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COVID-19 continues to spread, and cause increasing deaths. Physicians diagnose COVID-19 using not only real-time polymerase chain reaction but also the computed tomography (CT) and chest x-ray (CXR) modalities, depending on the stage of infection. However, with so many patients and so few doctors, it has become difficult to keep abreast of the disease. Deep learning models have been developed in order to assist in this respect, and vision transformers are currently state-of-the-art methods, but most techniques currently focus only on one modality (CXR).

This work aims to leverage the benefits of both CT and CXR to improve COVID-19 diagnosis. This paper studies the differences between using convolutional MobileNetV2, ViT DeiT and Swin Transformer models when training from scratch and pretraining on the MedNIST medical dataset rather than the ImageNet dataset of natural images. The comparison is made by reporting six performance metrics, the Scott–Knott Effect Size Difference, Wilcoxon statistical test and the Borda Count method. We also use the Grad-CAM algorithm to study the model's interpretability. Finally, the model's robustness is tested by evaluating it on Gaussian noised images.

Although pretrained MobileNetV2 was the best model in terms of performance, the best model in terms of performance, interpretability, and robustness to noise is the trained from scratch Swin Transformer using the CXR (accuracy = 93.21 per cent) and CT (accuracy = 94.14 per cent) modalities.

Models compared are pretrained on MedNIST and leverage both the CT and CXR modalities.

How can we take multimodalities (the discursive, material, spatial, visual, emotional, embodied, etc.) of institutions seriously? In contemplating the implications of the “multimodal turn” (broadly defined) for institutional inquiry and theory, I first situate it within its intellectual current in the social sciences more broadly. I then use three ethnographic vignettes from Israeli high-tech conferences, all centering on “place” (as a – presumably first and foremost – geographical and material reality) to highlight the shortcomings of a “weak” multimodal approach and the promise of a “strong” one. Finally, I suggest ways to capture multiple modalities within an integrated account and discuss the challenges entailed in an institutional inquiry undertaken to acknowledge, and conceptualize, non-linguistic realities.

The purpose of this research is to explore how an industry is represented in multimodal public media narratives and to explore how this representation subsequently affects the formation of public sense-giving space during a persisting crisis, such as a pandemic. The question asked is: how do the use of multimodality by public service media dynamically shape representations of industry identity during a persisting crisis?

This study made use of a multimodal approach. The verbal and visual media text on the restaurant industry during the COVID-19 pandemic that were published in Finland by the public service media distributor Yle were studied. Data published between March 2020 and March 2022 were analysed. The data consisted of 236 verbal texts, including 263 visuals.

Three narratives were identified– victim, servant and survivor – that construct power relations and depict the identity of the restaurant industry differently. It was argued that multimodal media narratives hold three meaning making functions: sentimentalizing, juxtaposing and nuancing industry characteristics. It was also argued that multimodal public service media narratives have wider implications in possibly shaping the future attractiveness of the industry and organizational members' understanding of their identity.

This research contributes to sensemaking literature in that it explores the role of power – explicitly or implicitly constructed through media narratives during crisis. Furthermore, this research contributes to sensemaking literature in that it shows how narratives take shape multimodally during a continuous crisis, and how this impacts the construction of industry identity.

Our world had always been multimodal, but studying how young children enact and embody literacy practices, especially reading, has often been overlooked. The purpose of this study was to examine how young children respond to nonfiction picturebooks in multimodal ways. This paper aims to answer the question: What multimodal resources do readers use to respond to and construct meaning from nonfiction picturebooks?

Undergirded by Rosenblatt’s transactional theory of reading and social semiotic multimodality, a 9-min video clip of three boys making sense of one nonfiction picturebook during reading workshop was analyzed using Norris’ approach to multimodal data analysis. This research stemmed from a five-month-long case study of one kindergarten class’s multimodal and collective responses to nonfiction picturebooks.

Findings demonstrate how readers use gesture, gaze and proxemics in addition to language to signal agreement with one another, explain new ideas or concepts to one another and incorporate their background knowledge. In addition to reading images, the children learned to read each other.

This research indicates that reading is inherently multimodal, recursive and complex and provides implications for teachers to reconsider what kinds of responses they prioritize in their classrooms. Additionally, this research establishes the need to better understand how readers respond to nonfiction books and a broader examination of multimodality in the literacy curriculum.

In job advertisements, companies present claims about their organizational identity. My study explores how employers use multimodality in visuals and verbal text to construct organizational identity claims and address potential future employees. Drawing on a multimodal analysis of job advertisements used by German fashion companies between 1968 and 2013, I identify three types of job advertisements and analyze their content and latent meanings. I find three specific relationships between identity claims’ verbal and visual dimensions that also influence viewers’ attraction to, perception of the legitimacy of, and identification with organizations. My study contributes to research on multimodality and on organizational identity claims.

This chapter explores the challenges and opportunities of using multiliteracies pedagogy and multimodality in a nontraditional English language arts classroom. The paper highlights the dynamic and contemporary nature of the multiliteracies pedagogy and multimodal literacy practices proposed by the New London Group (1996). This paper makes connections through the analysis of scholarship and practice and provides solutions for educators to promote learning that is meaningful, engaging, and relevant to students. The focus is on promoting literacy instruction that values students' creativity, language, and culture to cultivate analysis, inquiry, and agency.

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

The article seeks to enrich the body of research on store atmospherics by identifying how storefront window design impacts store entry decisions. An innovative multimodal design approach is presented, considering both visual and verbal constituents.

Study 1 draws on a corpus of high-end storefront windows to create a categorization regarding different levels of verbo-visual complexity. The survey in Study 2 (n = 234) serves two purposes: first, to confirm these levels of complexity and second, to investigate the relation between the complexity of window design and store entry decisions.

Study 2 confirms the order of complexity established in Study 1. The results reveal an inverted-U relationship between window complexity and store entry propensity. Windows of medium level of complexity produce shoppers' relatively highest store entry propensity.

The findings suggest that retailers would benefit from adopting verbo-visual window designs of medium complexity, as this combination optimizes the likeliness of consumers to enter stores.

Research on store atmospherics has until recently primarily focused on in-store cues. Studies on store windows remain vastly underrepresented in extant scholarship. The article not only fills this gap but also incorporates an original interdisciplinary angle on multimodality, which offers new methodological perspectives for research in retail and distribution scholarship.

This paper aims to investigate adolescent English as a foreign language (EFL) learners’ digitally mediated multimodal compositions across different genres of writing.

Three Korean high school students participated in the study and created multiple multimodal texts over the course of one academic semester. These texts and other materials were the basis for this study’s qualitative case studies. Multiple sources of data (e.g. class observations, demographic surveys, interviews, field notes and students’ artifacts) were collected. Drawing upon the inductive approach, a coding-oriented analysis was used for the collected data. In addition, a multimodal text analysis was conducted for the students’ multimodal texts and their storyboards.

The study participants’ perceptions of multimodal composing practices seemed to be positively reshaped as a result of them creating multimodal texts. Some participants created multimodal products in phases (e.g. selecting or changing a topic, constructing a storyboard and editing). Especially, although the students’ creative processes had a similarly fixed and linear flow from print-based writing to other modalities, their creative processes proved to be flexible, recursive and/or circular.

This study contributes to the understanding of adolescent English language learners’ multimodal composing practices in the EFL context, which has been underexplored in the literature. It also presents the students’ perspectives on these practices. In short, it provides theoretical and methodological grounds for future L2 literacy researchers to conduct empirical studies on multimodal composing practices.

This paper aims to examine language learners’ critical multimodal literacy practices with a moving-image text, focusing on text comprehension and interpretation rather than text production. It takes a critical perspective towards multimodality and proposes the simultaneous emphasis on critical and multimodal literacies.

This qualitative teacher-inquiry adopts critical multimodal literacy as the framework for understanding learners’ literacy practices. The course implementation highlights images, sounds and words as encompassing the five modes of visual, aural, linguistic, gestural and spatial (Arola et al., 2014) in emphasizing the multimodal in critical multimodal literacy, and the purposeful organization of the images, sounds and words as reflecting the critical in critical multimodal literacy. The analysis also adopts Serafini’s (2010) concentric perceptual, structural and ideological perspectives as the tenets of critical multimodal literacy.

The findings show that focusing on images, sounds, words and their purposeful organization enabled the students to critically examine a moving-image text through considerations for the multiple modes and arriving at the structural and ideological interpretive perspectives.

This study fills a gap in the literature, as very little research has been done to investigate the ways in which language learners engage with, that is, comprehend and interpret, moving-image multimodal texts. In addition, it presents a critical multimodal literacy framework based on Serafini’s (2010) tripartite perspectives and offers pedagogical suggestions for incorporating critical multimodal literacy in language classrooms.