TCSRNet: a lightweight tobacco leaf curing stage recognition network model by Panzhen Zhao, Panzhen Zhao, Songfeng Wang, Shijiang Duan, Aihua Wang, Lingfeng Meng, Yichong Hu

“…Secondly, the incorporation of Ghost modules significantly reduces the model’s computational complexity and parameter count through parameter sharing, enabling efficient recognition of tobacco leaf curing stages. …”
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StrawberryNet: Fast and Precise Recognition of Strawberry Disease Based on Channel and Spatial Information Reconstruction by Xiang Li, Lin Jiao, Kang Liu, Qihuang Liu, Ziyan Wang

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YOLOv11-RDTNet: A Lightweight Model for Citrus Pest and Disease Identification Based on an Improved YOLOv11n by Qiufang Dai, Shiyao Liang, Zhen Li, Shilei Lyu, Xiuyun Xue, Shuran Song, Ying Huang, Shaoyu Zhang, Jiaheng Fu

“…This model integrates multi-scale features and attention mechanisms to enhance recognition performance in complex scenarios, while adopting a lightweight design to reduce computational costs and improve deployment adaptability. …”
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Stability Selection and Consensus Clustering in R: The R Package sharp by Barbara Bodinier, Sabrina Rodrigues, Maryam Karimi, Sarah Filippi, Julien Chiquet, Marc Chadeau-Hyam

“…In stability selection, a feature selection algorithm is combined with a resampling technique to estimate feature selection probabilities. …”
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MELTING RATE CALCULATION ON PREHEATED WIRES OF VARIOUS CHEMISTRY UNDER ARC WELDING by Evgeny N. Varukha, Alexander S. Korobtsov, Igor S. Morozkin

“…The calculation accuracy by the empirical formula and by the known computational melting model of the same wires is comparatively appraised. …”
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NuCap: A Numerically Aware Captioning Framework for Improved Numerical Reasoning by Yuna Jeong, Yongsuk Choi

“…Despite the significant improvement in numerical reasoning power, our proposed approach has significantly fewer parameters and lower inference latency than large-scale vision language models, demonstrating both computational efficiency and stability. …”
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Design of Jitter Compensation Algorithm for Robot Vision Based on Optical Flow and Kalman Filter by B. R. Wang, Y. L. Jin, D. L. Shao, Y. Xu

“…Computing cases show that more point pairs are beneficial for getting more precise motion parameters. …”
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INTEGRATING ACOUSTIC MODULATION AND LISTENER DEMOGRAPHICS FOR ENHANCED PODCAST EMOTIONAL RESONANCE by Jun Ji, Kotchaphan Youngmee, Khachakrit Liamthaisong, Narisara Brikshavana

“…The research contradicts conventional views in previous studies by including an overall framework for the improvement of auditory features in podcasts. The underlying framework combines analytical methods, computational modelling, and machine learning in order to systematically enhance audio quality and consequently increase listener engagement.  …”
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Finite Element Model Updating in Bridge Structures Using Kriging Model and Latin Hypercube Sampling Method by Jie Wu, Quansheng Yan, Shiping Huang, Chao Zou, Jintu Zhong, Weifeng Wang

“…For FE model updating, the Kriging model is serving as a surrogate model, and it is a linear unbiased minimum variance estimation to the known data in a region which have similar features. To predict the relationship between the structural parameters and responses, samples are preselected, and then Latin hypercube sampling (LHS) method is applied. …”
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A Mixed-Integer Linear Formulation for a Dynamic Modified Stochastic p-Median Problem in a Competitive Supply Chain Network Design by Amir Hossein Sadeghi, Ziyuan Sun, Amirreza Sahebi-Fakhrabad, Hamid Arzani, Robert Handfield

“…The proposed model uses robust optimization in order to address the uncertainty of demand by allowing for the optimization of solutions that are not overly sensitive to small changes in the data or parameters. To manage the computational challenges presented by large-scale DMS-p-MP networks, a Lagrangian relaxation (LR) algorithm is employed. …”
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BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios by Xiao Tang, Kun Cao, Yunzhi Xia, Enkun Cui, Weining Zhao, Qiong Chen

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Impact of Tunnel Stern Design on Hydrodynamic Characteristics of Catamarans by Osmanov Osman, Aksu Erhan

“…This study investigates the influence of stern tunnel modifications on catamarans, emphasising their unique design and hydrodynamic features. Computational fluid dynamics (CFD) is used to assess resistance and flow around the hull. …”
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YOLOv8-LSW: A Lightweight Bitter Melon Leaf Disease Detection Model by Shuang Liu, Haobin Xu, Ying Deng, Yixin Cai, Yongjie Wu, Xiaohao Zhong, Jingyuan Zheng, Zhiqiang Lin, Miaohong Ruan, Jianqing Chen, Fengxiang Zhang, Huiying Li, Fenglin Zhong

“…The model incorporates the inverted bottleneck structure of LeYOLO-small to design the backbone network, utilizing depthwise separable convolutions and cross-stage feature reuse modules to achieve lightweight design, reducing the number of parameters while enhancing multi-scale feature extraction capabilities. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

“…This modification not only enhances feature extraction capabilities and detection accuracy for citrus fruits but also achieves a significant reduction in model parameters. …”
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YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

“…Additionally, an improved C3K2_PartialConv neck module is used to enhance information interaction and fusion among multi-scale features while maintaining computational efficiency. …”
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MobileDepth: Monocular Depth Estimation Based on Lightweight Vision Transformer by Yundong Li, Xiaokun Wei

“…Unlike CNNs, ViT is capable of capturing global feature information, but it requires numbers of parameters and data augmentation owing to its lack of inductive bias. …”
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Design of Airscrew Propeller as an Alternative Main Propulsion for Wing in Surface Effect (WiSE) A2C Using the Simplified Method Approach by Cahyo Sasmito, Rutma Pujiwat, Dany Hendrik Priatno, Iskendar Iskendar, Muh Hisyam Khoirudin, Dimas Bahtera Eskayudha

“…This method balances practicality with empirical data, offering a straightforward framework for generating initial design parameters without extensive computational demands. …”
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A Fast Prediction Model of Supercritical Airfoils Based on Deep Operator Network and Variational Autoencoder Considering Physical Constraints by Mengxin Liu, Yunjia Yang, Chenyu Wu, Yufei Zhang

“…Flow field prediction is crucial for evaluating the performance of airfoils and aerodynamic optimization. Computational fluid dynamics (CFD) methods usually require a considerable amount of computational resources and time. …”
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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…Additionally, we enhance the initial C2f layers with a modified block that integrates SimAM and DCNv4, minimizing the background noise and sharpening the focus on the relevant features. A second version of the C2f block using SimAM and standard convolutions ensures robust feature extraction in deeper layers with optimized computational efficiency. …”
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Accurately Identifying Different Ripening Stages of Strawberry Fruits in Complex Agricultural Scenarios by Xuefeng Ren, Yang Gan, Huan Liu, Yongming Chen, Ping Lin

“…Third, in the neck network, a multi-scale attention mechanism is introduced to preserve channel information and reduce computational overhead by reshaping selected channels into the batch dimension and grouping them into multiple sub-features, thereby facilitating the model’s perception of evenly distributed semantic features. …”
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