The graduation project of Andrii Roizin, a software engineering student at Saxion, was developed as a part of the Sportkeur 2.0 project. This project is led by Go2Sure and the Saxion Ambient Intelligence research group is one of its partners.             The purpose of the project was to discover the …

Predictive maintenance is the promise of the future in infrastructure asset management. Predictive maintenance more and more uses sensor data. Sensors are relatively cheap, and their data mostly comes in huge quantities. Trends or flags may be observed in the data, sometimes with traditional statistical …

The number of applications in which industrial robots share their working environment with people is increasing. Robots appropriate for such applications are equipped with safety systems according to ISO/TS 15066:2016 and are often referred to as collaborative robots (cobots). Due to the nature of human-robot …

This paper reports on the first stage of a research project1) that aims to incorporate objective measures of physical activity into health and lifestyle surveys. Physical activity is typically measured with questionnaires that are known to have measurement issues, and specifically, overestimate the amount …

This is a thesis on developing software that detects things using machine learning and computer vision algorithms. Furthermore, the application includes the use of RTDE to operate a robotic arm that can take the fruit and deliver it to a certain location.

Software developer OVSoftware seeks to improve the speed and quality of their testing suites using Machine Learning. This paper aims to research the possibilities of using Machine Learning for unit test generation within OVSoftware. By determining the performance indicators that indicate test quality, …

Explainable artificial intelligence (xAI) is seen as a solution to making AI systems less of a “black box”. It is essential to ensure transparency, fairness, and accountability – which are especially paramount in the financial sector. The aim of this study was a preliminary investigation of the perspectives …

Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological …

The use of algorithmic tools by journalists for information-gathering has received particular attention in recent years. While it might facilitate the research process, there are also concerns about their impact on journalism. Based on reconstruction interviews with 27 journalists, we first answer the …

Graphs are ubiquitous. Many graphs, including histograms, bar charts, and stacked dotplots, have proven tricky to interpret. Students’ gaze data can indicate students’ interpretation strategies on these graphs. We therefore explore the question: In what way can machine learning quantify differences in …