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Deep Variational Auto-Encoder for Model-Based Water Quality Patrolling with Intelligent Surface Vehicles
This paper addresses persistent monitoring challenges in Lake Ypacaraí, Paraguay, a crucial hydrological resource facing issues of eutrophication and...
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Community-Based Topic Modeling with Contextual Outlier Handling
E-commerce has become an essential aspect of modern life, providing consumers globally with convenience and accessibility. However, the high volume...
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Exploring the Use of LLMs for Teaching AI and Robotics Concepts at a Master’s Degree
This article explores the use of Large Language Models (LLM) as transformative tools for teaching Artificial Intelligence (AI) and Robotics concepts...
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Taking Advantage of Depth Information for Semantic Segmentation in Field-Measured Vineyards
RGB-D cameras mounted on moving agricultural robotic platforms provide detailed information about both appearance and volume of plants. Those images...
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Driven PCTBagging: Seeking Greater Discriminating Capacity for the Same Level of Interpretability
The partial consolidated tree bagging (PCTBagging) was presented as a multiple classifier that, based on a parameter, the consolidation percentage,...
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Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains
This comprehensive review explores the rapidly advancing field of Spiking Neural Networks (SNNs), particularly emphasizing their computational...
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Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction
This paper contributes with an alternative to the multivariate Analogue Method (AM) version, using a preprocessing stage carried out by an...
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Reconstruction-Based Anomaly Detection in Wind Turbine Operation Time Series Using Generative Models
Unsupervised time series anomaly detection is a common tasks in many real world problems, in which the normal/anomaly labels are extremely...
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O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification
Time Series Ordinal Classification (TSOC) is a yet unexplored field with a substantial projection in following years given its applicability to...
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An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines
Quantum computing holds great promise for enhancing machine learning algorithms, particularly by integrating classical and quantum techniques. This...
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Explaining Problem Recommendations in an Intelligent Tutoring System
Students learning with intelligent tutoring systems (ITS) do not always trust system recommendations. One solution for this is explainable AI (XAI),...
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An AI-Learner Shared Control Model Design for Adaptive Practicing
Online higher education offers great learning flexibility but demands learners’ high self-regulated learning (SRL) skills, especially in self-paced...
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Generating Learning Sequences Using Contextual Bandit Algorithms
Personalized learning paths have become a promising instructional strategy in online learning, as they can cater to individual learners’ needs and...
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Detecting Function Inputs and Outputs for Learning-Problem Generation in Intelligent Tutoring Systems
Designing of the function interface is one of the key skills in programming. That requires feedback, which can be generated in the necessary quantity...
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Early Math Skill as a Predictor for Foundational Literacy
This study examined the validity of early math skills as predictors of literacy skills. Data was collected from students using a home-based...
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Analyzing the Role of Generative AI in Fostering Self-directed Learning Through Structured Prompt Engineering
This study explores the use of Generative AI, particularly large language models such as ChatGPT, in promoting self-directed learning among beginners...
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Social AI Agents Too Need to Explain Themselves
Social AI agents interact with members of a community, thereby changing the behavior of the community. For example, in online learning, an AI social...
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Improving LLM Classification of Logical Errors by Integrating Error Relationship into Prompts
LLMs trained in the understanding of programming syntax are now providing effective assistance to developers and are being used in programming...
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Analysis of Machine Learning Models for Academic Performance Prediction
The prevalent issue of increased student dropouts, shared by universities worldwide, often culminates in decreased academic performance and prolonged...
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LLM-Based Course Comprehension Evaluator
Large language models (LLMs) like GPT-4 reshape intelligent tutoring systems by enabling nuanced natural language interactions. Leveraging LLMs’...