Memory Flow-Controlled Knowledge Tracing with Three Stages

Information Science, Artificial Intelligence,
Knowledge Tracing   Time Series Prediction   Educational Data Mining   Memory Processing   Cognitive Process  

Academic Background With the rapid development of artificial intelligence (AI) technology, intelligent tutoring systems (ITS) such as Khan Academy and Coursera have made significant progress in personalized learning. Knowledge Tracing (KT), as a key technology in ITS, aims to infer students’ knowledge mastery and predict their future learning perfo...

Continual Learning of Conjugated Visual Representations through Higher-Order Motion Flows

Information Science, Computer Science, Artificial Intelligence,
continual learning   motion flows   self-supervised learning   feature extraction   higher-order motion   visual representations   online learning  

Continual Learning of Conjugated Visual Representations through Higher-Order Motion Flows: A Study on the CMOSFET Model Academic Background In the fields of artificial intelligence and computer vision, continual learning from continuous visual data streams has long been a challenge. Traditional machine learning methods typically rely on the assumpt...

Exploiting Instance-Label Dynamics through Reciprocal Anchored Contrastive Learning for Few-Shot Relation Extraction

Information Science, Computer Science, Artificial Intelligence,
Few-shot relation extraction   Contrastive learning   Pre-train   Fine-tune   Information extraction  

Exploiting Instance-Label Dynamics through Reciprocal Anchored Contrastive Learning for Few-Shot Relation Extraction Academic Background In the field of Natural Language Processing (NLP), Relation Extraction (RE) is a fundamental task aimed at identifying and extracting relationships between entities in text. However, traditional supervised learnin...

Rise-Editing: Rotation-Invariant Neural Point Fields with Interactive Segmentation for Fine-Grained and Efficient Editing

Rise-Editing: Rotation-Invariant Neural Point Fields with Interactive Segmentation for Fine-Grained and Efficient Editing

Information Science, Computer Science, Artificial Intelligence,
Neural Radiance Fields   3D Scene Editing   Point-Based Representation   Interactive Editing   Rotation-Invariance  

Research on Efficient Fine-Grained 3D Scene Editing Based on Rotation-Invariant Neural Point Fields Academic Background In the fields of computer vision and graphics, modeling and rendering novel views of real scenes from multi-view images is a central problem. Neural Radiance Fields (NeRF) have recently demonstrated significant potential in genera...

Anxiety Disorder Identification with Biomarker Detection through Subspace-Enhanced Hypergraph Neural Network

Anxiety Disorder Identification with Biomarker Detection through Subspace-Enhanced Hypergraph Neural Network

Information Science, Artificial Intelligence, Medicine, Psychiatry, Medical Imaging, Life Sciences, Bioengineering,
anxiety disorder   hypergraph neural network   multimodal data   subspace enhancement   biomarker  

Anxiety Disorder Identification and Biomarker Detection Based on Subspace-Enhanced Hypergraph Neural Network Academic Background Anxiety Disorders (ADs) are prevalent mental health issues globally, affecting approximately 7.3% of the population. Patients with anxiety disorders typically exhibit excessive fear, worry, and related behavioral abnormal...

Theoretical Insights into 1:2 and 1:3 Internal Resonance for Frequency Stabilization in Nonlinear Micromechanical Resonators

Physics, Mechanics, Engineering, Mechanical Engineering,
internal resonance   micromechanical resonator   MEMS resonator   frequency stabilization   amplitude-frequency effect   Duffing hardening nonlinearity  

Research on Internal Resonance Mechanisms in Micromechanical Resonators and Their Application in Frequency Stabilization Background Introduction Micromechanical resonators play a crucial role in modern timekeeping and sensing devices due to their high frequency, high quality factor, and high sensitivity. However, the extremely low damping character...

Secure Finite-Time Filtering for Switched Fuzzy Systems with Scaling Attacks and Stochastic Sensor Faults

Engineering, Electrical Engineering, Information Science, Automation,
Switched systems   Mixed H∞ and passivity filter   Takagi-Sugeno fuzzy model   Finite-time analysis   Average dwell-time   Scaling attacks  

Research on Secure Finite-Time Filter Design for Switched Fuzzy Systems Academic Background In modern control systems, switched systems and fuzzy systems have garnered significant attention due to their effectiveness in handling complex nonlinear dynamics. However, with the proliferation of networked systems, these systems face threats from sensor ...

Stochastic Response Spectrum Determination of Nonlinear Systems Endowed with Fractional Derivative Elements

Physics, Mechanics, Engineering, Mechanical Engineering, Architecture and Civil Engineering,
nonlinear vibrations   fractional derivatives   statistical linearization   stochastic averaging   stationary responses   conditional power spectrum  

Stochastic Response Spectrum Study of Nonlinear Systems: Introduction and Analysis Methods of Fractional Derivative Elements Academic Background In the fields of engineering and physics, nonlinear dynamic systems are widely used to model complex phenomena. However, predicting the response of these systems under stochastic excitation becomes highly ...

Research on the Lowest Cost to Calculate the Lyapunov Exponents from Fractional Differential Equations

Mathematics,
fractional differential equations   Lyapunov exponents   Adomian decomposition method   chaotic systems   computational efficiency  

Background Introduction Fractional Differential Equations (FDEs) extend traditional calculus by allowing derivatives and integrals of non-integer orders. This mathematical framework exhibits unique advantages in describing complex dynamical behaviors, particularly in the study of chaotic and nonlinear systems. Lyapunov Exponents (LEs) are critical ...

Nonlinear Displacement Control and Force Estimation in a Piezoelectric Robotic Manipulator

Physics, Mechanics, Engineering, Mechanical Engineering, Electrical Engineering, Information Science, Automation,
piezoelectric manipulator   nonlinear control   force estimation   viscoelastic deformation   robotic systems  

Academic Background In the fields of engineering and materials science, precise control of robotic manipulator displacement and force is crucial for studying the mechanical properties of materials, especially when dealing with objects exhibiting nonlinear viscoelastic deformation. For instance, in textiles, aerospace, medical, and energy production...