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Due to the environmental conditions, the detection and identification of hazardous situations in coal mines is a challenge. The purpose of this research is to focus on the underground fire detection, especially of smoldering fires, which are characterized by the outgassing of CO and C2H4.

The study developed a system based on a single semiconductor gas sensor and sensors for relative humidity and temperature. With a high‐dynamic‐range hardware control and data acquisition platform a commercial semiconductor gas sensor is operated with an application‐optimized temperature cycle to improve stability and selectivity.

A hierarchical evaluation strategy not only allows identification of smoldering fires signified by CO and C2H4 with a ratio of 100:1, but is also suitable for separating or quantifying typical interfering compounds such as CH4, CO, NOX or H2 thus helping to avoid costly false alarms. After promising laboratory pre‐tests, a system was built for field tests including test gases and re‐calibration algorithms. Currently the authors are working on a self‐monitoring strategy based on redundant data from impedance spectroscopy to improve the stability of the system.

This approach allows detection of C2H4 at sub‐ppm concentrations even in the presence of CH4 at levels up to 1 percent with only a single gas sensor. The system achieves classification reproducibility as well as robustness allowing the development of a cost‐efficient under‐ground fire detection system. The novel self‐monitoring strategy will further improve the reliability of the system.

This study applies Garfinkel’s (1967) concept of ‘breaching experiment’ to explore the impact of COVID-19-induced disruptions on the ‘emotion management’ practices of residential care workers in the United Kingdom and Germany. It examines the influence of professional feeling rules on workers, emphasizing the prescribed importance of displaying affective, empathetic concern for residents’ health and well-being. Findings demonstrate that authenticity and adherence to professional feeling rules in relation to emotional management are not mutually exclusive. The authors underscore how adherence to professional feeling rules upholds authentic care by reinforcing a professional ethos, which acts as a cornerstone motivating residential care workers. Ultimately, the study showcases how a professional ethos substantiates altruistic motivations, guiding proficient emotion management practices among care workers. It highlights how these workers drew upon their personal understanding and experiences to determine the appropriate emotions to express while providing care for residents amid the unprecedented challenges of the pandemic.

It is almost unbelievable that it is already 11 years ago that our most beloved friend and teacher Anselm Strauss died. In 1999 we had a conference in Magdeburg, Germany, where we tried to commemorate his very personal and creative way of doing sociological research and of teaching sociology that established an almost miraculous bridge to the minds of German and other European social scientists even though Anselm Strauss was very American. He was American in the best sense of using and encouraging creative freedom of expression, of showing witty nonconventionality, of relating in an egalitarian way to his interaction partners, of being empathically cooperative and practical in his thinking and in his personal relationships with his European students and colleagues. Today, instead, I would like to talk a little bit about his longer lasting impact on German-speaking social sciences and on other European social sciences as far as I have insight into them.

Childhood sociology as it has evolved from explicit critique of socialization sciences has developed two central concepts: “The child as (competent) actor” and the notion of “generational order.” It is above all the second concept that has not yet been fully dealt with within its sociological context. The term “generational order” is not just supposed to refer to ordered relations between (socially defined) age groups and their members, but also to a social order in general, as it is achieved by the ordered arrangement of age groups. From a historical perspective one can see that those efforts that aim at a disciplined society with small social control expenses do at the latest from the 19th century onwards concentrate on education and a well organized family and thus on a well ordered arrangement of age groups. It is an ordering process towards self-control, towards self-government as the most dense as well as discrete way of government. Until just some years ago such development appeared as an indispensable prerequisite of social order to those sociologists dealing with questions of childhood and growing up – at least as long as they assumed the perspective of socialization theory and sciences. Only the absence or deficiency of such a generational order had any chance to become an important scientific question.

Ship route prediction (SRP) is a quite complicated task, which enables the determination of the next position of a ship after a given period of time, given its current position. This paper aims to describe a study, which compares five families of multiclass classification algorithms to perform SRP.

Tested algorithm families include: Naive Bayes (NB), nearest neighbors, decision trees, linear algorithms and extension from binary. A common structure for all the algorithm families was implemented and adapted to the specific case, according to the test to be done. The tests were done on one month of real data extracted from automatic identification system messages, collected around the island of Malta.

Experiments show that K-nearest neighbors and decision trees algorithms outperform all the other algorithms. Experiments also demonstrate that linear algorithms and NB have a very poor performance.

This study is limited to the area surrounding Malta. Thus, findings cannot be generalized to every context. However, the methodology presented is general and can help other researchers in this area to choose appropriate methods for their problems.

The results of this study can be exploited by applications for maritime surveillance to build decision support systems to monitor and predict ship routes in a given area. For example, to protect the marine environment, the use of SRP techniques could be used to protect areas at risk such as marine protected areas, from illegal fishing.

The paper proposes a solid methodology to perform tests on SRP, based on a series of important machine learning algorithms for the prediction.

The purpose of this paper is to further the understanding of experiences of anti-social behaviour in LGBTIQ+ youth in university settings.

The discussion reflects on qualitative interviews with LGBTIQ+ young people studying at university (n=16) exploring their experiences of anti-social behaviour including harassment, bullying and victimisation in tertiary settings.

The findings demonstrate that attention should be paid to the complex nature of anti-social behaviour. In particular, LGBTIQ+ youth documented experiences of microaggressions perpetrated by other members of the LGBTIQ+ community. Using the taxonomy of anti-social behaviour against LGBTIQ+ people developed by Nadal et al. (2010, 2011), the authors build on literature that understands microaggressions against LGBTIQ+ people as a result of heterosexism, to address previously unexplored microaggressions perpetrated by other LGBTIQ+ people.

Future research could seek a larger sample of participants from a range of universities, as campus climate may influence the experiences and microaggressions perpetrated.

Individuals within the LGBTIQ+ community also perpetrate microaggressions against LGBTIQ+ people, including individuals with the same sexual orientation and gender identity as the victim. Those seeking to respond to microaggressions need to attune their attention to this source of anti-social behaviour.

Previous research has focused on microaggressions and hate crimes perpetrated by non-LGBTIQ+ individuals. This research indicates the existence of microaggressions perpetrated by LGBTIQ+ community members against other LGBTIQ+ persons. The theoretical taxonomy of sexual orientation and transgender microaggressions is expanded to address LGBTIQ+ perpetrated anti-social behaviour.

By mapping-out the capabilities, challenges and limitations of named-entity recognition (NER), this article aims to synthesise the state of the art of NER in the context of the early modern research field and to inform discussions about the kind of resources, methods and directions that may be pursued to enrich the application of the technique going forward.

Through an extensive literature review, this article maps out the current capabilities, challenges and limitations of NER and establishes the state of the art of the technique in the context of the early modern, digitally augmented research field. It also presents a new case study of NER research undertaken by Enlightenment Architectures: Sir Hans Sloane's Catalogues of his Collections (2016–2021), a Leverhulme funded research project and collaboration between the British Museum and University College London, with contributing expertise from the British Library and the Natural History Museum.

Currently, it is not possible to benchmark the capabilities of NER as applied to documents of the early modern period. The authors also draw attention to the situated nature of authority files, and current conceptualisations of NER, leading them to the conclusion that more robust reporting and critical analysis of NER approaches and findings is required.

This article examines NER as applied to early modern textual sources, which are mostly studied by Humanists. As addressed in this article, detailed reporting of NER processes and outcomes is not necessarily valued by the disciplines of the Humanities, with the result that it can be difficult to locate relevant data and metrics in project outputs. The authors have tried to mitigate this by contacting projects discussed in this paper directly, to further verify the details they report here.

The authors suggest that a forum is needed where tools are evaluated according to community standards. Within the wider NER community, the MUC and ConLL corpora are used for such experimental set-ups and are accompanied by a conference series, and may be seen as a useful model for this. The ultimate nature of such a forum must be discussed with the whole research community of the early modern domain.

NER is an algorithmic intervention that transforms data according to certain rules-, patterns- or training data and ultimately affects how the authors interpret the results. The creation, use and promotion of algorithmic technologies like NER is not a neutral process, and neither is their output A more critical understanding of the role and impact of NER on early modern documents and research and focalization of some of the data- and human-centric aspects of NER routines that are currently overlooked are called for in this paper.

This article presents a state of the art snapshot of NER, its applications and potential, in the context of early modern research. It also seeks to inform discussions about the kinds of resources, methods and directions that may be pursued to enrich the application of NER going forward. It draws attention to the situated nature of authority files, and current conceptualisations of NER, and concludes that more robust reporting of NER approaches and findings are urgently required. The Appendix sets out a comprehensive summary of digital tools and resources surveyed in this article.

The use of articles from scientific journals is an important part of research-based teaching at universities. The selection of relevant work from among the increasing amount of scientific literature can be problematic; the challenge is to find relevant recommendations, especially when the related articles are not obviously linked. This paper seeks to discuss these issues.

This paper focuses on the analysis of user activity traces in journals using the open source software “Open Journal Systems” (OJS). The research questions to what extent end users follow a certain link structure given within OJS or immediately select the articles according to their interests. In the latter case, the recorded data sets are used for creating further recommendations. The analysis is based on an article matrix, displaying the usage frequency of articles and their user selected successive articles within the OJS. Furthermore, the navigation paths are analysed.

It was found that the users tend to follow a set navigation structure. Moreover, a hybrid recommendation system for OJS is described, which uses content based filtering as the basic system extended by the results of a collaborative filtering approach.

The paper presents two original contributions: the analysis of user path tracing and a novel algorithm that allows smooth integration of new articles into the existing recommendations, due to the fact that scientific journals are published in a frequent and regular time sequence.

The purpose of this paper is to improve users’ search results relevancy by manipulating their explicit feedback.

CoRRe – an explicit feedback model integrating three popular feedback, namely, Comment-Rating-Referral is proposed in this study. The model is further enhanced using case-based reasoning in retrieving the top-5 results. A search engine prototype was developed using Text REtrieval Conference as the document collection, and results were evaluated at three levels (i.e. top-5, 10 and 15). A user evaluation involving 28 students was administered, focussing on 20 queries.

Both Mean Average Precision and Normalized Discounted Cumulative Gain results indicate CoRRe to have the highest retrieval precisions at all the three levels compared to the other feedback models. Furthermore, independent t-tests showed the precision differences to be significant. Rating was found to be the most popular technique among the participants, producing the best precision compared to referral and comments.

The findings suggest that search retrieval relevance can be significantly improved when users’ explicit feedback are integrated, therefore web-based systems should find ways to manipulate users’ feedback to provide better recommendations or search results to the users.

The study is novel in the sense that users’ comment, rating and referral were taken into consideration to improve their overall search experience.