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Advanced Mortality Prediction in Adult ICU: Introducing a Deep Learning Approach in Healthcare
Accurate mortality prediction in Intensive Care Units (ICUs) is crucial for optimizing patient care and resource allocation. Traditional prediction...
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Mindset Matters: The Role of Mathematics Self-concept and Age in Mental Rotation Performance Among Primary School Children
This cross-sectional study investigates the role of maths self-concept in spatial skills development among primary school children. The study,...
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Cognitive Perspectives on Perceived Spatial Ability in STEM
Spatial ability, crucial for success in science, technology, engineering, and mathematics (STEM) fields, displays intriguing gender differences,...
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Divided Attention in Human-Robot Teaming: Assessing Performance in Large-Scale Interactive Virtual Environments
This paper explores division of attention for people in human-robot teaming within immersive virtual environments (IVEs), focusing on search tasks...
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Eliciting Spatial Reasoning Actions Through Projective Geometry in the Elementary Classroom
Spatial thinking is an essential and uniting form of reasoning across science, technology, engineering, and mathematics (STEM). This paper explores...
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Gender in Teacher-Student Interactions: Another Factor in Spatial Ability Development and STEM Affiliation
This study explores gender dynamics in teacher-student interactions during a route planning task in science classes, examining six classes—three in...
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Strategizing the Shallows: Leveraging Multi-Agent Reinforcement Learning for Enhanced Tactical Decision-Making in Littoral Naval Warfare
Naval engagements, though rare, present complex challenges for data-driven machine learning due to their intricate dynamics and the scarcity of...
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Local Community-Based Anomaly Detection in Graph Streams
The problem of anomaly detection on static networks has been broadly studied in various research domains. Anomaly detection concerns the...
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A Prediction Analysis for the Case of a Korean Police Dataset
In the evolving landscape of law enforcement, predictive policing, which leverages data analysis and machine learning to anticipate crimes and...
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Improved \(NO_2\) Prediction Using Machine Learning Algorithms
Improved air pollution management approaches are required to ensure better air quality and tackle climate change. The ability to accurately forecast...
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Hybrid Explanatory Interactive Machine Learning for Medical Diagnosis
Machine learning (ML) models can be an effective assistance in medical diagnosis if they allow physicians to project their knowledge into model’s...
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Benign Paroxysmal Positional Vertigo Disorders Classification Using Eye Tracking Data
Nystagmus is a neurological condition characterized by involuntary and rhythmic eye movements. These abnormal eye movements can be indicative of...
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Towards Semantically Conscious, Conversation-Based Chatbot Services for Migrants
Many EU countries continue to face significant societal challenges related to the acceptance and integration of Third Country Nationals (TCNs). On...
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Lightweight Inference by Neural Network Pruning: Accuracy, Time and Comparison
This paper addresses the application of neural networks in resource constrained edge-devices. The goal is to achieve a speedup both in inference and...
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A Constraint-Based Greedy-Local-Global Search for the Warehouse Location Problem
Constraint optimization problems offer a means to obtain a global solution for a given problem. At the same time the promise of finding a global...
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C-XGBoost: A Tree Boosting Model for Causal Effect Estimation
Causal effect estimation aims at estimating the Average Treatment Effect as well as the Conditional Average Treatment Effect of a treatment to an...
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The Impact of Augmentation Techniques on Icon Detection Using Machine Learning Techniques
This article examines the use of image augmentation techniques to improve icon detection in mobile interfaces, a critical task due to the small size...
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Carbon-Aware Machine Learning: A Case Study on Cellular Traffic Forecasting with Spiking Neural Networks
Cellular traffic forecasting is an essential task that enables network operators to perform resource allocation and anomaly mitigation in fast-paced...
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A Machine Learning Approach for Points of Interest Extraction and Event Classification
This paper presents a novel approach that utilizes machine learning techniques, specifically clustering algorithms and artificial neural networks, to...
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Optimizations for Learning from Linear Feedback Shift Register Variations with Artificial Neural Networks
Recent years have seen an increase in Machine Learning techniques being applied to learn from Pseudorandom Number Generators (PRNGs). Currently, the...