From big smartphone data to worldwide research: The Mobile Data Challenge

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A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Digital technology has become an integral part of our lives, offering various benefits from communication and entertainment to education and productivity. However, its pervasive use has also raised concerns about its potential negative impact on users' wel ...

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

The ongoing war in Ukraine has profoundly impacted the Ukrainian scientific community. Numerous researchers have either emigrated or transitioned to alternate professions. For those who remain in research, the destruction of civil infrastructure and psycho ...

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

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 ...

Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper proposes a framework that infers e ...

This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried ou ...

In today's world, there is no shortage of disruptors acting on various professional domains. The Fourth Industrial Revolution, with its AI-driven and automation-focused technologies, has fundamentally changed many domains -- particularly the Information an ...

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 ...

As the volume of produced data is exponentially increasing, companies tend to rely on distributed systems to meet the surging demand for storage capacity. With the business workflows becoming more and more complex, such systems often consist of or are acce ...

Educational recommender systems channel most of the research efforts on the effectiveness of the recommended items. While teachers have a central role in online platforms, the impact of recommender systems for teachers in terms of the exposure such systems ...

There is an increasing interest in a fast-growing machine learning technique called Federated Learning (FL), in which the model training is distributed over mobile user equipment (UEs), exploiting UEs' local computation and training data. Despite its advan ...

Despite human geographers’ growing recognition of the need to explore how digital technologies are increasingly co‐producing geographies, the methodological implications of such forms of data production are rarely discussed. This paper explores how smartph ...

Background: Physical activity and sleep are behavioral risk factors for cancer that may be influenced by environmental exposures, including built and natural environments. However, many studies in this area are limited by residence-based exposure assessmen ...

Power-Force-Velocity profile obtained during a sprint test is crucial for designing personalized training and evaluating injury risks. Estimation of instantaneous velocity is requisite for developing these profiles and the predominant method for this estim ...

Background: Many recent studies have reported that autofluorescence bronchoscopy (AFB) has a superior sensitivity and decreased specificity in the diagnosis of bronchial cancers when compared with white-light bronchoscopy (WLB). We specifically analyzed th ...

The privacy of individuals does not only depend on their own actions and data but may also be affected by the privacy decisions and by the data shared by others individuals. This interdependence is an essential aspect of privacy and ignoring it can lead to ...

From big smartphone data to worldwide research: The Mobile Data Challenge

Chat with Graph Search

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Understanding and Enhancing Digital Wellbeing Dimensions: Empirical Studies on Smartphone Usage Patterns and Recommendations of Micro-Informative Content

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

The effects of war on Ukrainian research

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Embedding Mobile Health Technology into the Nurses' Health Study 3 to Study Behavioral Risk Factors for Cancer

A Sensor Fusion Approach to the Estimation of Instantaneous Velocity Using Single Wearable Sensor During Sprint

Comparison of autofluorescence and white-light bronchoscopies performed with the Evis Lucera Spectrum for the detection of bronchial cancers: a meta-analysis

A Survey on Interdependent Privacy