Enhanced YOLOv8 with lightweight and efficient detection head for for detecting rice leaf diseases by Bo Gan, Guolin Pu, Weiyin Xing, Lianfang Wang, Shu Liang

“…The MSPPF improves the model’s ability to capture intricate details of rice leaf diseases at various scales by fusing multi-level feature maps. …”
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Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system by Li Xin, Li Yuesong

“…According to the key frames saved in the previous steps, feature points in local maps, sensor information, and loop information, a global optimization algorithm based on graph optimization model is constructed to optimize the position and pose of intelligent hardware system and the position of spatial feature points. …”
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Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders by Vahid Babaey, Hamid Reza Faragardi

“…Compared to conventional ensemble techniques like majority voting, our approach demonstrates superior anomaly detection performance by fusing diverse feature representations at the latent level rather than the output level. …”
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Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture by Junaid Aftab, Muhammad Attique Khan, Sobia Arshad, Shams ur Rehman, Dina Abdulaziz AlHammadi, Yunyoung Nam

“…In the training phase of the deep learning models, data augmentation is performed at the first stage on all selected datasets. …”
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End-to-End Mandarin Speech Reconstruction Based on Ultrasound Tongue Images Using Deep Learning by Fengji Li, Fei Shen, Ding Ma, Jie Zhou, Shaochuan Zhang, Li Wang, Fan Fan, Tao Liu, Xiaohong Chen, Tomoki Toda, Haijun Niu

“…The model includes a pretrained feature extractor to process ultrasound images, an upsampling block to generate speech, and discriminators to ensure the similarity and fidelity of the reconstructed speech. …”
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Association between triglyceride-glucose index and carotid atherosclerosis in Chinese steelworkers: a cross-sectional study by Haoyue Cao, Qinglin Li, Juxiang Yuan

“…Additionally, the TyG index demonstrated additional predictive capability beyond existing risk factors, significantly improving discriminatory performance (P < 0.05). In LASSO regression, TyG index and other covariables are screened as important feature variables to be incorporated into the development of machine learning models. …”
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Spatiotemporal Heterogeneity and Zoning Strategies of Multifunctional Trade-Offs and Synergies in Cultivated Land in the Hexi Corridor by Kaichun Zhou, Zixiang Sun, Tingting Ma, Yulin Li, Binggeng Xie

“…However, in application, there is often a conflict between the multiple functions of cultivated land and the limited ability of cultivated land to perform multiple functions. Therefore, this paper uses hot spot analysis, the IUEMS model, the InVEST model, Pearson correlation coefficients and self-organizing feature maps (SOFMs) to explore the multifunctional trade-offs and synergistic relationships of cultivated land in the Hexi Corridor at the grid scale and the zoning optimization scheme. …”
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Controlling Cable Driven Parallel Robots Operations&#x2014;Deep Reinforcement Learning Approach by Muhammad Kamran Joyo, Abdulmajeed M. Alenezi, Wenfu Xu, Mohamad A. Alawad, Muhmmad Tayyab Yaqoob, Noor Maricar, Sheroz Khan

“…Deep Reinforcement Learning (DRL) is a powerful approach for generating control strategies for a variety of complex systems, representing an emerging paradigm in control applications. An important feature of Deep RL is that it does not explicitly model the process, but instead it relies on optimization-driven techniques to devise effective control policies. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…For nonlinear models, GA-SVR performed the best (R² = 0.74, RMSE = 22.07 Mg/ha), surpassing the GA-CatBoost model (R² = 0.64, RMSE = 25.88 Mg/ha). …”
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Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth develop... by Jiahe Liu, Lang Chen, Yuxin Chen, Jingsong Luo, Kexin Yu, Linlin Fan, Chan Yong, Huiyu He, Simei Liao, Zongyuan Ge, Lihua Jiang, Lihua Jiang

“…Feature selection and SHapley Additive exPlanations (SHAP) analysis were utilised for model improvement and interpretability, respectively.ResultsExtraRFC achieved the best performance (Test AUC = 0.854, Accuracy = 0.798, F1 = 0.659), outperforming all other models across most metrics and external validations. …”
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Evaluation of the Occurrence of Initial Failures from Stress Concentrators in Welded Joints and Structural Elements by K. А. Molokov, V. V. Novikov, M. Dabalez

“…The literature on the topic was analyzed. The features of proven physical models and patterns of behavior of materials were taken into account. …”
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Characterization of lysine crotonylation-related lncRNAs for prognostic assessment and immune response in glioma by Miaomiao Song, Juan Xu, Zhonghao Gui, Yun Wu, Feifei Wang, Hongmei Sheng, Xueyong Huang, Junyu Qian, Haotian Qin, Ying Wang, Ying Wang

“…A multigene risk score model was constructed using univariate Cox, LASSO, and multivariate Cox regression analyses. …”
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Early IgE production is associated with accumulation of CD11b+ classical dendritic cells and CD11b+CD11c- macrophages in subcutaneous adipose tissue by D. B. Chudakov, M. V. Konovalova, O. D. Kotsareva, M. A. Shevchenko, M. A. Streltsova, A. A. Sergeev, G. V. Fattakhova

“…However, the role of distinct APCs upon long-term penetration of low antigen doses via the tissue barriers, is yet poorly understood, as well as specific features of these events upon entrance of the antigen through the subcutaneous adipose tissue which contains tissueassociated lymphoid clusters (TALC).The aim of this work was to determine the relationship between the local accumulation of various APCs in the subcutaneous adipose tissue and development of early IgE production in a clinically relevant experimental model of allergy with long-term administration of low allergen doses. …”
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The method of determining the forces in the tendon apparatus of human fingers by S. P. Panchenko, A. O. Mametiev, L. Yu. Naumenko, S. A. Chernyshov, T. O. Zub

“…Despite the power of specialized software, building digital models of biological objects and performing calculations is quite a difficult task. …”
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Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria by Zinabu Bekele Tadese, Teshome Demis Nimani, Kusse Urmale Mare, Fetlework Gubena, Ismail Garba Wali, Jamilu Sani

“…Permutation and Gini techniques were used to identify the feature's importance.ResultsRandom Forest achieved the highest performance with an accuracy of 92%, precision of 94%, recall of 91%, F1-score of 92%, and AUROC of 92%. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The CVC ClinicDB dataset supports this process, containing 1650 colonoscopy images classified as polyps or non-polyps. The best performance in the ensembles was done by the AD-22 + Transformer + SVM model, with an AUC of 0.99, a training accuracy of 99.50%, and a testing accuracy of 99.00%. …”
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Type 2 diabetes risk prediction using glycemic control Metrics: A machine learning approach by Radwan Qasrawi, Suliman Thwib, Ghada Issa, Razan Abu Ghoush, Malak Amro

“…Model performance was assessed via accuracy, area under the curve (AUC), and log loss. …”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…Using UAV data on vegetation indices, feature selection was performed using the Elastic Net. …”
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LYN and CYBB are pivotal immune and inflammatory genes as diagnostic biomarkers in recurrent spontaneous abortion by Zhuna Wu, Qiuya Lin, Zhimei Zhou, Yajing Xie, Li Huang, Liying Sheng, Qirong Shi, Yumin Ke

“…The performance of the predictive model was evaluated using a Nomo plot. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…To enhance model performance, we introduce a novel non-dominated sorting artificial bee colony (NSABC) algorithm, which fine-tunes the hyper-parameters of the CNN-RNN structure, including weights, biases, the number of layers, and neuron configurations. …”
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