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 …

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 …

Breast cancer is one of the most dangerous forms of cancer exists among women. The
breast cancer is diagnosed using histology images. The purpose of this paper is to classify …

Support vector machines (SVMs) represent a breakthrough in the theory of learning systems.
It is a new generation of learning algorithms based on recent advances in statistical …

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

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 …

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 …

1. The Age of Wavelets Introduction 1 1.1 The Origins of Wavelets-Are They Fundamentally
New? 1 1.2 Wavelets and Other Reality Transforms 3 1.3 Managing Heisenberg's …

Security breaches due to attacks by malicious software (malware) continue to escalate posing
a major security concern in this digital age. With many computer users, corporations, and …

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 …