Ahmed K. Ali¹, Jungpil Shin^2,*, Yujin Lim^3,*, Da-Hun Seong³

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4245-4278, 2025, DOI:10.32604/cmes.2025.073871 - 23 December 2025

Abstract Single-signal detection in orthogonal frequency-division multiplexing (OFDM) systems presents a challenge due to the time-varying nature of wireless channels. Although conventional methods have limitations, particularly in multi-input multioutput orthogonal frequency division multiplexing (MIMO-OFDM) systems, this paper addresses this problem by exploring advanced deep learning approaches for combined channel estimation and signal detection. Specifically, we propose two hybrid architectures that integrate a convolutional neural network (CNN) with a recurrent neural network (RNN), namely, CNN-long short-term memory (CNN-LSTM) and CNN-bidirectional-LSTM (CNN-Bi-LSTM), designed to enhance signal detection performance in MIMO-OFDM systems. The proposed CNN-LSTM and CNN-Bi-LSTM architectures are… More >

Yuyang Liu^1,2,*, Wensheng Zhou^1,2, Zhijie Wei^1,2, Engao Tang^1,2, Chenyang Shi³, Qirui Zhang^4,*, Zifeng Chen⁴

Energy Engineering, Vol.122, No.10, pp. 4245-4260, 2025, DOI:10.32604/ee.2025.066167 - 30 September 2025

Abstract After a long period of water flooding development, the oilfield has entered the middle and high water cut stage. The physical properties of reservoirs are changed by water erosion, which directly impacts reservoir development. Conventional numerical reservoir simulation methodologies typically employ static assumptions for model construction, presuming invariant reservoir geological parameters throughout the development process while neglecting the reservoir’s temporal evolution characteristics. Although such simplifications reduce computational complexity, they introduce substantial descriptive inaccuracies. Therefore, this paper proposes a meshless numerical simulation method for reservoirs that considers time-varying characteristics. This method avoids the meshing in traditional… More >

Olga Vlasova^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 2127-2137, 2024, DOI:10.32604/fdmp.2024.051202 - 23 August 2024

Abstract The dynamics of rotating hydrodynamic systems containing phase inclusions are interesting due to the related widespread occurrence in nature and technology. The influence of external force fields on rotating systems can be used to control the dynamics of inclusions of various types. Controlling inclusions is of current interest for space technologies. In low gravity, even a slight vibration effect can lead to the appearance of a force acting on phase inclusions near a solid boundary. When vibrations are applied to multiphase hydrodynamic systems, the oscillating body intensively interacts with the fluid and introduces changes in… More >

Siyuan Liu^1,*, Jinying Huang², Jiancheng Ma¹, Licheng Jing², Yuxuan Wang²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 761-777, 2024, DOI:10.32604/cmc.2024.049484 - 25 April 2024

Abstract Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems, such as relatively ideal speed conditions and sample conditions. In engineering practice, the rotational speed of the machine is often transient and time-varying, which makes the sample annotation increasingly expensive. Meanwhile, the number of samples collected from different health states is often unbalanced. To deal with the above challenges, a complementary-label (CL) adversarial domain adaptation fault diagnosis network (CLADAN) is proposed under time-varying rotational speed and weakly-supervised conditions. In the weakly supervised learning condition, machine prior information is used for sample annotation More >

Yujie Duan¹, Jianguo Liang^1,*, Jianglin Liu¹, Haifeng Gao¹, Yinhui Li², Jinzhu Zhang¹, Xinyu Wen³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1239-1261, 2024, DOI:10.32604/cmes.2023.044400 - 29 January 2024

Abstract In the fiber winding process, strong disturbance, uncertainty, strong coupling, and fiber friction complicate the winding constant tension control. In order to effectively reduce the influence of these problems on the tension output, this paper proposed a tension fluctuation rejection strategy based on feedforward compensation. In addition to the bias harmonic curve of the unknown state, the tension fluctuation also contains the influence of bounded noise. A tension fluctuation observer (TFO) is designed to cancel the uncertain periodic signal, in which the frequency generator is used to estimate the critical parameter information. Then, the fluctuation More >

Lei Zhu^1,2, Bin Liu², Xuewei Liu^2,*, Wei Deng¹, Wenjie Yao¹, Ying Fan¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.2, pp. 401-427, 2024, DOI:10.32604/fdmp.2023.041444 - 14 December 2023

Abstract To analyze the effects of a time-varying viscosity on the penetration length of grouting, in this study cement slurries with varying water-cement ratios have been investigated using the Bingham’s fluid flow equation and a discrete element method. A fluid-solid coupling numerical model has been introduced accordingly, and its accuracy has been validated through comparison of theoretical and numerical solutions. For different fracture forms (a single fracture, a branch fracture, and a fracture network), the influence of the time-varying viscosity on the slurry length range has been investigated, considering the change in the fracture aperture. The More >

Jiepeng Yao^1,2, Zhanjia Peng^1,2, Jingjing Liu^1,2, Chengxiao Fan^1,2, Zhongyi Wang^1,2,3, Lan Huang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2243-2265, 2023, DOI:10.32604/cmes.2023.028101 - 03 August 2023

Abstract In the establishment of differential equations, the determination of time-varying parameters is a difficult problem, especially for equations related to life activities. Thus, we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential equations. In the proposed framework, the learnable factors and scale parameters are used to implement adaptive activation functions, and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural networks. In this… More >

Lei Wang¹, Tiecheng Li¹, Hui Fan², Xuekai Hu¹, Lin Yang³, Xiaomei Yang^3,*

Energy Engineering, Vol.120, No.4, pp. 851-867, 2023, DOI:10.32604/ee.2023.025383 - 13 February 2023

Abstract In recent years, subsynchronous resonance (SSR) has frequently occurred in DFIG-connected series-compensated systems. For the analysis and prevention, it is of great importance to achieve wide area monitoring of the incident. This paper presents a Hankel dynamic mode decomposition (DMD) method to identify SSR parameters using synchrophasor data. The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors. It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes. Therefore, the SSR parameters can be calculated once the More >

Xujie Zhou^1,2,3,#, Yuting Sang^1,3,#, Jiajian Chen^1,3, Miao Mo^3,4, Jianjing Hou^1,3, Benlong Yang^1,3,*, Jiong Wu^1,2,3,*

Oncologie, Vol.24, No.3, pp. 451-469, 2022, DOI:10.32604/oncologie.2022.025226 - 19 September 2022

Abstract Background: To compare the time-varying recurrence patterns of different molecular subtypes of breast cancer in the contemporary era with those in the past era. Patients and Methods: This retrospective study included 14627 consecutive invasive breast cancer patients who underwent surgery from 2008 to 2016 at Fudan University Shanghai Cancer Center. We defined the period from 2013 to 2016 as the contemporary era and that from 2008 to 2012 as the past era. Five subtypes were defined according to the immunohistochemistry results. Emphasis was made on the changing patterns of recurrence for patients with different molecular subtypes changed… More >

Peng Zheng¹, Xiaozhen Guo^2,*, Guoguang Wen³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1451-1463, 2022, DOI:10.32604/cmes.2022.019769 - 19 April 2022

Abstract This paper deals with the fixed-time adaptive time-varying matrix projective synchronization (ATVMPS) of different dimensional chaotic systems (DDCSs) with time delays and unknown parameters. Firstly, to estimate the unknown parameters, adaptive parameter updated laws are designed. Secondly, to realize the fixed-time ATVMPS of the time-delayed DDCSs, an adaptive delay-unrelated controller is designed, where time delays of chaotic systems are known or unknown. Thirdly, some simple fixed-time ATVMPS criteria are deduced, and the rigorous proof is provided by employing the inequality technique and Lyapunov theory. Furthermore, the settling time of fixed-time synchronization (Fix-TS) is obtained, which More >