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Core to many scientific and analytics applications are spatial data capturing the position or shape of objects in space, and time series recording the values of a process over time. Effective analysis of such data requires a shift from confirmatory pipelin ...
Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...
In the Internet of Things (IoT), the large volume of data generated by sensors poses significant computational challenges in resource-constrained environments. Most existing machine learning algorithms are unable to train a proper model using a significant ...
Whether it is for personal use or for medical application, wearable sensors are becoming more and more widespread. This is the industry answer to two parallel trends. First, the public show a wish to collect data about their own lifestyle. This rather new ...
In this paper, we propose FedGP, a framework for privacy-preserving data release in the federated learning setting. We use generative adversarial networks, generator components of which are trained by FedAvg algorithm, to draw privacy-preserving artificial ...
State-owned enterprises (SOEs) provide important services such as power supply, postal services and public transportation. In doing this, SOEs operate at the intersection of political/regulatory and economic expectations. Therefore, SOEs are commonly consi ...
Purpose of review The goal of our nation-wide initiative is to provide clinicians intuitive and robust tools for accurate diagnosis, therapy monitoring and prognosis of cognitive decline that is based on large-scale multidomain data. Recent findings We des ...
The very shallow geothermal potential (vSGP) is increasingly recognized as a viable resource for providing clean thermal energy in urban and rural areas. This is primarily due to its reliability, low-cost installation, easy maintenance, and little constrai ...
This article studies the Cauchy problem for systems of semi-linear wave equations on R3+1 with nonlinear terms satisfying the null conditions. We construct future global-in-time classical solutions with arbitrarily large initial energy. The choice of the l ...
In the context of next-generation radio interferometers, we are facing a big challenge of how to economically process data. The classical dimensionality reduction technique, averaging visibilities on time, may dilute fast radio transients (FRT). We propose ...