A Recognition Method for Marigold Picking Points Based on the Lightweight SCS-YOLO-Seg Model by Baojian Ma, Zhenghao Wu, Yun Ge, Bangbang Chen, He Zhang, Hao Xia, Dongyun Wang

“…The approach enhances the baseline YOLOv8n-seg architecture by replacing its backbone with StarNet and introducing C2f-Star, a novel lightweight feature extraction module. These modifications achieve substantial model compression, significantly reducing the model size, parameter count, and computational complexity (GFLOPs). …”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…Additionally, the model size is reduced by 75%, the parameter count by 78%, and computational workload by 30%. …”
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Double-diffusive mixed convection and entropy generation of Fe3O4-CoFe2O4-water hybrid nanofluid in an enclosure with a heated wavy cylinder by Sharaban Thohura, Md. Mamun Molla

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ADULT-ONSET STILL’S DISEASE: ASPECTS OF THE HEMATOLOGY CLINIC by M. M. Agakishiev, I. I. Mulina, A. M. Popova, I. N. Nechunaeva, L. M. Maslova, I. B. Kovynev, T. I. Pospelova

“…The role of monitoring clinical and biochemical blood parameters has been proved such as: blood ferritin level, C-reactive protein, hemogram parameters. …”
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Lithium-Ion Battery Health Assessment Method Based on Double Optimization Belief Rule Base with Interpretability by Zeyang Si, Jinting Shen, Wei He

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Carreau’s Rheological Model and A.N. Tikhonov’s Regularization Method: Parametric Identification Based on a CFD model by Anatoly A. Khvostov, Gazibeg O. Magomedov, Victor I. Ryazhskih, Aleksey V. Kovalev, Aleksey A. Zhuravlev, Magomed G. Magomedov

“…Study objects and methods. The study featured fondant mass produced according to the traditional formulation for Creamy Fondant unglazed candies. …”
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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. …”
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Semantic Segmentation of Brain Tumors Using a Local–Global Attention Model by Shuli Xing, Zhenwei Lai, Junxiong Zhu, Wenwu He, Guojun Mao

“…In our model, we introduce: (1) a semantic-oriented masked attention to enhance the feature extraction capability of the decoder; and (2) network-in-network blocks to increase channel modeling complexity in the encoder while reducing the parameter consumption associated with residual blocks. …”
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Two-Stage Estimation for Ultrahigh Dimensional Sparse Quadratic Discriminant Analysis by Shengbin Zhou, Yejin Huang, Xiue Gao

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Functional state of the pancreas in adolescents with peptic ulcer of duodenum by I. S. Lembryk

“…The significant differences in indicators of fecal elastase-1 levels in the first and second groups were estimated. Coprogram parameters were not sufficiently informative, and dominant sonographic features included the pancreas head edema and increased echogenicity of the parenchyma with the presence of linear hyperechoic echoes. …”
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Lightweight Pyramidal Multi-Scale Attention Residual Network for Plant Disease Recognition by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

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A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM by Peihao Yang, Jiarui Chen, Hairong Zhang, Sheng Li

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Enhancing Real-Time Road Object Detection: The RD-YOLO Algorithm With Higher Precision and Efficiency by Weijian Wang, Wei Yu

“…This integration improves the model’s feature extraction capabilities while reducing the number of parameters. …”
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An efficient approach on risk factor prediction related to cardiovascular disease around Kumbakonam, Tamil Nadu, India, using unsupervised machine learning techniques by K Kannan, A Menaga

“…The stability of the clusters is tested using bootstrapping cluster analysis, and the result showed that the clusters are highly stable. We have applied feature selection using principal component analysis. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

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Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

“…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. …”
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Vehicle Re-Identification Method Based on Efficient Self-Attention CNN-Transformer and Multi-Task Learning Optimization by Yu Wang, Rui Li, Yihan Shao

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Coal gangue image recognition model based on improved U−Net and top coal caving control by Yong YUAN, Zhenghan QIN, Yongqi XIA, Rang WU, Libao LI, Yong LI

“…The results substantiate that the FPN−ASPP−U−Net model delivers superior performance in coal gangue image segmentation, while also maintaining the lowest overall computational parameter count. This model demonstrates a well-balanced compromise between segmentation accuracy and computational efficiency, thereby optimizing both precision and processing speed in practical scenarios. …”
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Improved Dual-tree Complex Wavelet Packet Transform with Application to Fault Diagnosis by She Bo, Tian Fuqing, Liang Weige

“…A approach for gearbox fault diagnosis based on the improved dual-tree complex wavelet packet transform and spectral kurtosis is presented,vibration signals of gearbox are decomposed into various frequency band signals,the spectral kurtosis is computed to determine the parameters of band pass filter and got the optimal frequency band. …”
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Noise-agnostic quantum error mitigation with data augmented neural models by Manwen Liao, Yan Zhu, Giulio Chiribella, Yuxiang Yang

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