Today's society must prioritize the design and development of platforms for Big Data
processing. Smart cities generate large volumes of valuable data which the government can …

In emerging applications of the Internet of Things (IoT), wireless sensor networks (WSNs)
are usually federally deployed for these purposes of data gathering, tracking and monitoring …

In indoor environments, such as smart homes, the number of occupants within the space
and their moving directions can provide a rich set of contextual information about the …

Large‐scale data training is vital to the generalization performance of deep learning (DL)
models. However, collecting data directly is associated with increased risk of privacy …

Concerning the needs of multi-service and network performance prediction in the Internet of
Things (IoT), we propose an asymmetric two-priority polling control system model, and use …

Anomaly detection plays a critical role in intelligent video surveillance. However, real‐world
video data obtained always contains large numbers of normal video data, along with large …

In industrial areas, most of databases are dynamic databases, and the volume of the
databases has grown with the passage of time. Especially, pattern mining for incremental …

Data mining is a method for extracting useful information that is necessary for a system from
a database. As the types of data processed by the system are diversified, the transformed …

On‐board training of artificial neural network (ANN) is important in instances where real time
data are required for model training. Provision of on‐board intelligence enables the …

As a parameter from the perspective of neighborhood structure in network, binding number
is applied to measure the vulnerability of the network. The network is represented by a …