Mujahid Ali^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2161-2194, 2024, DOI:10.32604/cmc.2024.058888 - 18 November 2024

Abstract Forecasting travel demand requires a grasp of individual decision-making behavior. However, transport mode choice (TMC) is determined by personal and contextual factors that vary from person to person. Numerous characteristics have a substantial impact on travel behavior (TB), which makes it important to take into account while studying transport options. Traditional statistical techniques frequently presume linear correlations, but real-world data rarely follows these presumptions, which may make it harder to grasp the complex interactions. Thorough systematic review was conducted to examine how machine learning (ML) approaches might successfully capture nonlinear correlations that conventional methods may… More >

Pengfei Duan^1,*, Luling Li¹, Jianhui Liu¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012431

Abstract The supply of hydrogen-blended natural gas to civil and industrial users can assist downstream firm to achieve carbon emission reduction, and ensure energy security as an alternative gas source. This application mode has been widely concerned by urban gas enterprises. This paper focuses on the leakage problem of hydrogen-blended pipelines in utility tunnel due to corrosion and other reasons. Using dimensional analysis method, a model experiment is designed to verify that the three-dimensional compressible fluid model coupled with transport equations can effectively simulate the concentration change of hydrogen-blended natural gas after leakage in the utility… More >

William H. Marshall V^1,2,*, Lydia K. Wright²

Congenital Heart Disease, Vol.19, No.4, pp. 419-433, 2024, DOI:10.32604/chd.2024.056608 - 31 October 2024

Abstract Heart failure (HF) is common in patients with congenital heart disease (CHD) and there are limited medical therapies. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are a proven medical therapy in patients with acquired HF, though data are limited in patients with CHD. The aim of this review is to summarize the current evidence for use of SGLT2i in patients with CHD and identify future directions for study. In available publications, SGLT2i in patients with CHD seem to be well tolerated, with similar side effect profile to patients with acquired HF. Improvement in functional capacity and natriuretic More >

Yijun Gao^1,2, Yong Wang^1,*, Qing Na¹, Jiawei Zhang¹, Aixiang Wu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2443-2458, 2024, DOI:10.32604/fdmp.2024.051385 - 28 October 2024

Abstract Filling methods in the mining industry can maximize the recovery of mineral resources and protect the underground and surface environments. In recent years, such methods have been widely used in metal mines where pipeline transportation typically plays a decisive role in the safety and stability of the entire filling system. Because the filling slurry contains a large percentage of solid coarse particles, the involved pipeline is typically eroded and often damaged during such a process. A possible solution is the so-called nesting repair technology. In the present study, nesting a 127 mm outer diameter pipeline… More >

Fan Yang^1,2,*, Honggang Mi^1,2, Jian Wu^1,2, Qi Yang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2637-2656, 2024, DOI:10.32604/fdmp.2024.048574 - 28 October 2024

Abstract The gas production of deep coalbed methane wells in Linxing-Shenfu block decreases rapidly, the water output is high, the supporting effect is poor, the effective supporting fracture size is limited, and the migration mechanism of proppant in deep coal reservoir is not clear at present. To investigate the migration behavior of proppants in complex fractures during the volume reconstruction of deep coal and rock reservoirs, an optimization test on the conductivity of low-density proppants and simulations of proppant migration in complex fractures of deep coal reservoirs were conducted. The study systematically analyzed the impact of… More >

Jingfa Ma, Hu Liu^*, Lingxiao Chen

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 443-469, 2024, DOI:10.32604/cmc.2024.056209 - 15 October 2024

Abstract Demand-responsive transportation (DRT) is a flexible passenger service designed to enhance road efficiency, reduce peak-hour traffic, and boost passenger satisfaction. However, existing optimization methods for initial passenger requests fall short in addressing real-time passenger needs. Consequently, there is a need to develop real-time DRT route optimization methods that integrate both initial and real-time requests. This paper presents a two-stage, multi-objective optimization model for DRT vehicle scheduling. The first stage involves an initial scheduling model aimed at minimizing vehicle configuration, and operational, and CO₂ emission costs while ensuring passenger satisfaction. The second stage develops a real-time scheduling… More >

Yubo Jiao¹, Wei Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011157

Abstract The source-sink matching optimization problem is one of the more important aspects of carbon capture and storage (CCS) system planning studies, and a large number of studies have been conducted using mathematical modeling to assess the feasibility of deployment in the planning region, thus providing important decision support. A framework of optimization system applicable to source-sink matching analysis was constructed based on the structural relationship between directly connected sources and sinks, taking into account multiple factors (transport characteristics, CO₂ injection rate and connection period, etc.), which can ensure the feasibility of CO₂ pipeline transportation operation and… More >

Changtao Wang¹, Honghua Dai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010943

Abstract Orbital uncertainty propagation is fundamental in space situational awareness-related missions such as orbit prediction and tracking. Linear models and full nonlinear Monte Carlo simulations were primarily used to propagate uncertainties [1]. However, these methods hampered the application due to low precision and intensive computation. Over the past two decades, numerous nonlinear uncertainty propagators have been proposed. Among these methods, the state transition tensor (STT) method has been widely used due to its controllable accuracy and high efficiency [2]. However, this method has two drawbacks. First, its semi-analytical formulation is too intricate to implement, which hinders… 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 >

Yongsheng Zhu^1,2,*, Chong Liu^3,4, Chunlei Chen⁵, Xiaoting Lyu^3,4, Zheng Chen^3,4, Bin Wang⁶, Fuqiang Hu^3,4, Hanxi Li^3,4, Jiao Dai^3,4, Baigen Cai¹, Wei Wang^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1305-1325, 2024, DOI:10.32604/cmes.2024.054820 - 27 September 2024

Abstract The development of Intelligent Railway Transportation Systems necessitates incorporating privacy-preserving mechanisms into AI models to protect sensitive information and enhance system efficiency. Federated learning offers a promising solution by allowing multiple clients to train models collaboratively without sharing private data. However, despite its privacy benefits, federated learning systems are vulnerable to poisoning attacks, where adversaries alter local model parameters on compromised clients and send malicious updates to the server, potentially compromising the global model’s accuracy. In this study, we introduce PMM (Perturbation coefficient Multiplied by Maximum value), a new poisoning attack method that perturbs model More >