Academic Articles & Research Papers

Vulnerability Assessment of Cybersecurity for SCADA Systems

Vulnerability assessment is a requirement of NERC's cybersecurity standards for electric power systems. The purpose is to study the impact of a cyber attack on supervisory control and data acquisition (SCADA) systems. Compliance of the requ...

Cybersecurity and cyberwar: what everyone needs to know

1. Why cyberspace is wonderfulEL and complicated What is cyberspace? Why do people talk about the difference of a networked world? How does the Internet actually work? Who owns this thing? WaitEL You mean no one runs the internet? What can ...

Emergence of Fintech and cybersecurity in a global financial centre

Purpose This paper aims to explore how the regulator of a global financial centre (GFC) under an international trend of adopting emerging technologies for financial services (Fintech) articulates such opportunities and risks strategically. ...

A Survey of Cybersecurity of Digital Manufacturing

The Industry 4.0 concept promotes a digital manufacturing (DM) paradigm that can enhance quality and productivity, which reduces inventory and the lead time for delivering custom, batch-of-one products based on achieving convergence of addi...

Cybersecurity for distributed energy resources and smart inverters

The increased penetration of distributed energy resources (DER) will significantly increase the number of devices that are owned and controlled by consumers and third‐parties. These devices have a significant dependency on digital communica...

A systemic framework for addressing cybersecurity in construction

Today, the built environment is designed, built, and managed using digital technology, making it increasingly exposed to cyber security risks. Cybersecurity is a general topic, and the construction sector has been borrowing general solution...

Suicide Note Classification Using Natural Language Processing: A Content Analysis

Suicide is the second leading cause of death among 25-34 year olds and the third leading cause of death among 15-25 year olds in the United States. In the Emergency Department, where suicidal patients often present, estimating the risk of r...

A literature survey of active machine learning in the context of natural language processing

Active learning is a supervised machine learning technique in which the learner is in control of the data used for learning. That control is utilized by the learner to ask an oracle, typically a human with extensive knowledge of the domain ...

Neural networks in control systems

Some of the problems that arise in the control of nonlinear systems in the presence of uncertainty are considered. Multilayer neural networks and radial basis function networks are used in the design of identifiers and controllers, and grad...

Artificial neural networks for speech and vision

Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...

Artificial neural networks in process engineering

Artificial neural networks are made up of highly interconnected layers of simple ‘neuron-like’ nodes. The neurons act as nonlinear processing elements within the network. An attractive property of artificial neural networks is that, given t...

Neural networks for control

Provides a quick overview of neural networks and explains how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorit...

Neural networks and fuzzy systems

Artificial Neural Networks in Agriculture

Artificial neural networks are one of the most important elements of machine learning and artificial intelligence. They are inspired by the human brain structure and function as if they are based on interconnected nodes in which simple proc...

Neural networks for system identification

Two approaches are presented for utilization of neural networks in identification of dynamical systems. In the first approach, a Hopfield network is used to implement a least-squares estimation for time-varying and time-invariant systems. T...

Multilayer perceptron and neural networks

Abstract:- The attempts for solving linear inseparable problems have led to different variations on the number of layers of neurons and activation functions used. The backpropagation algorithm is the most known and used supervised learning ...

Fuzzy logic and neural network handbook

Fuzzy logic principles and algorithms design guidelines for fuzzy logic systems enhanced training algorithms maximum likelihood training temporal difference learning NADINE hybrid learning systems explanation and reasoning within connectivi...

Prediction Intervals for Artificial Neural Networks

The artificial neural network (ANN) is becoming a very popular model for engineering and scientific applications. Inspired by brain architecture, artificial neural networks represent a class of nonlinear models capable of learning from data...

Nonlinear Flight Control Using Neural Networks

The theoretical developmentofa direct adaptivetracking controlarchitectureusingneuralnetworks ispresented. Emphasis is placed on utilization of neural networks in a  ight control architecture based on feedback linearization of the aircraft...

Cellular neural networks: theory

A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a m...