Conditional Diffusion-Flow models for generating 3D cosmic density fields: applications to f(R) cosmologies by Julieth K Riveros, Paola A Saavedra, Héctor J Hortúa, Jorge Enrique García-Farieta, Ivan Olier

“…To improve conditional generation, we introduce a novel multi-output model to develop feature representations of the cosmological parameters. …”
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Research on Equivalent One-Dimensional Cylindrical Modeling Method for Lead–Bismuth Fast Reactor Fuel Assemblies by Jinjie Xiao, Yongfa Zhang, Song Li, Ling Chen, Jiannan Li, Cong Zhang

“…Its neutron spectrum spans wider energy ranges with fast neutron dominance, exhibiting resonance phenomena across energy regions. These features require a fine energy group structure for fuel lattice calculations, significantly increasing computational demands. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Combined with an Inner Generalized Intersection-over-Union (Inner-GIoU) loss function to optimize bounding box geometric consistency, MLD-DETR achieves 36.7% AP50% and 14.5% APs on the VisDrone2019 dataset, outperforming the baseline RT-DETR by 3.2% and 1.8% in accuracy while achieving 20% parameter reduction and maintaining computational efficiency suitable for UAV platforms equipped with modern edge computing hardware. …”
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Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

“…Results on a self-built coal mine pedestrian-vehicle detection dataset show that the proposed model has parameters, computational load, and model size of 2.3 M, 4.0 GFLOPs, and 6.0 MB, respectively, achieving compression ratios of 4.9 times, 4.7 times, and 4.4 times compared to the baseline model. …”
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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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Enhancing Fatigue Life Prediction Accuracy: A Parametric Study of Stress Ratios and Hole Position Using SMART Crack Growth Technology by Yahya Ali Fageehi, Abdulnaser M. Alshoaibi

“…By uniquely employing an unstructured mesh method that significantly reduces computational overhead and automates mesh updates, this research overcomes traditional fracture simulation limitations. …”
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Machine Learning-Based Predictive Maintenance for Photovoltaic Systems by Ali Al-Humairi, Enmar Khalis, Zuhair A. Al-Hemyari, Peter Jung

“…Dimensionality reduction through the principal component analysis and correlation-based feature selection enhanced the model performance as well as the interpretability. …”
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Geometrical and structural design development of an active-bending structure from natural fibre pultruded profiles: The LightPRO shell by Evgenia Spyridonos, Yanan Guo, Marta Gil Pérez, Hanaa Dahy

“…The paper focuses on the geometrical and structural design development of the structure employing computational design tools for optimisation, ensuring design parameters and performance requirements were met. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Further innovation is evident in the introduction of the Residual Partial Convolutional Network (RPCN) as the backbone, which selectively applies convolutions to key channels, leveraging the concept of residuals to reduce computational redundancy and enhance accuracy. The enhancement of the RepBlock with Conv3XCBlock, along with the integration of a parameter-free attention mechanism within the convolutional layers, underscores our commitment to efficiency, ensuring that the model prioritizes valuable information while suppressing redundancy. …”
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Smart Solutions for Mega-Cities: Utilizing Long Short-Term Memory and Multi-Head Attention in Parking Prediction by Hasan Kemik, Tugba Dalyan, Murat Aydogan

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Impact of Nanofluid Flow over an Elongated Moving Surface with a Uniform Hydromagnetic Field and Nonlinear Heat Reservoir by Haroon U. R. Rasheed, Saeed Islam, Zeeshan Khan, Sayer O. Alharbi, Hammad Alotaibi, Ilyas Khan

“…Thus, innovative thermal transport fluids require to boost thermal conductivity and heat flow features to upsurge convection heat rate, and nanofluids have been effectively employed as standard heat transfer fluids. …”
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Efficient Side-Tuning for Remote Sensing: A Low-Memory Fine-Tuning Framework by Haichen Yu, Wenxin Yin, Hanbo Bi, Chongyang Li, Yingchao Feng, Wenhui Diao, Xian Sun

“…The proposed EST Block is the main component of the parallel network, which uses the multichannel adapter fusion module, gate layer and depthwise convolution to achieve feature selection and enhancement effects. In the evaluation, on six remote sensing datasets including object detection and semantic segmentation, EST achieved SOTA performance results using only less than 40<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> of the memory expenditure of full fine-tuning, which is better than all current parameter efficient fine-tuning methods. …”
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CDUNeXt: efficient ossification segmentation with large kernel and dual cross gate attention by Hailiang Xia, Chuantao Wang, Zhuoyuan Li, Yuchen Zhang, Shihe Hu, Jiliang Zhai

“…By designing lightweight module structures, utilizing large-kernel convolutions to extracts the long-distance dependencies of different features of the image, and adopting dual-cross-gate-attention(DCGA) to sequentially capture the channel and spatial dependencies so as to fast and accurate segmentation while maintaining fewer parameters and lower complexity. …”
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Mixture of prompts learning for vision-language models by Yu Du, Yu Du, Yu Du, Yu Du, Yu Du, Tong Niu, Tong Niu, Tong Niu, Tong Niu, Tong Niu, Rong Zhao, Rong Zhao, Rong Zhao, Rong Zhao, Rong Zhao

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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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Voice biomarkers as prognostic indicators for Parkinson’s disease using machine learning techniques by Ifrah Naeem, Allah Ditta, Tehseen Mazhar, Muhammad Anwar, Mamoon M. Saeed, Habib Hamam

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Sodium Silicate, Potassium Silicate, and Copper Sulfate’s Effectiveness In Vitro and In Silico against the Wood-decaying Fungus Phanerochaete chrysosporium by Mohammed Ibrahim Alghonaim, Sulaiman A. Alsalamah, Suha Alharbi, Abeer Mahmoud Mohammad

“…Surfactant and desiccant features of derived products of silicates are considered the main contributors in wood resistance to decay. …”
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Sketch-Guided Topology Optimization with Enhanced Diversity for Innovative Structural Design by Siyu Zhu, Jie Hu, Jin Qi, Lingyu Wang, Jing Guo, Jin Ma, Guoniu Zhu

“…The results reveal that the sketch-based constraints and length-scale control have distinct control effects on structural features and have different impacts on the mechanical performance and diversity, thereby enabling fine-grained and flexible human controllability to better balance conflicting objectives.…”
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Predicting survival in malignant glioma using artificial intelligence by Wireko Andrew Awuah, Adam Ben-Jaafar, Subham Roy, Princess Afia Nkrumah-Boateng, Joecelyn Kirani Tan, Toufik Abdul-Rahman, Oday Atallah

“…Imaging models excel at identifying tumour-specific features through radiomics, achieving high predictive accuracy. …”
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Research on Digital Media Art for Image Caption Generation Based on Integrated Transformer Models in CLIP by Lu Gao, Xiaofei Pang

“…In order to replace the fundamental features of conventional multi-modal fusion models, we propose a New Multi-modal Fusion Attention module (NMFA), which efficiently decreases parameter sizes and computational complexity in half. …”
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