Generative Adversarial Networks (GANs) have shown remarkable success in producing
realistic-looking images in the computer vision area. Recently, GAN-based techniques are …

Change Point Detection (CPD) methods identify the times associated with changes in the
trends and properties of time series data in order to describe the underlying behaviour of the …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Due to the increasing popularity of recent advanced features and context-awareness in
smart mobile phones, the contextual data relevant to users' diverse activities with their …

Extracting informative and meaningful temporal segments from high-dimensional wearable
sensor data, smart devices, or IoT data is a vital preprocessing step in applications such as …

Call and messaging logs from mobile devices have successfully been used to predict
personality traits. Yet accelerometer data have not been applied for this purpose. Here we …

Mobility data captures the locations of moving objects such as humans, animals, and cars.
With the availability of GPS-equipped mobile devices and other inexpensive location …

Knowing" what is happening" and" what will happen" of the mobility in a city is the building
block of a data-driven smart city system. In recent years, mobility digital twin that makes a …

Mobile networks are expected to face major problems such as low network capacity, high
latency, and limited resources but are expected to provide seamless connectivity in the …

The novel IoT-based data sensing and service mode promotes the booming development of
crowdsensing-based mobile communication services (MCSs). MCS facilitates people's daily …