Shengdong Cheng¹, Juncheng Gao^1,*, Hongning Qi^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 871-892, 2024, DOI:10.32604/cmes.2024.052830 - 20 August 2024

Abstract Driven piles are used in many geological environments as a practical and convenient structural component. Hence, the determination of the drivability of piles is actually of great importance in complex geotechnical applications. Conventional methods of predicting pile drivability often rely on simplified physical models or empirical formulas, which may lack accuracy or applicability in complex geological conditions. Therefore, this study presents a practical machine learning approach, namely a Random Forest (RF) optimized by Bayesian Optimization (BO) and Particle Swarm Optimization (PSO), which not only enhances prediction accuracy but also better adapts to varying geological environments… More > Graphic Abstract

Chenkai Hong^1,2,*, Zhongda Lyu^2,*, Fei Wang², Zhuo Zhao², Lei Wang²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1565-1592, 2024, DOI:10.32604/fdmp.2024.042685 - 23 July 2024

Abstract To scrutinize the characteristics of wave–current loads on a bridge shuttle-shaped cap–pile foundation, a 1:125 test model was considered in a laboratory flume. The inline, transverse and vertical wave–current forces acting on the shuttle-shaped cap–pile group model were measured considering both random waves and a combination of random waves with a current. The experimental results have shown that the wave–current forces can be well correlated with the wave height, the wavelength, the current velocity, the incident direction and the water level in the marine environment. An increase in the current velocity can lead to a More >

Wei Zhou¹, Xincong Jiang^2,*, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2069-2093, 2024, DOI:10.32604/cmes.2023.043248 - 29 January 2024

Abstract Edge devices, due to their limited computational and storage resources, often require the use of compilers for program optimization. Therefore, ensuring the security and reliability of these compilers is of paramount importance in the emerging field of edge AI. One widely used testing method for this purpose is fuzz testing, which detects bugs by inputting random test cases into the target program. However, this process consumes significant time and resources. To improve the efficiency of compiler fuzz testing, it is common practice to utilize test case prioritization techniques. Some researchers use machine learning to predict… More >

Zhoujie Zhu¹, Gang Wang¹, Qingquan Liu¹, Guojun Wang², Rui Dong², Dayong Zhang^2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 625-639, 2024, DOI:10.32604/fdmp.2023.042128 - 12 January 2024

Abstract Important challenges must be addressed to make wind turbines sustainable renewable energy sources. A typical problem concerns the design of the foundation. If the pile diameter is larger than that of the jacket platform, traditional mechanical models cannot be used. In this study, relying on the seabed soil data of an offshore wind farm, the m-method and the equivalent embedded method are used to address the single-pile wind turbine foundation problem for different pile diameters. An approach to determine the equivalent pile length is also proposed accordingly. The results provide evidence for the effectiveness and reliability More >

Sheng Lan¹, Fei Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09077

Abstract Non-autoclaved concrete pipe piles are gaining attention as an environmentally friendly alternative to autoclaved concrete pipe piles. The purpose of this study was to investigate the changes in the impact resistance of a non-autoclaved concrete pipe pile with the addition of rubber. To this end, various volume fractions of rubber particles were used to replace the fine sand in the non-autoclaved pipe pile concrete (0%, 5%, 10% and 15%). Additionally, the axial impact resistance of rubber modified non-autoclaved concrete pipe pile was studied from the concrete materials and pipe pile components through quasi-static, dynamic compression… More >

Ziyang Jiang¹, Ziping Wang^1,*, Kan Feng¹, Yang Zhang², Rahim Gorgin¹

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 557-569, 2023, DOI:10.32604/sdhm.2023.042393 - 17 November 2023

Abstract With the advancement of computer and mathematical techniques, significant progress has been made in the 3D modeling of foundation piles. Existing methods include the 3D semi-analytical model for non-destructive low-strain integrity assessment of large-diameter thin-walled pipe piles and the 3D soil-pile dynamic interaction model. However, these methods have complex analysis procedures and substantial limitations. This paper introduces an innovative and streamlined 3D imaging technique tailored for the detection of pile damage. The approach harnesses the power of an eight-channel ring array transducer to capture internal reflection signals within foundation piles. The acquired signals are subsequently… More >

JIAO HU, JIALU MO, XIANGLIN CHENG^*

BIOCELL, Vol.47, No.8, pp. 1689-1701, 2023, DOI:10.32604/biocell.2023.029409 - 28 August 2023

Abstract Epilepsy is one of the most common neurological diseases worldwide with a high prevalence and unknown pathogenesis. Further, its control is challenging. It is generally accepted that an imbalance between the excitatory and inhibitory properties of the central nervous system (CNS) leads to a large number of abnormally synchronized neuronal discharges in the brain. Transient receptor potential vanilloid protein type 1 (TRPV1) is a non-selective cation channel that contributes to the regulation of the nervous system and influences the excitability of the nervous system. This includes the release of neurotransmitters, action potential generation due to More >

Zaihe Cheng¹, Yuwen Tao², Xiaoqing Gu³, Yizhang Jiang², Pengjiang Qian^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1613-1633, 2023, DOI:10.32604/cmes.2023.027708 - 26 June 2023

Abstract Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-Kang (TSK) fuzzy system framework is proposed for epilepsy data classification in this study. The new method is based on the maximum mean discrepancy (MMD) method and TSK fuzzy system, as a basic model for the classification of epilepsy data. First, for medical data, the interpretability of TSK fuzzy systems can ensure that the prediction results are traceable and safe. Second, in view of the deviation in the data distribution between the real source domain and the target domain, MMD is used to measure the distance between… More >

Jiali Wang¹, Bing Li², Chengyu Qiu¹, Xinyun Zhang¹, Yuting Cheng¹, Peihua Wang¹, Ta Zhou³, Hong Ge², Yuanpeng Zhang^1,3,*, Jing Cai^3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4843-4866, 2023, DOI:10.32604/cmc.2023.037457 - 29 April 2023

Abstract Epilepsy is a central nervous system disorder in which brain activity becomes abnormal. Electroencephalogram (EEG) signals, as recordings of brain activity, have been widely used for epilepsy recognition. To study epileptic EEG signals and develop artificial intelligence (AI)-assist recognition, a multi-view transfer learning (MVTL-LSR) algorithm based on least squares regression is proposed in this study. Compared with most existing multi-view transfer learning algorithms, MVTL-LSR has two merits: (1) Since traditional transfer learning algorithms leverage knowledge from different sources, which poses a significant risk to data privacy. Therefore, we develop a knowledge transfer mechanism that can More >

Srikanth Cherukuvada, R. Kayalvizhi^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4101-4118, 2023, DOI:10.32604/cmc.2023.036207 - 31 March 2023

Abstract The term Epilepsy refers to a most commonly occurring brain disorder after a migraine. Early identification of incoming seizures significantly impacts the lives of people with Epilepsy. Automated detection of epileptic seizures (ES) has dramatically improved the life quality of the patients. Recent Electroencephalogram (EEG) related seizure detection mechanisms encountered several difficulties in real-time. The EEGs are the non-stationary signal, and seizure patterns would change with patients and recording sessions. Further, EEG data were disposed to wide noise varieties that adversely moved the recognition accuracy of ESs. Artificial intelligence (AI) methods in the domain of… More >