Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks by Yingjie Wang, Yingjie Fan, Meixuan Li

“…On this basis, an important lemma is derived, which contributes to performing a stability analysis. Then, the corresponding closed-loop system model is established in the presence of a trigger scheme. …”
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P12 | VISUALIZING NUCLEAR ARCHITECTURE DURING MAMMAL ERYTHROPOIESIS

“…Mammalian erythropoiesis is characterized by profound chromatin reorganization prior to nuclear extrusion2, representing a suitable model to investigate nuclear architecture and its impact on gene expression regulation. …”
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Soft Schemes for Earthquake-Geotechnical Dilemmas by Silvia García

“…Considering the strengths and weaknesses of the algorithms, in this work a criterion to leverage the best features to develop efficient hybrid models is presented. …”
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Basic concepts and definitions of the PAS design and decision system by Monique Arkesteijn

“…The two main problems were that (1) it remained unclear how alternative CRE strategies are made on portfolio and building level and (2) most problems occur when selecting an alternative; none of the models has an overall performance measure that incorporates both quantitative and qualitative criteria, and uses correct measurement. …”
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Linear pattern detection of building groups by integrating dynamic snake convolution with YOLO11 by Xiao Wang, Yue Wu, Longfei Cui, Haizhong Qian, Bohao Li, Xu Wang

“…Experimental results show that the improved YOLO11-DSC model has better performance compared to the original YOLO11 and another two commonly used strategies (improving with CBAM, AKConv). …”
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Reliable estimation via hybrid gradient boosting machine for mud loss volume in drilling operations by Xiaozhi Lu, Farag M. A. Altalbawy, Tarak Vora, R. Manjunatha, Debasish Shit, Shirin Shomurotova, Akshay Kumar, Atreyi Pramanik, Ajay Sharma, Raed H. C. Alfilh, Samim Sherzod, Mohammad Mahtab Alam

“…A Gradient Boosting Machine (GBM) served as the core predictor, with its hyperparameters fine-tuned using four optimization strategies: Evolution Strategies (ES), Batch Bayesian Optimization (BBO), Bayesian Probability Improvement (BBI), and Gaussian Process Optimization (GPO). Model performance was evaluated using k-fold cross-validation, with metrics including R², mean squared error and average absolute relative error percentage. …”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…A Dense-ReLU-Dropout model was trained with K-fold cross-validation (K = 3), and performance metrics like accuracy, precision, recall, and F1-score were used to evaluate the model. …”
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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

“…Furthermore, the model reduces parameter count by 6.9% and computational load by 13.1%, demonstrating its improved efficiency. …”
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YOLOv8n-DSDL: A lightweight dual-backbone network with decoupled self-attention for cotton maturity detection by Meiqi Zhong, Linjing Wei, Henghui Mo

“…The model integrates the original YOLOv8n with a lightweight StarNet to form a dual-backbone structure, enabling efficient multi-channel feature fusion and enhancing fine-grained maturity feature extraction. …”
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MSO‐DETR: Metric space optimization for few‐shot object detection by Haifeng Sima, Manyang Wang, Lanlan Liu, Yudong Zhang, Junding Sun

“…Abstract In the metric‐based meta‐learning detection model, the distribution of training samples in the metric space has great influence on the detection performance, and this influence is usually ignored by traditional meta‐detectors. …”
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The Application of Imperialist Competitive Algorithm in Determining the Optimal Parameters of Empirical Area Reduction Method to Predict the Sedimentation Process in Dez Dam by Arash Azari, Sadegh Soori Hossein Bonakdari, Hossein Bonakdari

“…Then, by introducing new reservoir hydrography data in the optimal model, the sedimentation trend was predicted in the feature years (1410 and 1420). …”
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Decoupling mean teacher via Dual students: a prototype-based framework for semi-supervised medical segmentation by Yang Zuo, Renfeng Zhang, Xiurui Guo, Chunmeng Kang, Lei Lyu

“…Among the existing SSL methods, the mean teacher framework is one of the most popular approaches due to its simple architecture and outstanding performance. However, this framework has two critical challenges: (1) parameter coupling between the teacher and student models, and (2) unreliable pseudo label generation. …”
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AI-Powered Mobile App for Nuclear Cataract Detection by Alicja Anna Ignatowicz, Tomasz Marciniak, Elżbieta Marciniak

“…All models demonstrated comparable performance, with classification accuracies exceeding 91–94.5%. …”
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Property-driven localization and characterization in deep molecular representations by Celia Cintas, Payel Das, Jerret Ross, Brian Belgodere, Girmaw Abebe Tadesse, Vijil Chenthamarakshan, Jannis Born, Skyler Speakman

“…When we use the discovered property-driven elements as features for a new task, we find the same or improved performance (3 points up) while reducing the dimensions by 75% without fine-tuning required, thus indicating information localization.…”
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Using Explainable Machine Learning Methods to Predict the Survivability Rate of Pediatric Respiratory Diseases by Roshan Kumar, V Srirama, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, Srikanth Prabhu, Rajagopala Chadaga

“…Shapley Additive Values (SHAP), Explain Like I’m 5 (ELI5), QLattice, and Local Interpretable Model-agnostic Explanations (LIME) are four Explainable Artificial Intelligence (XAI) techniques used to interpret model predictions. …”
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Research on Defect Detection in Lightweight Photovoltaic Cells Using YOLOv8-FSD by Chao Chen, Zhuo Chen, Hao Li, Yawen Wang, Guangzhou Lei, Lingling Wu

“…Given the high computational complexity and poor real-time performance of current photovoltaic cell surface defect detection methods, this study proposes a lightweight model, YOLOv8-FSD, based on YOLOv8. …”
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Zero-shot intelligent fault diagnosis via semantic fusion embedding by Honghua Xu, Zijian Hu, Ziqiang Xu, Qilong Qian

“…However, they can hardly adapt to the practical conditions since the man-made data can hardly model the fault patterns across domains. Aiming to solve this problem, this paper proposes a novel deep fault semantic fusion embedding model (DFSFEM) to realize zero-shot intelligent fault diagnosis. …”
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STTMC: A Few-Shot Spatial Temporal Transductive Modulation Classifier by Yunhao Shi, Hua Xu, Zisen Qi, Yue Zhang, Dan Wang, Lei Jiang

“…In this paper, we present a novel few-shot AMC model named the Spatial Temporal Transductive Modulation Classifier (STTMC), which comprises two modules: a feature extraction module and a graph network module. …”
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Evaluation of large‐scale cycling environment by using the trajectory data of dockless shared bicycles: A data‐driven approach by Ying Ni, Shihan Wang, Jiaqi Chen, Bufan Feng, Rongjie Yu, Yilin Cai

“…First, critical cycling behaviour features that reflect cyclists’ perceptions are identified applying the fuzzy C‐means and random forest model. …”
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Efficient ID-based multicast authentication protocol in wireless sensor networks by WANG Gang1, WEN Tao1, GUO Quan2, MA Xue-bin1

“…In order to overcome the drawback of the existent multicast authentication protocol in WSN,the PKC-based services for WSN was explored and an efficient ID-based multicast authentication protocol was presented.The protocol with message recovery provided the feature that the message was recoverable from the signature and hence the computa-tional cost and communication overhead of the protocol had been reduced greatly.This protocol was proved secure against existential forgery under adaptive chosen message and ID attack in the random oracle model.The performance analysis results show that the proposed scheme can effectively reduce resource cost,adapt the characteristics of WSN and is clearly superior to the HESS,Zhang and BLS protocols.…”
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