Academic Articles & Research Papers

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...

State-of-the-art in artificial neural network applications: A survey

This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and ar...

Neural networks and fuzzy systems

Understanding of a convolutional neural network

The term Deep Learning or Deep Neural Network refers to Artificial Neural Networks (ANN) with multi layers. Over the last few decades, it has been considered to be one of the most powerful tools, and has become very popular in the literatur...

Are artificial neural networks black boxes?

Artificial neural networks are efficient computing models which have shown their strengths in solving hard problems in artificial intelligence. They have also been shown to be universal approximators. Notwithstanding, one of the major criti...

Modular learning in neural networks

In the development of large-scale knowledge networks much recent progress has been inspired by connections to neurobiology. An important component of any neural network is an accompanying learning algorithm. Such an algorithm, to be biologi...

Neural Networks for Pattern Recognition

Abstract This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes technique...

Neural networks for financial forecasting

When applied to the world of finance, neural networks are automated trading systems, based on mapping inputs and outputs for forecasting probable future values. In Neural Networks for Financial Forecasting - the first book to focus on the r...

Neural Networks

Neural Networks, Second Edition provides a complete introduction to neural networks. It describes what they are, what they can do, and how they do it. While some scientific background is assumed, the reader is not expected to have any prior...

Pro Deep Learning with TensorFlow

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with T...

Federated Machine Learning

Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security. We propose a possible solution to t...

Challenges in automotive software engineering

The amount of software in cars grows exponentially. Driving forces of this development are cheaper and more powerful hardware and the demand for innovations by new functions. The rapid increase of software and software based functionality b...

Knowledge management in software engineering

Software organizations’ main assets are not plants, buildings, or \nexpensive machines. A software organization’s main asset is its intellectual \ncapital, as it is in sectors such as consulting, law, investment \nbanking, and advertising. ...

Advances in Software Engineering and Knowledge Engineering

The papers collected in this book were invited by the editors as tutorial courses or keynote speeches for the Fourth International Conference on Software Engineering and Knowledge Engineering. The book offers wide coverage of the main topic...

Software engineering economics

This work aims to shed light on an important topic that has begun to emerge in recent years, which is the economics of software engineering as a basic pillar in national development and confronting the competitive market challenges that cha...

Ultrasound-based breast nodule malignancy diagnosis using CNN enhanced by knowledge distillation.

Nuclear astrophysics

Nuclear astrophysics is that branch of astrophysics which helps understanding some of the many facets of the Universe through the knowledge of the microcosm of the atomic nucleus. In the last decades much advance has been made in nuclear as...

High Energy Astrophysics

What role does viscosity play in accretion discs? How do you calculate the 'glitch function' of a pulsar? And can strong shocks account for the energy spectrum of electrons in our Galaxy? These are just some of the exciting questions that P...

Astrophysics for Physicists

Designed for teaching astrophysics to physics students at advanced undergraduate or beginning graduate level, this textbook also provides an overview of astrophysics for astrophysics graduate students, before they delve into more specialize...

Accretion Power in Astrophysics

Accretion Power in Astrophysics examines accretion as a source of energy in both binary star systems containing compact objects, and in active galactic nuclei. Assuming a basic knowledge of physics, the authors describe the physical process...