Game Programming by Demonstration

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Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recomme ...

In the clinic, it is difficult to distinguish the malignancy and aggressiveness of solid pulmonary nodules (PNs). Incorrect assessments may lead to delayed diagnosis and an increased risk of complications. We developed and validated a deep learning-based m ...

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

The potential of automatic code generation through Model-Driven Engineering (MDE) frameworks has yet to be realized. Beyond their ability to help software professionals write more accurate, reusable code, MDE frameworks could make programming accessible fo ...

The analysis of nuclear reactors for performance and safety assessment benefits from the use of computational tools. In this context, this work aims at the development and application of a thermal-hydraulics methodology and related software that respond to ...

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anaesthesi ...

The last few years have experienced the emergence of Industry 4.0 (I4.0), ultra-customization, and the explosion of demand for ethical, fair trade, and sustainable consumption. Organizations have therefore started a digital transformation of their SCs and ...

Technology supporting meditation is a multimillion-dollar market that continues to grow. There is also strong academic interest to understand and improve the impact technology can have for the user experience of practitioners. However, little work investig ...

The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, traditional ...

The implementation of non-user-centered design is sometimes effective for traditionally mass-produced items; however, these methods do not take into account local needs, resources, and cultures, and the history of individual people and communities in low- ...

Convolutional neural networks perform a local and translationally-invariant treatment of the data: quantifying which of these two aspects is central to their success remains a challenge. We study this problem within a teacher-student framework for kernel r ...

Humans often rely on their perspective taking skills to thrive within the world's complex relations and connections. An adequate understanding of others' spatial perspectives can increase the quality of the interaction, not only perceptually but also cogni ...

Cellulose nanocrystal (CNC) suspensions can self-assemble into chiral nematic films upon the slow evaporation of water. These films are brittle, as indicated by their fracturing instead of plastically deforming once they are fully elastically deformed. Thi ...

Discomfort glare metrics typically consider at least one of the two effects of discomfort glare-saturation and contrast-in their equation. The former occurs when there is an excessively bright glare source in the field of view, while the latter occurs when ...

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantitie ...

The RAPTOR suite of codes combines real-time model-based predictions of the plasma state with the available diagnostic measurements. Following the work on TCV and ASDEX-Upgrade, this paper presents the implementation of the RAPTOR suite for JET. This suite ...

Using Bayes's theorem, we derive a unit-wise recurrence as well as a backward recursion similar to the forward-backward algorithm. The resulting Bayesian recurrent units can be integrated as recurrent neural networks within deep learning frameworks, while ...

Familiarity is an elusive concept, capturing what we know intimately and what we only recognize from having seen before. This article aims to disambiguate these interpretations by proposing a sociological conceptualization of familiarity as a dynamic relat ...

This perspective paper explores the rising impacts of the COVID-19 and the Russia-Ukraine war from different perspectives, with an emphasis on the role of climate financing in achieving equitable and just transition mechanisms and that of peace in expediti ...

Game Programming by Demonstration

Chattez avec Graph Search

Multi-Step Critiquing User Interface for Recommender Systems

Deep learning predicts malignancy and metastasis of solid pulmonary nodules from CT scans

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Chat2Code: A Chatbot for Model Specification and Code Generation, The Case of Smart Contracts

A Coarse-mesh Methodology for the Analysis of One and Two-phase Nuclear Reactor Thermal-hydraulics in a Multi-physics Context

Sensitivity to user mischaracterizations in electric vehicle charging

Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

Industry 4.0 Technologies and Customer-centricity for Digital Supply Chains

Adapting Haptic Feedback for Guided Meditation

Democratizing Machine Learning

Design Approaches for Creating Person-Centered, Context Sensitive, and Sustainable Assistive Technology with the Global South

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios*

Exploring Spatial Perspective Taking in Human-Robot Interaction

Design of experiments to investigate multi-additive cellulose nanocrystal films

User Evaluations of Contrast-Dominant Discomfort Glare Dim Daylit Scenarios: Preliminary Findings

Manifold Learning-Based Polynomial Chaos Expansions For High-Dimensional Surrogate Models

Development of the RAPTOR suite of codes towards real-time reconstruction of JET discharges

Bayesian Recurrent Units and the Forward-Backward Algorithm

Familiarity as a Practical Sense of Place

The Rising Impacts of the COVID-19 Pandemic and the Russia-Ukraine War: Energy Transition, Climate Justice, Global Inequality, and Supply Chain Disruption