Article
Engineering, Multidisciplinary
Lin Chen, Hanyan Huang
Summary: This study proposes a generalized hybrid metamodel using radial basis function (RBF) and sparse polynomial chaos expansion (PCE) for covariance-based global sensitivity analysis (GSA) of multivariate outputs in engineering applications. An efficient sequential sampling method is introduced to improve the efficiency and performance of the RBF-PCE model in multivariate settings. Experimental results demonstrate that the proposed method outperforms existing methods in terms of accuracy and efficiency, with a significant reduction in sample demand compared to MCS-based Sobol' indices.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Kuan-Chung Lin, Cheng-Hung Hu, Kuo-Chou Wang
Summary: This work introduces a novel investigation into the use of the deep energy approach for addressing multi-physics issues often encountered in the field of piezoelectricity. The deep energy approach has become known as a robust numerical technique, demonstrating remarkable ability in handling complex nonlinearities and producing very precise results. The study comprehensively investigates the impact of various network characteristics on the accuracy of the approach, and the results show that the tanh activation function outperforms other solutions. Furthermore, the study expands the technique to examine piezoelectric composite plate actuators, demonstrating its flexibility and effectiveness.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Jiang Li, Xiaoping Wang, Zhigang Zeng
Summary: In real-world dialog systems, understanding user emotions and interacting anthropomorphically is crucial. Emotion Recognition in Conversation (ERC) is a key approach to achieve this goal and has gained increasing attention. This study proposes a model called DualRAN, which combines recurrent and attention mechanisms to model conversations. Experimental results show that DualRAN achieves competitive performance on multiple datasets.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Tran Cong Dao, Nguyen Thi Tam, Huynh Thi Thanh Binh
Summary: Wireless Sensor Networks (WSNs) face challenges related to limited energy resources, and network lifetime and energy consumption are critical considerations. This paper introduces a novel approach to extend network lifetime and reduce energy consumption in WSNs by optimizing network architecture selection. The proposed method addresses limitations of previous studies and consistently generates valid solutions by incorporating efficient encoding and tailor-made genetic operators. It also harnesses knowledge transfer in a multitask evolutionary algorithm to explore various network architectures and achieve state-of-the-art results in terms of solution quality, convergence rate, and running time.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Halar Memon, Eskil Gjerde, Alex Lynam, Amiya Chowdhury, Geert De Maere, Grazziela Figueredo, Tanvir Hussain
Summary: This study proposes the first use of the active learning framework in thermal spray to enhance the accuracy of in-flight particle characteristics prediction. By implementing Bayesian Optimization, the maximum uncertainty is reduced, significantly improving the prediction accuracy and informativeness of the existing database. The AL-driven optimization not only accurately predicts the particle characteristics but also finds expected improvements around desired in-flight characteristics.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Wenchun Jiang, Wenlu Xie, Xinyue Qi, Yangguang Deng, Yu Wan, Xuefang Xie
Summary: Various types of solid-state phase transformations (SSPT) occur during the SA508 steel welding process, leading to complex microstructure distribution and significant influence on residual stress distribution. To better control microstructure and residual stress, optimization of process parameters related to welding thermal cycles is necessary.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Sanjeev Kumar
Summary: The local scaling symmetry of the Lagrange density is used to study the electro-mechanical coupling effects in elastic dielectrics. This approach not only explains the induced polarization and electric potential, but also considers the geometric foundations. By introducing minimal replacement and the concept of gauge compensating one form field, the gauge invariance of the Lagrange density is restored. Different components of the gauge invariant energy density are constructed using scale invariant gauge curvature. Numerical simulations and validation demonstrate the effectiveness of the theory. Explorations of this kind of coupling could have significant implications in various industrial and laboratory applications.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Jicong Duan, Xibei Yang, Shang Gao, Hualong Yu
Summary: The study proposes a novel partition-based imbalanced multi-label learning algorithm, MLHC, which divides the original label space into disconnected subspaces using hierarchical clustering. It successfully tackles the class imbalance problem in multi-label data and outperforms other class imbalance multi-label learning algorithms.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yagang Zhang, Xue Kong, Jingchao Wang, Siqi Wang, Zheng Zhao, Fei Wang
Summary: This paper introduces a comprehensive wind speed forecasting system, including a signal reconstruction system, a signal reconstruction prediction model, and an error analysis algorithm. Experimental results show that the system has good performance and accuracy in wind speed prediction.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Huiling Zheng, Jun Yang, Wenda Kang, Yu Zhao
Summary: This paper develops a nonlinear accelerated model and inverse Gaussian process for depicting accelerated degradation data, considering the unit heterogeneity and nonlinear parameter-stress relationship. To address the challenge of parameter interval estimation, a novel two-step interval estimation method is proposed. The method derives generalized confidence intervals of random effect parameters and accelerated model parameters, as well as predictive reliability indexes, using the Cornish-Fisher expansion and generalized pivotal quantity procedure. Simulation studies and real examples demonstrate the effectiveness of the proposed method.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Jongchan Baek, Changhyeon Lee, Young Sam Lee, Soo Jeon, Soohee Han
Summary: This work utilizes reinforcement learning to achieve real-time control of a non-simulated triple inverted pendulum, using a structure-aware virtual experience replay method to enhance learning efficiency, and demonstrates its effectiveness on an actual system.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Dexuan Zou, Mengdi Li, Haibin Ouyang
Summary: In this study, a photovoltaic thermal collector is integrated into a combined cooling, heating, and power system to reduce primary energy consumption, operation cost, and carbon dioxide emission. By applying a novel genetic algorithm and constraint handling approach, it is found that the CCHP scenarios with PV/T are more efficient and achieve the lowest energy consumption.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Bo Fan, Zhongmin Wang
Summary: A 3D rotating hyperelastic composite REF model was proposed to analyze the influence of tread structure and rotating angular speed on the vibration characteristics of radial tire. Nonlinear dynamic differential equations and modal equations were established to study the effects of internal pressure, tread pressure sharing ratio, belt structure, and rotating angular speed on the vibration characteristics.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Shanya Baghel, Shuvashree Mondal
Summary: This study focuses on the reliability analysis of one-shot devices and applies it to SEER gallbladder cancer data. The two-parameter logistic-exponential distribution is used as the lifetime distribution and weighted minimum density power divergence estimators and maximum likelihood estimators are used for parameter estimation. The performance of estimators is evaluated through simulation experiments and the search for optimum inspection times is performed using a population-based heuristic optimization method.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Mohamed Mehdaoui
Summary: This paper presents an extended class of epidemic models and proves their existence and uniqueness using mathematical methods. Numerical simulations are conducted to compare the new models with traditional models. These results lay the groundwork for further research on other problems associated with the new proposed class of epidemic models.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Ann Nwankwo, Daniel Okuonghae
Summary: This study investigates the impact of macrophages' uptake of hemozoin on the dynamics of malaria within a human host. The results reveal a backward bifurcation phenomenon induced by the suppression of macrophages' phagocytic function due to their interaction with hemozoin. Moreover, numerical simulations demonstrate that the model can undergo a Hopf bifurcation with periodic solutions appearing in all compartments when the suppression rate is sufficiently small.
APPLIED MATHEMATICAL MODELLING
(2024)
Review
Automation & Control Systems
Qing Qin, Yuanyuan Chen
Summary: This paper offers a comprehensive review of retinal vessel automatic segmentation research, including both traditional methods and deep learning methods. In particular, supervised learning methods are summarized and analyzed based on CNN, GAN, and UNet. The advantages and disadvantages of existing segmentation methods are also outlined.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Si-Li Liu, Qi-Zhi Zhu, Lun-Yang Zhao, Qiao-Juan Yu, Jin Zhang, Ya-Jun Cao
Summary: This paper presents a study on the transition from brittle to ductile behavior in a low-porosity sandstone under drained conditions. Experimental results show that the mechanical behavior changes from brittle faulting to dilatant ductile flow with increasing effective confining pressure. A micromechanics-based elastoplastic damage model is formulated to simulate this behavior, taking into account the coupling between plasticity, damage, and pore pressure. The model effectively reproduces the main features of the sandstone with a brittle-ductile transition, as shown by the comparison with experimental data.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Chinu Singla, Raman Maini, Munish Kumar
Summary: This study investigates the field of age, gender, and handedness prediction through handwriting analysis, offering valuable insights into its applications in forensics, psychology, and education. A comprehensive survey is conducted on Indic and non-Indic scripts, highlighting research gaps and providing a roadmap for future advancements. The study concludes that non-Indic scripts achieve higher accuracy compared to Indic scripts, and focuses on providing a catalog of publicly accessible datasets for further research in this area.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Abhinav Pandey, Litton Bhandari, Vidit Gaur
Summary: This research proposes a novel model-agnostic framework based on genetic algorithms to identify and optimize the set of coefficients of the constitutive equations of engineering materials. The framework demonstrates solution convergence, scalability, and high explainability for a wide range of engineering materials. The experimental validation shows that the proposed framework outperforms commercially available software in terms of optimization efficiency.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
