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Managing passenger information during disruption (PIDD) is a significant factor in running effective and quick-to-recover rail operations. Disruptions are unpredictable, and their timely resolution is ultimately dependent on the expert knowledge of experienced frontline staff. The development of frontline employees by their employers usually takes the form of practice reviews and 'on-the-job' learning, while academic education majors on theoretical approaches and classroom-based teaching. This paper reports on a novel industry-funded project that has developed a serious game (the 'Rail Disruption Game') that combines theory and practice to better manage PIDD for frontline staff in a UK train operating company (TOC). It defines challenges and the development method for the Rail Disruption Game; it also incorporates developer and user feedback. This paper provides insight into how to design, make and deploy a serious game as part of a gamified management process. [ABSTRACT FROM AUTHOR]

Right from the beginning, attendance has played an important role in the education systems, not only in student success but in the overall interest of the matter. Although all schools try to accentuate good attendance, still some schools find it hard to achieve the required level (96% in UK) of average attendance. The most productive way of increasing the pupils′ attendance rate is to predict when it is going to go down, understand the reasons—why it happened—and act on the affecting factors so as to prevent it. Artificial intelligence (AI) is an automated machine learning solution for different types of problems. Several machine learning (ML) models like logistic regression, decision trees, etc. are easy to understand; however, complicated (Neural Network, BART etc.) ML models are not transparent but are black-boxes for humans. It is not always evident how machine intelligence arrived at a decision. However, not always, but in critical applications it is important that humans can understand the reasons for such decisions. In this paper, we present a methodology on the application example of pupil attendance for constructing explanations for AI classification algorithms. The methodology includes building a model of the application in the Isabelle Insider and Infrastructure framework (IIIf) and an algorithm (PCR) that helps us to obtain a detailed logical rule to specify the performance of the black-box algorithm, hence allowing us to explain it. The explanation is provided within the logical model of the IIIf, thus is suitable for human audiences. It has been shown that the RR-cycle of IIIf can be adapted to provide a method for iteratively extracting an explanation by interleaving attack tree analysis with precondition refinement, which finally yields a general rule that describes the decision taken by a black-box algorithm produced by Artificial intelligence. [ABSTRACT FROM AUTHOR]

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration. [ABSTRACT FROM AUTHOR]

Toxic online content has become a major issue in recent years due to the exponential increase in the use of the internet. In France, there has been a significant increase in hate speech against migrant and Muslim communities following events such as Great Britain's exit from the EU, the Charlie Hebdo attacks, and the Bataclan attacks. Therefore, the automated detection of offensive language and racism is in high demand, and it is a serious challenge. Unfortunately, there are fewer datasets annotated for racist speech than for general hate speech available, especially for French. This paper attempts to breach this gap by (1) proposing and evaluating a new dataset intended for automated racist speech detection in French; (2) performing a case study with multiple supervised models and text representations for the task of racist language detection in French; and (3) performing cross-lingual experiments. [ABSTRACT FROM AUTHOR]

Citizen engagement and participation are a key focus for government and government agencies, and with the advent of Internet technologies questions arise about the role and impact of technology on citizen participation. This paper aims to explore the role of technology in citizen participation within schools. This research used in-depth comparative case studies using examples from two different schools and school systems, one in the United Kingdom and one in Indonesia. The wider school systems are complex and dynamic environments with multiple stakeholders, media, and supporting systems, and the schools operate under geopolitical and social influences. This paper provides a framework, based on Actor-Network Theory (ANT), for capturing e-participation in schools, particularly identifying the influence of technology as a conduit for enabling, engaging, and empowering stakeholders. [ABSTRACT FROM AUTHOR]

Most aircraft in the world are tracked by various surveillance radar systems. Currently there is no legal requirement for light aircraft to be fitted with a transponder; however, this does not mean light aircraft should not be tracked. By adding a cheap, live tracking solution for light aircraft, the safety of low-flying aircraft pilots can be greatly increased. The radio operators who coordinate the aircraft can have an improved understanding of the air traffic and in the event of an emergency, the position of the aircraft can be relayed to emergency services. This paper proposes an approach to use a smartphone as an aircraft transponder to improve the radar tracking capabilities of low-flying aircraft. This study presents a practical and effective approach as well as a prototype implementation. The study includes the development of the three main components: (1) A mobile application that transforms a smartphone into an aircraft transponder; exploiting the GPS functionalities, (2) a desktop application that visualizes the aircraft data in real time on a map, and (3) a backend that bridges the mobile and the desktop application. To evaluate the study, flight tests were performed in a real aircraft over the Isle of Wight in the UK. [ABSTRACT FROM AUTHOR]