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Distinct Behavioural and Brain Response Profiles Between Arithmetic Word Problem Solving and Sentence Comprehension in Third and Fourth Graders.
Eur J Neurosci
January 2025
Department of Psychology, National Chengchi University, Taipei, Taiwan.
Word problems are essential for math learning and education, bridging numerical knowledge with real-world applications. Despite their importance, the neural mechanisms underlying word problem solving, especially in children, remain poorly understood. Here, we examine children's cognitive and brain response profiles for arithmetic word problems (AWPs), which involve one-step mathematical operations, and compare them with nonarithmetic word problems (NWPs), structured as parallel narratives without numerical operations.
View Article and Find Full Text PDFLittleFaceNet: A Small-Sized Face Recognition Method Based on RetinaFace and AdaFace.
J Imaging
January 2025
School of Artificial Intelligence, Changchun University of Science and Technology, Changchun 130012, China.
For surveillance video management in university laboratories, issues such as occlusion and low-resolution face capture often arise. Traditional face recognition algorithms are typically static and rely heavily on clear images, resulting in inaccurate recognition for low-resolution, small-sized faces. To address the challenges of occlusion and low-resolution person identification, this paper proposes a new face recognition framework by reconstructing Retinaface-Resnet and combining it with Quality-Adaptive Margin (adaface).
View Article and Find Full Text PDFMulti-Strategy Improved Red-Tailed Hawk Algorithm for Real-Environment Unmanned Aerial Vehicle Path Planning.
Biomimetics (Basel)
January 2025
Laboratory for Robot Mobility Localization and Scene Deep Learning Technology, Guizhou Equipment Manufacturing Polytechnic, Guiyang 550025, China.
In recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring. However, planning reliable, safe, and economical paths for UAVs in real-world environments remains a significant challenge. In this paper, we propose a multi-strategy improved red-tailed hawk (IRTH) algorithm for UAV path planning in real environments.
View Article and Find Full Text PDFAn Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning.
Biomimetics (Basel)
January 2025
Technology Research and Development Centre, Xuelong Group Co., Ltd., Ningbo 315899, China.
To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). First, a mathematical model is used to construct a three-dimensional terrain environment, and a multi-constraint path cost model is established, framing path planning as a multidimensional function optimization problem. Second, recognizing the sensitivity of population diversity to Logistic Chaotic Mapping in a traditional Human Evolution Optimization Algorithm (HEOA), an opposition-based learning strategy is employed to uniformly initialize the population distribution, thereby enhancing the algorithm's global optimization capability.
View Article and Find Full Text PDFNovel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction.
Entropy (Basel)
January 2025
School of Computer Science, Minnan Normal University, Zhangzhou 363000, China.
With the development of intelligent technology, data in practical applications show exponential growth in quantity and scale. Extracting the most distinguished attributes from complex datasets becomes a crucial problem. The existing attribute reduction approaches focus on the correlation between attributes and labels without considering the redundancy.
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