Towards Automatic Principles of Persuasion Detection Using Machine Learning Approach

Persuasion is a human activity of influence. In marketing, persuasion can help customers find solutions to their problems, make informed choices, or convince someone to buy a useful (or useless) product or service. In computer crimes, persuasion can trick users into revealing sensitive information, or even performing actions that benefit...

In silico exploration of post-burn contraction using uncertainty quantification

Burns can make patients’ lives quite miserable. Apart from prominent and thickened, or hypertrophic, scars, the skin may be characterized by contraction. When this contraction is so severe that the patient loses joint mobility, it is called contracture. Then a patient may have difficulties with sports or other daily activities. The consequence...

The usefulness of artificial intelligence for safety assessment of different transport modes

Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency...

Driver Profile and Driving Pattern Recognition for Road Safety Assessment: Main Challenges and Future Directions

This study reviews the Artificial Intelligence and Machine Learning approaches developed thus far for driver profile and driving pattern recognition, representing a set of macroscopic and microscopic behaviors respectively, to enhance the understanding of human factors in road safety, and therefore reduce the number of crashes. It provides a...

Explainable Artificial Intelligence for human-AI collaboration

As a society, we have come to notice the influence and impact Artificially Intelligent (AI) agents have on the way we live our lives. For these AI agents to support us both effectively and responsibly, we require an understanding on how they make decisions and what the consequences are of these decisions. The research _field of Explainable...

Perceived challenges and opportunities of machine learning applications in governmental organisations: an interview-based exploration in the Netherlands

As the application of machine learning (ML) algorithms becomes more widespread, governmental organisations try to benefit from this technology. While ML has the potential to support public services, its application also introduces challenges. Several scholars have described the possible opportunities and challenges of ML applications in the...

A literature review of Artificial Intelligence applications in railway systems

Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective,...

Machine Learning and Counter-Terrorism: Ethics, Efficacy, and Meaningful Human Control

Machine Learning (ML) is reaching the peak of a hype cycle. If you can think of a personal or grand societal challenge – then ML is being proposed to solve it. For example, ML is purported to be able to assist in the current global pandemic by predicting COVID-19 outbreaks and identifying carriers (see, e.g., Ardabili et al. 2020). ML can make...

The Prevalence of Code Smells in Machine Learning Projects

Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer science landscape. Yet, there still exists a lack of software engineering experience and best practices in this field. One such best practice, static code analysis, can be used to find code smells, i.e., (potential) defects in the source code,...