Human exploration of deep space will involve missions of substantial distance and duration.
To effectively mitigate health hazards, paradigm shifts in astronaut health systems are …

Within clinical, biomedical, and translational science, an increasing number of projects are
adopting graphs for knowledge representation. Graph‐based data models elucidate the …

Machine learning techniques are being widely used to develop an intrusion detection system
(IDS) for detecting and classifying cyberattacks at the network-level and the host-level in a …

Stock market or equity market have a profound impact in today's economy. A rise or fall in
the share price has an important role in determining the investor's gain. The existing …

This article describes how sequential data modeling is a relevant task in Cybersecurity.
Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent neural …

… the form K[1 - cos(40 - 4'o)], where 40 is the end point of the "allowed" range and K = 32
kcal/mol. Based on our experience and that of others (22), we increased the torsional constant K. …

… We call i, j, k as bases of space 5R3. By this we mean that any vector in 933 can be … We
also say i, 1?, k span the space 933. Let 17 = ai + b; + ck be a vector in 5R3. Continuously …

The neural network, one of the intelligent data mining technique that has been used by
researchers in various areas for the past 10 years. Prediction and analysis of stock market data …

Recently, Convolutional neural network (CNN) architectures in deep learning have achieved
significant results in the field of computer vision. To transform this performance toward the …

The R-peak detection is crucial in all kinds of electrocardiogram (ECG) applications.
However, almost all existing R-peak detectors suffer from the non-stationarity of both QRS …