Improved UAV Target Detection Model for RT-DETR by Yong He, Yufan Pang, Guolin Ou, Renfeng Xiao, Yifan Tang

“…On the VisDrone2019 dataset, the mAP0.5 of the enhanced model demonstrates a 3.5% improvement, accompanied by a 6.1% and 2.9% reduction in parameters and computations, respectively. The efficacy of these enhancements is substantiated by the model’s superior performance in comparison to other target detection models at equivalent levels.…”
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A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study by Lingfeng Zhang, Gang Xie, Yue Zhang, Yue Zhang, Junlin Li, Junlin Li, Wuli Tang, Wuli Tang, Ling Yang, Ling Yang, Kang Li

“…The radiomics features linked to MCE were pinpointed through a consistency test, Student’s t test and the least absolute shrinkage and selection operator (LASSO) method for selecting features. …”
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Neural mechanisms of maladaptive risk decision-making across psychiatric disorders by Cancan Lin, Yuhui Wang, Wenjie Xia, Defu Zhang, Xvbo Wang, Yue Wang, Yuxin Du, Hao Yu, Shanling Ji

“…Second, disorder-specific neural signatures are noted, such as insular dysfunction in anxiety disorders, ventral striatal blunting in depression, and orbitofrontal-insula decoupling in schizophrenia. Third, computational modeling reveals distinct alterations in risk sensitivity, loss aversion, and reward valuation parameters across different diagnostic categories. …”
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Quantifying Uncertainties Associated with Liver Disorder Using Interval-Valued Complex Fuzzy Hypersoft Set by Muhammad Arshad, Atiqe Ur Rahman, Salwa El-Morsy

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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

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Lightweight pose estimation spatial-temporal enhanced graph convolutional model for miner behavior recognition by WANG Jianfang, DUAN Siyuan, PAN Hongguang, JING Ningbo

“…However, existing miner behavior recognition models based on graph convolution struggle to balance high accuracy and low computational complexity. To address this issue, this study proposed a miner behavior recognition model based on a lightweight pose estimation network (Lite-HRNet) and a multi-dimensional feature-enhanced spatial-temporal graph convolutional network (MEST-GCN). …”
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EEMtoolbox: A user‐friendly R package for flexible ensemble ecosystem modelling by Luz Valerie Pascal, Sarah A. Vollert, Malyon D. Bimler, Christopher M. Baker, Maude Vernet, Stefano Canessa, Christopher Drovandi, Matthew P. Adams

“…Ensemble ecosystem modelling (EEM) is a quantitative method used to parameterize models from theoretical ecosystem features rather than data. Two approaches have been considered to find parameter values satisfying those features: a standard accept–reject algorithm, appropriate for small ecosystem networks, and a sequential Monte Carlo (SMC) algorithm that is more computationally efficient for larger ecosystem networks. …”
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A novel vascular stent and insert concept to improve hemodynamics and support vascular health by Bahram Vaziri, Saadat Zirak, Mohammad Azadi, Amir Keshmiri, Nima Shokri

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EnsembleXAI-Motor: A Lightweight Framework for Fault Classification in Electric Vehicle Drive Motors Using Feature Selection, Ensemble Learning, and Explainable AI by Md. Ehsanul Haque, Mahe Zabin, Jia Uddin

“…A lightweight framework for fault diagnosis in EV drive motors is presented with the aid of Recursive Feature Elimination with Cross-Validation (RFE-CV), parameter optimization, and in-depth preprocessing. …”
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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…Despite the significant advancements in computer speech emotion recognition technology, the deployment of intelligent robots in this domain continues to encounter challenges related to inefficiency and emotional ambiguity. …”
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A Method of Word Sense Disambiguation with Recurrent Netural Networks by ZHANG Chunxiang, ZHOU Xuesong, GAO Xueyao

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Understanding user experience for mobile applications: a systematic literature review by Guoying Lu, Siyuan Qu, Yining Chen

“…We developed the Scenarios, Themes, Features, and Methodologies framework to examine both the theoretical and practical applications across multiple dimensions. …”
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Development and calibration of roundabout safety performance functions using machine learning: a case study from Amman, Jordan by Diana Al-Nabulsi, Aya Hassouneh

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DAMI-YOLOv8l: A multi-scale detection framework for light-trapping insect pest monitoring by Xiao Chen, Xinting Yang, Huan Hu, Tianjun Li, Zijie Zhou, Wenyong Li

“…The DMC module improves multi-scale feature extraction to enable the effective capture and merging of features across different detection scales while reducing network parameters. …”
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Implementation of Chernobyl disaster optimizer based feature selection approach to predict software defects [version 2; peer review: 2 approved, 1 not approved] by Himansu Das, Ajay Kumar Jena, Kunal Anand

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Research on scenario recognition for THz channels based on mRMR-GA by HAO Xinyu, LIAO Xi, WANG Yang, LIN Feng, LUO Jiao, ZHANG Jie

“…To address the challenges of excessive feature parameter redundancy and insufficient scene correlation in terahertz (THz) channel scenario recognition, a recognition algorithm integrating the minimal redundancy maximal relevance (mRMR) criterion with genetic algorithm (GA) optimization was constructed based on feature selection theory and evolutionary computation principles. …”
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Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature... by Mark Roper, Chrisantha Fernando, Lars Chittka

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LSANet: Lightweight Super Resolution via Large Separable Kernel Attention for Edge Remote Sensing by Tingting Yong, Xiaofang Liu

“…The core of LSANet is the large separable kernel attention mechanism, which efficiently expands the receptive field while retaining low computational overhead. By integrating this mechanism into an enhanced residual feature distillation module, the network captures long-range dependencies more effectively than traditional shallow residual blocks. …”
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SDNet: a lightweight ship detection network in remote sensing images by super-resolution enhancement and detail completion by Yu Tong, Jun Liu, Guixing Cao, Leyang Li, Yufei Wang

“…The main detector branch uses the adaptive cross-stage partial convolution (ACPC) module to form an efficient backbone. The feature pyramid network (FPN) combines with the cross-level wavelet transform multi-head attention (CWTMA) module for ship feature extraction. …”
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