Supply chain crime - taxonomy development and empirical validation

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Despite the widespread use of self-tracking technologies for promoting personal wellbeing, there is limited research on the monitoring of intimate data, particularly urine. To shed light on the design possibilities within this unexplored domain we designed ...

Self-tracking technologies open new doors to previously unimaginable scenarios. The diagnosis of diseases years in advance, or supporting the health of astronauts on missions to Mars are just some of many example applications. During the COVID-19 pandemic, ...

Social media studies often collect data retrospectively to analyze public opinion. Social media data may decay over time and such decay may prevent the collection of the complete dataset. As a result, the collected dataset may differ from the complete data ...

Raw data and Matlab scripts from the publication at https://doi.org/10.1021/jacs.3c01279 All codes are provided free of charge and come with no warranty. Future use (original or modified) is required to cite: Zenedo data deposit at DOI 10.5281/zenodo. ...

Despite the importance of using artifacts during the design thinking process, there is a limited understanding of the influence of tangibles with lower perceptual richness on design thinking skills within educational settings. It is speculated that tangibl ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

Object detection plays a critical role in various computer vision applications, encompassing domains like autonomous vehicles, object tracking, and scene understanding. These applica- tions rely on detectors that generate bounding boxes around known object ...

Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...

The social discourse surrounding the climate emergency progressively infuses the society, transforming into both micro- and macro-social injunctions to change. Yet, society - grounded in a territorial, social, and cultural contingency - appears to resist t ...

Artificial Intelligence often relies on information obtained from others through crowdsourcing, federated learning, or data markets. It is crucial to ensure that this data is accurate. Over the past 20 years, a variety of incentive mechanisms have been dev ...

Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given ...

Advances in soft sensors coupled with machine learning are enabling increasingly capable wearable systems. Since hand motion in particular can convey useful information for developing intuitive interfaces, glove-based systems can have a significant impact ...

Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...

In this work, a purely data-driven discharge prediction model was developed and tested without integrating any data or results from simulations. The model was developed based on the experimental data from the Experimental Advanced Superconducting Tokamak ( ...

In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...

Optimal performance of civil infrastructure is an important aspect of liveable cities. A judicious combination of physics-based models with monitoring data in a validated methodology that accounts for uncertainties is explored in this paper. This methodolo ...

We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...

Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a materi ...

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

We have recently released in the open domain data originating from a series of flights conducted with a fixed-wing micro UAV carrying high-quality small camera and navigation sensors. This data was previously used in several peer-reviewed publications. How ...

Supply chain crime - taxonomy development and empirical validation

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Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Designing self-tracking experiences: A qualitative study of the perceptions of barriers and facilitators to adopting digital health technology for automatic urine analysis at home

The Impact of Data Persistence Bias on Social Media Studies

Imaging radial distribution functions of complex particles by relayed dynamic nuclear polarization

What Role Do Tangibles Play in Fostering Design Thinking Skills? An Exploratory Study

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Improving Object Detection under Domain Shifts

Co-constructing an Effective, Sustainable and Scalable Primary School Computer Science Curricular Reform

Resistances to change in urban travel behaviors

Game-theoretic Mechanisms for Eliciting Accurate Information

New particle formation event detection with Mask R-CNN

A Wearable Smart Glove and Its Application of Pose and Gesture Detection to Sign Language Classification

Bridging the gap between model-driven and data-driven methods in the era of Big Data

EAST discharge prediction without integrating simulation results

Multitask adaptation with Lattice-Free MMI for multi-genre speech recognition of low resource languages

Validating model-based data interpretation methods for quantification of reserve capacity

Human mortality at extreme age

A data-driven perspective on the colours of metal-organic frameworks

A Pareto Dominance Principle for Data-Driven Optimization

Fixed-wing micro UAV open data with digicam and raw INS/GNSS