The non-intrusive detection of Autism Spectrum Disorder (ASD) marks a significant advancement in early diagnosis and intervention. This approach allows users to upload videos to a web interface, where visual and audit...
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Multicore processors spend a varying amount of time and energy when executing a user application. The specific amount of time and energy consumed depends on application parameters as well as on the execution mode, whi...
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This paper investigates rapid cooperative guidance with finite time convergence in the context of missile attacks. Cooperative guidance systems play a crucial role in coordinating multiple missiles toward a common tar...
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Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool...
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Augmented Reality (AR) has been gaining increased attention in science education, as research has demonstrated its ability to provide students with an engaging and interactive way to learn. Students are able to visual...
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ISBN:
(纸本)9783031804748;9783031804755
Augmented Reality (AR) has been gaining increased attention in science education, as research has demonstrated its ability to provide students with an engaging and interactive way to learn. Students are able to visualize and experience phenomena that would otherwise remain hidden, practice in simulated hazardous conditions, and develop their spatial skills. While the potential benefits of this technology are clear, more research is needed to understand how students actually interact with and experience AR. Due to its novelty, using AR is challenging for some users. This sometimes leads to a high cognitive load during the learning task, which can ultimately impact performance. To investigate how students interact with an AR application, the present study examined students' in-app performance, knowledge acquisition and perceived cognitive load through a Bayesian hypothesis testing approach. Moreover, process mining was used to qualitatively assess students' behaviour patterns. The contribution of this work is twofold: 1) the observed interactions during an AR intervention provide insights into the relationship between students' cognitive load, in-app performance and knowledge acquisition, and 2) the process analysis helps to derive general recommendations for practitioners who are designing or using a similar AR application in their practice.
Non-invasive brain-computer interface technology has become a research hotspot in the field of human-computer interaction with its characteristics of no surgery and safe reliability. This paper introduces the non-inva...
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In recent years, global climate change and human activities have intensified the frequency and severity of floods. Based on the big data of flood probability, combined with the index data of monsoon intensity, river m...
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This paper delves into the critical role that machine learning plays in the accurate classification of sentiments expressed in movie reviews. Throughout the study we research and apply NLP using deep learning and mach...
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Jackfruit is the national fruit of Bangladesh, and one of the most consumed fruits in India, Sri Lanka, Philippines, Indonesia, Malaysia, Australia, and many more countries. The every year due to diseases jackfruit pr...
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The difficulty of unbalanced datasets in classification issues has become more noticeable with the fast expansion of data science and machine learning approaches. When confronted with uneven data, conventional machine...
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