aircraft is of important to experts in all these fields. Geometrically, all the domains of fluid flow in all these cases can be referred to as the upper horizontal surface of a paraboloid of revolution (uhspr). Meanwhile, the solution of the corresponding partial differential equation is an open question due to unavailability of suitable similarity variable to non-dimensionalize the angular momentum equation. This article unravels… More >

Cuiyu Wang, Xinyu Li, Yiping Gao^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1849-1870, 2023, DOI:10.32604/cmes.2023.028098

Abstract Job shop scheduling (JS) is an important technology for modern manufacturing. Flexible job shop scheduling (FJS) is critical in JS, and it has been widely employed in many industries, including aerospace and energy. FJS enables any machine from a certain set to handle an operation, and this is an NP-hard problem. Furthermore, due to the requirements in real-world cases, multi-objective FJS is increasingly widespread, thus increasing the challenge of solving the FJS problems. As a result, it is necessary to develop a novel method to address this challenge. To achieve this goal, a novel collaborative evolutionary algorithm with two-population based… More >