Prediction of students’engagement in aCollaborative Learning setting is essential to improve the quality of *** learning is a strategy of learning through groups or *** cooperative learning behavior occurs,each stude...
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Prediction of students’engagement in aCollaborative Learning setting is essential to improve the quality of *** learning is a strategy of learning through groups or *** cooperative learning behavior occurs,each student in the group should participate in teaching *** showed that students who are actively involved in a class gain *** behavior and facial expression are important nonverbal indicators to reveal engagement in collaborative learning *** studies require the wearing of sensor devices or eye tracker devices,which have cost barriers and technical interference for daily teaching *** this paper,student engagement is automatically analyzed based on computer *** tackle the problem of engagement in collaborative learning using a multi-modal deep neural network(MDNN).We combined facial expression and gaze direction as two individual components of MDNN to predict engagement levels in collaborative learning *** multi-modal solution was evaluated in a real collaborative *** results show that the model can accurately predict students’performance in the collaborative learning environment.
Nyctophobia is a phobia of the dark and is common among children but also found in adults. While the phobia itself is commonly known, the diversity of its treatment is still minimal. As technology has reached its high...
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Current technology utilizes a sophisticated standard room measurement system to analyze the average roughness of Stainless Steel Bearing Surface. However, this process relies on random sampling at infrequent intervals...
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Now object detection based on deep learning tries different *** uses fewer data training networks to achieve the effect of large dataset ***,the existing methods usually do not achieve the balance between network para...
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Now object detection based on deep learning tries different *** uses fewer data training networks to achieve the effect of large dataset ***,the existing methods usually do not achieve the balance between network parameters and training *** makes the information provided by a small amount of picture data insufficient to optimize model parameters,resulting in unsatisfactory detection *** improve the accuracy of few shot object detection,this paper proposes a network based on the transformer and high-resolution feature extraction(THR).High-resolution feature extractionmaintains the resolution representation of the *** and spatial attention are used to make the network focus on features that are more useful to the *** addition,the recently popular transformer is used to fuse the features of the existing *** compensates for the previous network failure by making full use of existing object *** on the Pascal VOC and MS-COCO datasets prove that the THR network has achieved better results than previous mainstream few shot object detection.
One of the key challenges in e-commerce is how to provide relevant and personalized product recommendations to users. To achieve this, data analysis and text processing techniques are essential. This research aims to ...
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The field of Multimodal Sentiment Analysis (MSA) has recently witnessed an emerging direction seeking to tackle the issue of data incompleteness. Recognizing that the language modality typically contains dense sentime...
Graph neural networks (GNNs) have shown outstanding performance in graph node classification. However, as a deep learning model, GNNs can be influence by adversarial attacks, such as graph injection attacks or graph m...
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1 IntroductionText categorization methods based on machine learning always encounter the curse of dimensionality. Therefore, it is crucial to perform feature selection to reduce dimensionality of text vectors. Methods...
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1 IntroductionText categorization methods based on machine learning always encounter the curse of dimensionality. Therefore, it is crucial to perform feature selection to reduce dimensionality of text vectors. Methods based on the difference between document rate of a term in the positive class and that in the negative class have been widely studied in recent years, which is originated from balanced accuracy measures (ACC2) [1].
Gastrointestinal diseases are significant health concerns that mostly affect the digestive and biliary tracts. These can only be observed internally through endoscopy, or a modern approach named Wireless Capsule Endos...
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Time series classification problems are prevalent across various domains, often characterized by intra-series relationships within features, and inter-series relationships between the same features over time. Developi...
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