A Fused Multiscale Pictorial Sequence Learning Mechanism Applied to Pavement Detection by Zhang Jiazhen, Wang Xiulai, Zhao Shuxu

“…The static statistical evaluation value is retained as one of the specific data to assist in identifying the sample, and the two angle data complement each other to maximize the feature information entropy. Using the SVM classifier with the global sequence alignment algorithm as the main kernel function, the data classification module detects anomalies, so that the algorithm can mine valuable feature attributes from multiple angles as much as possible while stably exerting its classification function. …”
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Research on Natural Language Misleading Content Detection Method Based on Attention Mechanism by Boning Liu

“…To address these challenges, we propose a novel dual-component system consisting of the Content-Driven Encoder (CoDE) and the Domain-Informed Detection Adapter (DiDA). CoDE employs a dynamic attention mechanism with hierarchical semantic encoding and domain-aware feature modulation, allowing adaptive representation learning across unimodal and multimodal inputs. …”
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Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data by Niklas D. Neumann, Jur J. Brauers, Nico W. van Yperen, Mees van der Linde, Koen A. P. M. Lemmink, Michel S. Brink, Fred Hasselman, Ruud J. R. den Hartigh

“…Abstract Background There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. …”
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Real-Time Lightweight Morphological Detection for Chinese Mitten Crab Origin Tracing by Xiaofei Ma, Nannan Shen, Yanhui He, Zhuo Fang, Hongyan Zhang, Yun Wang, Jinrong Duan

“…To address this challenge, this study proposes a two-stage origin traceability framework that integrates a lightweight object detector and a high-precision classifier. In the first stage, an improved YOLOv10n-based model is designed by incorporating omni-dimensional dynamic convolution, a SlimNeck structure, and a Lightweight Shared Convolutional Detection head, which effectively enhances the detection accuracy of crab targets under complex multi-scale environments while reducing computational cost. …”
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Time-Adaptive Machine Learning Models for Predicting the Severity of Heart Failure with Reduced Ejection Fraction by Trevor Winger, Cagri Ozdemir, Shanti L. Narasimhan, Jaideep Srivastava

“…This demonstrates the model’s ability to handle diverse patient presentations and the dynamic nature of disease progression. <b>Conclusions:</b> The findings show the potential of time-adaptive machine learning models, particularly the Passive-Aggressive classifier, in managing heart failure with reduced ejection fraction and other chronic diseases. …”
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Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT by Yonas Kibret Beshah, Surafel Lemma Abebe, Henock Mulugeta Melaku

“…To address this challenge, a novel Multistage Adversarial Attack Defense (MSAAD) framework has been developed to protect online DDoS attack detection systems from adversarial attacks. The framework consists three defense layers: 1) the Resilient Adversarial Detector and Purification (RADP), which detects and purifies adversarial attacks targeting online DDoS attack detection systems against multiple and unknown adversarial attacks. 2) a multiple classifier, that increase complexity for an attacker to replicate the DDoS attack detection model. 3) the Multi-Armed Bandit (MAB) with Thompson Sampling, which dynamically selects the optimal classifier or ensemble of classifiers for each incoming traffic request. …”
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Holistic Pose Estimation and Dynamic Motion Analysis for Telerehabilitation of Physically Disabled Individuals by Aleena Kamal, Shaheryar Najam, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Jeongmin Park

“…We propose a novel Lightweight Two-tier Key Body Point Detection (LT-KBPD) algorithm to efficiently and accurately identify key skeletal points, which are then used to extract both static and dynamic kinematic features. …”
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Algorithms, Techniques, and Applications of Intelligent Diagnosis Using Dynamic Ultrasound: A Review by Jialong Liu, Jianfeng Zhang, Yuan Shao, Xiaolong Xiao, Shoujun Huang, Dexing Kong

“…We classify the applications of dynamic ultrasound into six categories and provide detailed discussions on the use of machine learning, particularly deep learning, in intelligent diagnosis. …”
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Assessment of Land Cover and Land Use Change Dynamics in Kibwezi Watershed, Kenya by Reuben C. Ruttoh, John P. O. Obiero, Christian T. Omuto, Lucas Tanui

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Spatio-temporal dynamic functional brain network for mild cognitive impairment analysis by Shipeng Wen, Jingru Wang, Wenjie Liu, Xianglian Meng, Xianglian Meng, Zhuqing Jiao, Zhuqing Jiao

“…IntroductionAlzheimer’s Disease (AD) is a progressive neurodegenerative disorder, with Mild Cognitive Impairment (MCI) often serving as a prodromal stage. Early detection of MCI is critical for timely intervention.MethodsDynamic Functional Connectivity analysis reveals temporal dynamics obscured by static functional connectivity, making it valuable for analyzing and classifying psychiatric disorders. …”
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Assessment of land dynamics transformation into tea plantations using support vector machine by Md Sahadat Hossan, Masud Ibn Afjal, Md.Faruq Hasan, Md.Abu Hanif

“…Precisely monitoring land use dynamics and spatial distributions is essential for sustainable development and long-term land management. …”
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Evaluating aufeis detection methods using Landsat imagery: Comparative assessment and recommendations by Julian Dann, Simon Zwieback, Paul Leonard, W. Robert Bolton

“…Additionally, we evaluate the utility of additional bands and indices in aufeis detection using a grid-search for the top features (3FT) and feature importance metrics.The more complex RF classifier, which relies on an extensive training dataset, outperforms both feature thresholding methods across all validation datasets with an average F1 score of 0.967±0.029. …”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We developed four random forest algorithms to (1) detect asynchronous breathing, (2) classify types of breathing asynchrony, (3) assess the extent of signal disruption, and (4) identify dynamic hyperinflation. …”
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DIO-SLAM: A Dynamic RGB-D SLAM Method Combining Instance Segmentation and Optical Flow by Lang He, Shiyun Li, Junting Qiu, Chenhaomin Zhang

“…Following this, an optical flow consistency method is implemented to assess the dynamic nature of rigid object mask regions, classifying them as either moving or stationary rigid objects. …”
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Decoding Pain Dynamics: EEG Insights into Neural Responses and Classification via RQA Analysis by Mahsa Tavasoli, Zahra Einalou, Reza Akhondzadeh

“…Conclusion: The simulation results proved that cerebral behaviors are detectable during pain. Also, one of the most merits of the proposed method is the high accuracy of classifier for an investigation into dynamical features of the brain during happening pain. …”
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A comparison of several intrusion detection methods using the NSL-KDD dataset by hazem salim abdullah

“…This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. …”
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Dynamic Voting-Based Ensemble Deep Learning for Closely Resembling Crop Classification by Engin Eşme, Muhammed Arif Şen, Halil Çimen

“…This study focuses on classifying agricultural crop images, which often bear close resemblance, employing 17 distinct deep learning models and dynamic voting. …”
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The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study by Jae-Hyun Lee, Ye-Seul Jang, Won-Du Chang

“…Conclusion These findings highlight the feasibility of measuring and classifying cartilage-generated potentials during dynamic physical activities, providing valuable insights into load-related differences. …”
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Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering by Chao Chun Liu, William W. L. Hsiao

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Harnessing Deep Learning for Lung Cancer Detection and Prevention: A Comprehensive Survey by Tidke Dipika, Banait Satish S.

“…This survey investigates how deep learning is changing the landscape of lung cancer detection and prevention, with attention to recent breakthroughs in medical imaging analysis. …”
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