Building Successful Long Child-Robot Interactions in a Learning Context

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Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

Context: Introducing Computer Science (CS) into formal education can be challenging, notably when considering the numerous stakeholders involved which include the students, teachers, schools, and policy makers. We believe these perspectives should be con ...

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

Sustaining changes in teachers’ practices is a challenge that determines the success of curricular reforms, from which Digital Education (DE) is not exempt. As the literature on sustainability is considered “scarce” and “scattered”, long-term studies model ...

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

Objectives Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-supp ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

Engineering accreditation bodies express a strong consensus that in addition to technical and scientific skills, engineering education also needs to promote the development of professional skills. In general, team-based projects are considered to be valuab ...

Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

Conventional leg prostheses do not convey sensory information about motion or interaction with the ground to aboveknee amputees, thereby reducing confidence and walking speed in the users that is associated with high mental and physical fatigue(1-4). The l ...

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical m ...

Object detection, a fundamental task in computer vision, is crucial for various intelligent edge computing applications. However, object detection algorithms are usually heavy in computation, hindering their deployments on resource-constrained edge devices ...

MammAlps is a multimodal and multi-view dataset of wildlife behavior monitoring. Nine camera-traps were placed at three monitoring sites in the Swiss National Park, from which we curated over 14 hours of video with audio, 2D segmentation maps and 8.5 hours ...

As the demand for high channel counts and high-resolution recordings of neural activity continues to grow, the increased power and data rate generated impose hard constraints on the telemetry capabilities of wireless implantable neural interfaces. To addre ...

Automatic speech recognition (ASR) systems are well known to perform poorly on dysarthric speech. Previous works have addressed this by speaking rate modification to reduce the mismatch with typical speech. Unfortunately, these approaches rely on transcrib ...

Image steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile. To address this, this ...

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving differential equations by integrating physical laws into the learning process. This work leverages PINNs to simulate gravitational collapse, a critical phenomenon in astro ...

The Birman-Williams theorem gives a connection between the collection of unstable periodic orbits (UPOs) contained within a chaotic attractor and the topology of that attractor, for three-dimensional systems. In certain cases, the fractal dimension of a ch ...

Introduction: Brain-inspired computing has become an emerging field, where a growing number of works focus on developing algorithms that bring machine learning closer to human brains at the functional level. As one of the promising directions, Hyperdimensi ...

We consider a network of agents that must solve an online optimization problem from continual observation of streaming data. To this end, the agents implement a distributed cooperative strategy where each agent is allowed to perform local exchange of infor ...

Building Successful Long Child-Robot Interactions in a Learning Context

Chat with Graph Search

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

A Research-Practice Partnership to Introduce Computer Science in Secondary School: Lessons from a Pilot Program

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Modelling the sustainability of a primary school digital education curricular reform and professional development program

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Which professional skills do students learn in engineering team-based projects?

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Sensory feedback restoration in leg amputees improves walking speed, metabolic cost and phantom pain

Designing for impact: a conceptual framework for learning analytics as self-assessment tools

Edge-Cloud Collaborated Object Detection via Bandwidth Adaptive Difficult-Case Discriminator

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

Image steganalysis using active learning and hyperparameter optimization

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks

The topology of a chaotic attractor in the Kuramoto-Sivashinsky equation

Hyperdimensional computing with holographic and adaptive encoder

Distributed Adaptive Learning Under Communication Constraints