Academic Articles & Research Papers

Cybersecurity

Cybersecurity encompasses the protection of networks, computers, software, and data from unauthorized access, damage, or misuse. In academic institutions, cybersecurity is particularly critical due to the growing volume of sensitive informa...

Cybersecurity

Cybersecurity is generally considered as an information security topic, often associated with personal data and information databases: collecting, exposing, corrupting, or deleting these data. However, it is a more global problem, and relat...

Semi-State Actors in Cybersecurity

Abstract What does the global telecommunications company Huawei, a hacking-for-hire outfit in India, and Russian cyber criminals have in common? They all share a special relationship to the state, which significantly shapes the politics of ...

Cybersecurity

"This book is the first of its kind to introduce the integration of ethics, laws, risks, and policies in cyberspace. The book will advance understanding of the ethical and legal aspects of cyberspace followed by the risks involved along wit...

Recommender Systems in Cybersecurity

Abstract With the growth of CyberTerrorism, enterprises worldwide have been struggling to stop intruders from obtaining private data. Despite the efforts made by Cybersecurity experts, the shortage of skillful security teams and the usage o...

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...

Cyber risk and cybersecurity: a systematic review of data availability

Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020, indicating an increase of more than 50% since 2018. With the average cyber insurance claim rising from USD 145,000 in 2019 to USD 359,000 in 2020, th...

Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science

In this paper, we propose data statements as a design solution and professional practice for natural language processing technologists, in both research and development. Through the adoption and widespread use of data statements, the field ...

Neural Network Methods for Natural Language Processing

Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...

Special Issue: Finite State Methods in Natural Language Processing

Finite state methods have been in common use in various areas of natural language processing (NLP) for many years. A series of specialized workshops in this area illustrates this. In 1996, András Kornai organized a very successful workshop...

Natural Language Processing

Hints of the outbreak are detected through the modified circumstances favoring the outbreaks, like the warm weather contributing to epidermal outbreaks or the loss of sanitation leading to cholera outbreaks typically relying on the routine ...

Autoassociative neural networks

Pattern Recognition with Neural Networks in C++

From the Publisher: The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...

A renaissance of neural networks in drug discovery

INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...

Artificial Neural Networks in Medical Diagnosis

Artificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Two cases are studied. The first one is acute nephritis disease; da...

Recurrent Neural Networks for Prediction

New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) ...

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...

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 ...

The Graph Neural Network Model

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper,...

Neural Networks in Bioprocessing and Chemical Engineering