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The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Typical convolutional neural networks (CNNs) are unable to capture both local and global contextual information effectively and apply a uniform operation to all pixels in an image. To address this, we propose an innovative approach that integrates a dynamic convolution operation at the encoder stage, improving image encoding quality and disease detection. In addition, a decoder based on the gated recurrent unit (GRU) is used for language modeling, and an attention network is incorporated to enhance consistency. This novel combination allows for improved feature extraction, mimicking the expertise of radiologists by selectively focusing on important areas and producing coherent captions with valuable clinical information.

In this study, we have presented a new report generation approach that utilizes dynamic convolution applied Resnet-101 (DyCNN) as an encoder (Verelst and Tuytelaars, 2019) and GRU as a decoder (Dey and Salemt, 2017; Pan et al., 2020), along with an attention network (see Figure 1). This integration innovatively extends the capabilities of image encoding and sequential caption generation, representing a shift from conventional CNN architectures. With its ability to dynamically adapt receptive fields, the DyCNN excels at capturing features of varying scales within the CXR images. This dynamic adaptability significantly enhances the granularity of feature extraction, enabling precise representation of localized abnormalities and structural intricacies. By incorporating this flexibility into the encoding process, our model can distil meaningful and contextually rich features from the radiographic data. While the attention mechanism enables the model to selectively focus on different regions of the image during caption generation. The attention mechanism enhances the report generation process by allowing the model to assign different importance weights to different regions of the image, mimicking human perception. In parallel, the GRU-based decoder adds a critical dimension to the process by ensuring a smooth, sequential generation of captions.

The findings of this study highlight the significant advancements achieved in chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Experiments conducted using the IU-Chest X-ray datasets showed that the proposed model outperformed other state-of-the-art approaches. The model achieved notable scores, including a BLEU_1 score of 0.591, a BLEU_2 score of 0.347, a BLEU_3 score of 0.277 and a BLEU_4 score of 0.155. These results highlight the efficiency and efficacy of the model in producing precise radiology reports, enhancing image interpretation and clinical decision-making.

This work is the first of its kind, which employs DyCNN as an encoder to extract features from CXR images. In addition, GRU as the decoder for language modeling was utilized and the attention mechanisms into the model architecture were incorporated.

This paper compares the web accessibility of Indian museum websites assessing the level of compliance to the Web Content Accessibility Guidelines 2.1 (WCAG 2.1). The study aims to assess the accessibility of Indian museum websites in terms of their severity.

The accessibility evaluation of 11 Indian museum websites was conducted using Siteimprove Accessibility Checker (SAC), an automated website testing tool.

The study results indicate that the mean conformance score for the Indian museum websites for level A was 19.27, while for level AA and AAA, it came out to be 2.63 and 4.09, respectively, with the highest severity scores for error (16.3) followed by review (5.81) criteria and warning (3.81). The major findings indicate that the websites of Indian museums poorly conform to web accessibility guidelines.

The study's findings will assist the museum's website creators, managers and administrators in determining the level of conformity as per standard accessibility guidelines helping them make strategic decisions to improve the accessibility.

Most of the studies available in the field of website accessibility range from the web accessibility of educational institutions, tourism websites, municipal websites and ministerial websites, but there are very few studies investigating the accessibility of museum websites. A quantitative evaluation of different aspects of accessibility was conducted in the study, which can pave the way for the better design of web sites by addressing deficiencies.

The study aims to qualitatively analyze how faculty can mobilize the intellectual capital of higher education institutions (HEIs), comprising human, structural and relational capital to enable the education and learning of individuals with intellectual and developmental disabilities.

Drawing upon the extant literature, the researcher conducted a qualitative study through written, in-depth interviews with a sample of 40 academic staff/faculty members having prior experience in teaching individuals with intellectual and developmental disabilities. The data was collected through a set of questions formulated as key questions, to be asked to all participants for their responses.

Results of the analysis demonstrated that intellectual capital’s contribution to higher education of individuals with intellectual and developmental disabilities can be best understood in terms of its three components/dimensions. Accordingly, three main themes, with each comprising two sub-themes were uncovered. The first theme, leveraging human capital comprised: faculty acumen and faculty training as sub-themes; the second theme, resourcing structural capital comprised: tangible and intangible structural capital as sub-themes; and the third theme, nurturing relational capital comprised: in-class engagement and the second is ex-class connection as sub-themes.

The paper collects data from 40 faculty having prior experience in teaching individuals with intellectual and developmental disabilities to explore and reveal a completely new perspective of looking at intellectual capital as a means of providing accessible and inclusive higher education to differently-abled students, making them a part of the mainstream.

This study aims to explore how a postmodern tribe enacts and re-interprets ideologies as a part of consumers’ collective experience, to enhance our understanding of consumer communities in conjunction with ideological capacities.

The community of “presenteers” is conceptualized as a self-organized tribe with heterogeneous components that generate capacities to act. Netnographic observation was conducted on 18 presenteer accounts and lasted around six months. Real-time data were collected by taking screenshots of the posts and stories that these users created and publicly shared. Data were analysed by adopting assemblage theory, combining inductive and deductive approaches. Firstly, a qualitative visual-textual content analysis of the tribe’s defining components was conducted. Then, the process continued with the thematic analysis of the ideological underpinnings of the tribe’s enactments.

Findings shed light on the ways in which consumer communities interpret the entanglement of religious, political, and cultural ideologies in shaping their experiences. In the case of the presenteers tribe, findings reflect a novel ideological interplay between neo-Ottomanism, post-feminism and consumerism.

The study offers a deep dive into a unique tribe that is being organized around the consumer-created practice of “presenteering” and investigates consumer communalization in alignment with the ideological turn in culture-oriented interpretative research on consumers, consumption, and markets. This exploration helps to bridge the research on the communalization of consumers with the recent discussions of ideology in the postmodern market.

The study offers a deep dive into a unique tribe that is being organized around the consumer-created practice of “presenteering” and investigates consumer communalization in alignment with the ideological turn in culture-oriented interpretative research on consumers, consumption, and markets. This exploration helps to bridge the research on the communalization of consumers with the recent discussions of ideology in the postmodern market.

This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.

A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.

The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.

The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.

Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.

The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.

This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.

This collaborative paper presents three case studies on four scholars' experiences with remote data collection. The authors highlight the challenges and strengths of online qualitative research across three disparate projects: an interdisciplinary exploration of matrilineal heritage, an examination of Irish women's sexual identity and an investigation of dress practices among Tz'utujil-Maya.

Qualitative researchers traditionally go into the field to explore and understand social phenomena. At the onset of the COVID-19 pandemic, while people faced the daily realities of a worldwide crisis from within their homes, remote data collection became a necessary strategy to pursue knowledge. As a result, researchers adapted to unknowns regarding recruiting, scheduling, technology, interviewing and analysis.

Participant and researcher experiences during the adaptation to remote interviewing yielded important lessons on research strategies.

Outcomes from these studies highlight the potential value of online data collection alongside the necessity for flexibility in designing and conducting qualitative research.

A key social networking site for teachers, TikTok offers a new and valuable lens on educator attrition. This study aims to explore social media’s role in the increased transparency around leaving the profession and the online narratives crafted around transitioning out of the classroom.

Drawing on the conceptual framework of emergent storytelling and a recursive thematic analysis of videos and comments posted to the #teacherquittok hashtag on TikTok, this study examines how teachers are using social media to share their experiences of exiting the classroom.

The authors find that teachers used TikTok to share personal accounts that form a meta-narrative that provides context to their decisions to leave, share stories of loss and gain through negotiating the transition out of the classroom and finally debate the implications for preservice teachers. The authors discuss key takeaways for rethinking teacher support, teacher education and the role of social media in teachers’ professional lives.

While many studies seek to understand teacher attrition, this work examines how teachers’ stories shared on social media may be shaping attrition into an increasingly networked and narrated act.

The purpose of this paper is to examine how social media can be an effective tool for academic libraries to support their communities in the digital environment and relay information about their cultural functions.

This paper involves a literature review to discuss the implementation of academic libraries’ cultural functions through social media account. This paper also observes some academic libraries’ accounts that use social media to carry out their cultural functions.

Social media provides opportunities for academic libraries in performing and developing their cultural functions. Academic libraries already use social media to deliver and communicate their cultural functions. However, some challenges might arise and necessitate a review of the library’s resources and the skills of library professionals.

This paper fills the lack of empirical studies analyzing the implementation of academic libraries’ cultural functions through social media accounts and contributes to the literature about the cultural functions of libraries in the digital environment. This paper can help those academic libraries wanting to leverage, bring innovation and increase their cultural functions in the digital environment through their social media accounts.

The purpose of this study was to examine the application of the collaborative research supervision approach (CRSA) to learning projects in higher education, using socialisation, externalisation, combination and internalisation (SECI) dimensions. The study, therefore, examined how these dimensions assisted learners in Botswana's higher education to generate research knowledge.

The study used a mixed-method research approach and exploratory research design. Purposive sampling was used to examine how the CRSA dimensions were employed in a classroom of 111 higher education learners who were carrying out research projects. Out of this population, 97 responded to a questionnaire, and 14 learners participated in a face-to-face interview. One hundred and eleven research documents produced by learners were analysed, and 42 observations were conducted.

The study found that the four dimensions of CRSA assist greatly in the development of knowledge of the research processes. This study confirms that the CRSA in higher education institutions has the potential to enhance research knowledge and skills, build learners' confidence in research, engage in learning, reduce workload, reduce the frustration of doing research and help learners complete their work in time. Learners with weak research skills easily catch up with their average-performing peers.

It is important to recognise the methodological limitations of this study. The study used a mixed method and a single case. As a result, the results' significance cannot be justified. Additionally, the context and methodology restrict the findings' generalisability. There is obviously potential for additional cases since this article only offers a preliminary analysis of the single case issue. Consequently, the study recommends that yet another study could be conducted to check if the approach could be used for graduate learners. Another study could also be conducted to check if the approach could be used as a supervisory approach that can provide prospects for knowledge sharing and creating learning in an organisation.

The study discovered that when properly implemented, CRSA arrangement enhances research knowledge development and reduces the workload for both the supervisor and the student. When choosing this desired research supervision approach, either in terms of policy or in actual practice, it is important to take the potential for information exchange into account. This might result in improved research supervision efficacy in higher education and hence the production of better quality graduate learning projects.

This study recommends the use of the CRSA in higher education, so as to help learners with weak research skills, to collaboratively work with learners with high and average research skills. It also improves the quality of supervisor–learner learning relationship.

The research results were given to participants and respondents for approval to find out if what was written was what they said. The research results were also given to colleagues to check whether the analysis is balanced and fair and to check biases and exaggerations.

Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).