Song Xu^1,2,*, Liang Xuan^1,2, Yifeng Li^1,2, Qiang Zhang^1,2

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070472 - 09 December 2025

Abstract The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts. In the industrial robot production scenarios, the 6D pose estimation of industrial parts mainly faces two challenges: one is the loss of information and interference caused by occlusion and stacking in the sorting scenario, the other is the difficulty of feature extraction due to the weak texture of industrial parts. To address the above problems, this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts, namely CB-PVNet. On the… More >

Nikhil S. Mane¹, Sheetal Kumar Dewangan^2,*, Sayantan Mukherjee³, Pradnyavati Mane⁴, Deepak Kumar Singh¹, Ravindra Singh Saluja⁵

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.072090 - 10 November 2025

Abstract The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids. Researchers rely on experimental investigations to explore nanofluid properties, as it is a necessary step before their practical application. As these investigations are time and resource-consuming undertakings, an effective prediction model can significantly improve the efficiency of research operations. In this work, an Artificial Neural Network (ANN) model is developed to predict the thermal conductivity of metal oxide water-based nanofluid. For this, a comprehensive set of 691 data points was collected from the literature. This dataset is split More >

Guangyu Xu^1,2, Siyuan Xu³, Siyu Lu^4,*, Yuxin Liu¹, Bo Yang¹, Junmin Lyu⁵, Wenfeng Zheng^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4037-4053, 2025, DOI:10.32604/cmes.2025.074901 - 23 December 2025

Abstract Robust stereo disparity estimation plays a critical role in minimally invasive surgery, where dynamic soft tissues, specular reflections, and data scarcity pose major challenges to traditional end-to-end deep learning and deformable model-based methods. In this paper, we propose a novel disparity estimation framework that leverages a pretrained StyleGAN generator to represent the disparity manifold of Minimally Invasive Surgery (MIS) scenes and reformulates the stereo matching task as a latent-space optimization problem. Specifically, given a stereo pair, we search for the optimal latent vector in the intermediate latent space of StyleGAN, such that the photometric reconstruction… More >

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 >

Yu Tao¹, Tian Yin², Yang Jie^1,*

Journal on Artificial Intelligence, Vol.7, pp. 549-570, 2025, DOI:10.32604/jai.2025.072727 - 01 December 2025

Abstract To address the issue of insufficient accuracy in attitude estimation using Inertial Measurement Units (IMU), this paper proposes a multi-sensor fusion attitude estimation method based on an improved Error-State Kalman Filter (ESKF). Several adaptive mechanisms are introduced within the standard ESKF framework: first, the process noise covariance is dynamically adjusted based on gyroscope angular velocity to enhance the algorithm’s adaptability under both static and dynamic conditions; second, the Sage-Husa algorithm is employed to estimate the measurement noise covariance of the accelerometer and magnetometer in real-time, mitigating disturbances caused by external accelerations and magnetic fields. Additionally,… More >

Fawad Zaman^1,#, Adeel Iqbal^2,#, Bakhtiar Ali¹, Abdul Khader Jilani Saudagar^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2535-2550, 2025, DOI:10.32604/cmes.2025.072638 - 26 November 2025

Abstract Accurate estimation of the Direction-of-Arrival (DoA) of incident plane waves is essential for modern wireless communication, radar, sonar, and localization systems. Precise DoA information enables adaptive beamforming, spatial filtering, and interference mitigation by steering antenna array beams toward desired sources while suppressing unwanted signals. Traditional one-dimensional Uniform Linear Arrays (ULAs) are limited to elevation angle estimation due to geometric constraints, typically within the range [0, π]. To capture full spatial characteristics in environments with multipath and angular spread, joint estimation of both elevation and azimuth angles becomes necessary. However, existing 2D and 3D array geometries… More >

Amit Prakash Singh¹, Kajal Kaul^1,*, Anuradha Chug¹, Ravinder Kumar², Veerubommu Shanmugam²

Journal on Artificial Intelligence, Vol.7, pp. 451-468, 2025, DOI:10.32604/jai.2025.070773 - 06 November 2025

Abstract In agricultural farms in India where the staple diet for most of the households is potato, plant leaf diseases, namely Potato Early Blight (PEB) and Potato Late Blight (PLB), are quite common. The class label Plant Healthy (PH) is also used. If these diseases are not identified early, they can cause massive crop loss and thereby incur huge economic losses to the farmers in the agricultural domain and can impact the gross domestic product of the nation. This paper presents a hybrid approach for potato plant disease severity estimation and classification of diseased and healthy… More >

Tian Tian¹, Huayi Wei^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-2, 2025, DOI:10.32604/icces.2025.011175

Abstract Brittle fracture is a critical failure mode in structural materials, and accurately simulating its evolution is essential for engineering design, material performance evaluation, and failure prediction. Traditional numerical methods, however, face significant challenges when dealing with higher-order fracture models and complex fracture behaviors. To overcome these challenges, this study proposes an innovative simulation framework based on higher-order finite element methods and adaptive mesh refinement, effectively balancing computational efficiency and simulation accuracy.
The research first develops a higher-order finite element method for the continuum damage fracture phase-field model. By incorporating higher-order finite element techniques, the proposed method… More >

Farzad Mohebbi^*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1417-1441, 2025, DOI:10.32604/fhmt.2025.069024 - 31 October 2025

Abstract An inverse analysis is presented to estimate line heat source in two-dimensional steady-state and transient heat transfer problems. A constant heat source is considered in the steady-state heat transfer problem (a parameter estimation problem) and a time-varying heat source is considered in the transient heat transfer problem (a function estimation problem). Since a general irregular 2D heat conducting body is considered, a body-fitted grid generation is used to mesh the domain. Then governing equations and associated boundary and initial conditions are transformed from the physical domain to the computational domain and finite difference method is… More >

He Wang, Shiqiang Li^*, Yiqi Liu, Jing Bian

Energy Engineering, Vol.122, No.11, pp. 4497-4521, 2025, DOI:10.32604/ee.2025.065244 - 27 October 2025

Abstract With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures, the number of measurement points supporting synchronous communication remains relatively limited. This poses challenges for conventional fault distance estimation methods, which are often tailored to simple topologies and are thus difficult to apply to large-scale, multi-node DC networks. To address this, a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper. First, a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range… More >