The Journal of Supercomputing

With the rapid development of Internet technology, network attacks occur frequently and numerous hidden dangers appear in network security. Therefore, improving the performance of intrusion detection systems to detect and defend against attacks is ...

As more and more applications with high computing requirements appear on mobile devices, considering the limited computing resources and energy of those devices, many devices offload this type of task to the surrounding cloud or fog. By offloading ...

This study proposes a pleasure–arousal–outlier (PAO) model to quantify the experiences derived from games. The proposed technique identifies pleasure, arousal, and outlier levels based on the facial expression of a user, keyboard input information,...

The occurrence of destructive earthquakes is a small probability event, that is, the seismic samples are extremely imbalanced, which increases the difficulty of earthquake prediction. The existing earthquake prediction methods rarely adopt sample ...

This work aims to promote smart city construction and smart city management. Firstly, this work analyzes the relevant theories and processing methods of short-term traffic flow prediction. Secondly, the random forest regression (RFR) theory in ...

Land consolidation is an essential tool for public administrations to reduce the fragmentation of land ownership. In particular, parcel exchange shows promising potential for restructuring parcel holdings, even more when the number of parcels and ...

This paper mainly studies the retrieval and location of violence in long time sequence video. Aiming at the low accuracy of violence detection in long time sequence video, a two-stage violence time sequence location method based on DC3D network ...

As unsupervised learning algorithm, clustering algorithm is widely used in data processing field. Density-based spatial clustering of applications with noise algorithm (DBSCAN), as a common unsupervised learning algorithm, can achieve clusters via ...

The technological advancements in the semiconductor industry have significantly improved over the years. However, Complementary Metal Oxide Semiconductor (CMOS) technology has its fabrication limitations. This requires new methods and materials ...

Dependency graph discovery is a substantial step in heuristic mining algorithms which are among the most prevalent process discovery methods in the healthcare domain due to their ability to deal with noisy event logs derived from unstructured and ...

Real-world nonstationary data are usually characterized by high nonlinearity and complex patterns due to the effects of different exogenous factors that make prediction a very challenging task. An ensemble strategically combines multiple ...

Prior literature suggests that shared identity and social attraction between team members and their robots can be vital for the human–robot interaction. However, more attention is needed to understand the potential performance benefits associated ...

We developed the core components of the AI-aided multiple time stepping algorithm for multiscale modeling of cell dynamics. This algorithm was implemented and analyzed on two supercomputer architectures with an application of simulating the ...$\mathrm{}$

One of the major problems in microarray datasets is the large number of features, which causes the issue of “the curse of dimensionality” when machine learning is applied to these datasets. Feature selection refers to the process of finding ...