Bouncing Cosmology in fG,T Gravity with Logarithmic Trace Term by M. Farasat Shamir

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Intraparticle entanglement in noisy quantum channels: degradation and revival through amplitude damping by Animesh Sinha Roy, Namitha C. V., Subroto Mukerjee, Prasanta K. Panigrahi, Prasanta K. Panigrahi, Urbasi Sinha, Urbasi Sinha

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Predicting the Performance of Students Using Deep Ensemble Learning by Bo Tang, Senlin Li, Changhua Zhao

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Saliency-enhanced infrared and visible image fusion via sub-window variance filter and weighted least squares optimization. by Peicheng Wang, Tingsong Li, Pengfei Li

“…A saliency map measurement scheme based on weighted least squares optimization (WLSO) is then designed to compute weight maps, enhancing the visibility of important features. …”
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LHB-YOLOv8: An Optimized YOLOv8 Network for Complex Background Drop Stone Detection by Anjun Yu, Hongrui Fan, Yonghua Xiong, Longsheng Wei, Jinhua She

“…Finally, a bidirectional feature pyramid network (BiFPN) is introduced in the neck to effectively reduce the parameters and computational complexity and improve the overall performance of rockfall detection. …”
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Stability Optimization of Explicit Runge–Kutta Methods with Higher-Order Derivatives by Gerasim V. Krivovichev

“…The paper is devoted to the parametric stability optimization of explicit Runge–Kutta methods with higher-order derivatives. The key feature of these methods is the dependence of the coefficients of their stability polynomials on free parameters. …”
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ILViT: An Inception-Linear Attention-Based Lightweight Vision Transformer for Microscopic Cell Classification by Zhangda Liu, Panpan Wu, Ziping Zhao, Hengyong Yu

“…However, existing methods still struggle with the complexity and morphological diversity of cellular images, leading to limited accuracy or high computational costs. To overcome these constraints, we propose an efficient classification method that balances strong feature representation with a lightweight design. …”
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ABA-IDS: Attention-Based Autoencoder for Intrusion Detection in Assistive Mobility Robotic Network by Daniel Ayo Oladele, Elisha Didam Markus

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Hybrid mechanism‐data‐driven iron loss modelling for permanent magnet synchronous motors considering multiphysics coupling effects by Lin Liu, Wenliang Yin, Youguang Guo

“…Purely mechanistic models require detailed theoretical knowledge and exact parameters, often struggling to accurately describe complex systems, while purely data‐driven methods lack interpretability, which are susceptible to data noise and outliers in feature extraction and complicated pattern recognition. …”
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Shuffle window transformer DeepLabV3+: a lightweight convolutional neural network and transformer based hybrid semantic segmentation network by Yane Li, Zhichao Chen, Hongxia Qi, Ming Fan, Lihua Li

“…When the window size is fixed, by integrating window attention (WA) and shuffle WA mechanisms, cross-window global context modeling with linear computational complexity is achieved. Additionally, we enhance the atrous spatial pyramid pooling (ASPP) by incorporating strip pooling to construct a strip ASPP, effectively extracting both regular and irregular multi-scale (MS) features. …”
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Study on the Relationship Between Porosity and Mechanical Properties Based on Rock Pore Structure Reconstruction Model by Nan Xiao, Jun-Qing Chen, Xiang Qiu, Fu Huang, Tong-Hua Ling

“…Initially, high-resolution X-ray computed tomography (CT) was utilized to capture three-dimensional geometric features of Sichuan white sandstone microstructures, complemented by mechanical parameter acquisition through standardized testing protocols. …”
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Fault Diagnosis Method of Plunger Pump Based on Meta-Learning and Improved Multi-Channel Convolutional Neural Network Under Small Sample Condition by Xiwang Yang, Jiancheng Ma, Hongjun Hu, Jinying Huang, Licheng Jing

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MTMU: Multi-domain Transformation based Mamba-UNet designed for unruptured intracranial aneurysm segmentation by Bing Li, Nian Liu, Jianbin Bai, Jianfeng Xu, Yi Tang, Yan Liu

“…It endows the model with the capability of long-range dependency perceiving while balancing computational cost. Fourier Transform (FT) based connection allows for the enhancement of edge information in feature maps, thereby mitigating the difficulties in feature extraction caused by the small size of the target and the limited number of foreground pixels. …”
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A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. …”
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Research on Vehicle Road Noise Prediction Based on AFW-LSTM by Yan Ma, Ruxue Dai, Tao Liu, Jian Liu, Shukai Yang, Jingjing Wang

“…However, using the traditional TPA (transfer path analysis) method and CAE (Computer-Aided Engineering) method to analyze the road noise problem has the problems of complex transfer path, difficult acquisition of modeling parameters, long duration and high cost. …”
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A fiber channel modeling method based on complex neural networks by Haifeng Yang, Yongjun Wang, Chao Li, Lu Han, Qi Zhang, Xiangjun Xin

“…To address this limitation, we propose a complex-valued conditional generative adversarial network (C-CGAN) in this paper to comprehensively learn channel features. We describe the architecture and parameters of the C-CGAN and employ complex-valued windowed construction for input data. …”
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Lightweight YOLOv8 for tongue teeth marks and fissures detection based on C2f_DCNv3 by Chunyang Jin, Delong Zhang, Xiyuan Cao, Zhidong Zhang, Chenyang Xue, Yanjun Zhang

“…Additionally, the model reduces computational cost by approximately one-third in terms of FLOPS, maintaining high accuracy while greatly decreasing the number of parameters, thus offering a more robust and resource-efficient solution. …”
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Multi-step depth enhancement refine network with multi-view stereo. by Yuxuan Ding, Kefeng Li, Guangyuan Zhang, Zhenfang Zhu, Peng Wang, Zhenfei Wang, Chen Fu, Guangchen Li, Ke Pan

“…The MSDER-MVS network leverages the potent capabilities of modern deep learning in conjunction with the geometric intuition of traditional 3D reconstruction techniques, with a particular focus on optimizing the quality of the depth map and the efficiency of the reconstruction process.Our key innovations include a dual-branch fusion structure and a Feature Pyramid Network (FPN) to effectively extract and integrate multi-scale features. …”
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GPC-YOLO: An Improved Lightweight YOLOv8n Network for the Detection of Tomato Maturity in Unstructured Natural Environments by Yaolin Dong, Jinwei Qiao, Na Liu, Yunze He, Shuzan Li, Xucai Hu, Chengyan Yu, Chengyu Zhang

“…This study proposes a C2f-PC module based on partial convolution (PConv) for less computation, which replaced the original C2f feature extraction module of YOLOv8n. …”
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Machine Learning-Based Image Pattern Recognition Using Histogram of Oriented Gradient for Islanding Detection by Kumaresh Pal, Kumari Namrata, Ashok Kumar Akella, Manoj Gupta, Pannee Suanpang, Aziz Nanthaamornphong

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