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The purpose of this study was to explore the viability of transinformation analysis as a multimodal readability metric. A novel approach was called for, considering that existing and established readability metrics are strictly used to measure linguistic complexity. Yet, the corpus of multimodal literature continues to grow, along with the need to understand how non-linguistic modalities contribute to the complexity of the reading experience.

In this exploratory study, think aloud screen recordings of eighth-grade readers of the born-digital novel Inanimate Alice were analyzed for complexity, along with transcripts of post-oral retellings. Pixel-level entropy analysis served as both an objective measure of the document and a subjective measure of the amount of reader information attention. Post-oral retelling entropy was calculated at the unit level of the word, serving as an indication of complexity in recall.

Findings confirmed that transinformation analysis is a viable multimodal readability metric. Inanimate Alice is an objectively complex document, creating a subjectively complex reading experience for the participants. Readers largely attended to the linguistic mode of the story, effectively reducing the amount of information they processed. This was also evident in the brevity and below average complexity of their post-oral retellings, which relied on recall of the linguistic mode. There were no significant group differences among the readers.

This is the first study that uses entropy to analyze multimodal readability.

This chapter focuses on strategies to initiate a shift in mobility behaviour away from private cars towards a combination of more environmentally friendly transport modes including public transport, ride- and car sharing or even completely carbon-free modes like walking and cycling. The requirement for such a shift is that people must be able to actually choose between different travelling options and combine them within an intermodal mobility network. Here, shared mobility has a considerable potential to fill the gap between public and individual transport options.

This chapter summarises results from different studies on shared mobility from the providers’, the users’ and the political perspective. The user’s perspective is based on an empirical study comparing car sharers’, car drivers’ and public transport users’ attitudes and mobility patterns.

The empirical findings from the case study have shown that shuttle trips by car in general, and to the train station in particular, are an important field of action for improving the environmental impact of intermodal trips. The study has also shown that car sharing enables people to live without a private car by using different transport modes for different purposes. As the majority of car sharers report needing a car only one to three times a month, they have a very small carbon footprint compared to the average car owner.

Mobility patterns are determined by local transport options as well as by personal routines. Hence, current changes due to new shared mobility options seem to have a considerable direct impact on how people organise their daily lives on the one hand and an indirect impact on their living costs on the other hand, since private cars have an important share of private household costs.

From an environmental perspective, any incentives to encourage people to choose alternative forms of transport over their private cars would seem to be particularly effective. Thus, understanding the behaviour and needs of multi- and intermodal travellers is an important step towards sustainable mobility. Acknowledging that most travellers still need a car every now and then, car sharing is an essential addition to public transport systems, supporting both public transport use and carbon-free mobility like walking and cycling.

The Coronavirus pandemic in South Africa resulted in negative effects with high infection rates, health care shortages, increases in death rates, plus a collapsing economy. There was an urgent need for precautionary health promotional campaigns to educate populations about the virus. However, with South Africa’s diverse population cultural beliefs, socio-cultural aspects needed to be catered for. Health literacy also had to be considered for effective positive behaviour change patterns to occur. Social barriers such as misinformation, stigma, myths, anxiety and prejudice resulted into infodemics emerging in the population. Media representation about the pandemic needed to ensure truthful and authentic information reached target audiences. Specific examples related to religious beliefs (the Chief Justice Mogeng Mogeng) and cultural remedies (Madagascar’s artemisia or “green gold”) are included in this chapter, to elaborate examples of such cases in South Africa, with no audience engagement analysed. Two health promotional campaigns, Count Me In and We will beat this are analysed via a qualitative multimodal analysis. Behaviour change communication theories are included to triangulate and validate the findings. Findings indicated that health campaigns need to cater for socio-cultural diversities and be audience specific in order for adequate behaviour change to occur, via clear health messages.

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.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

The purpose of this paper is to focus on the reference model of a grid-like supply network that enables formulation of delivery routing and scheduling problems in the context of the periodic vehicle routing problem.

The conditions for seamless (collision-free) synchronization of periodically executed local transport processes presented in this paper guarantee cyclic execution of supply processes, thereby preventing traffic flow congestion.

Systems that satisfy this characteristic, cyclic deliveries executed along supply chains are given and what is sought is the number of vehicles needed to operate the local transport processes in order to ensure delivery from and to specific loading/unloading points on given dates. Determination of sufficient conditions guaranteeing the existence of feasible solutions that satisfy these constraints makes it possible to solve the considered class of problems online.

The computer experiments reported in this paper show the possibilities of practical application of the proposed approach in the construction of decision support systems for food supply chain management.

The aim of the present work is to develop a methodology for the synthesis of regularly structured supply networks that would ensure fixed cyclic execution of local transport processes. The proposed methodology, which implements sufficient conditions for the synchronization of local cyclic processes, allows one to develop a method for rapid prototyping of supply processes that satisfies the time windows constraints given.

The aim of the study is threefold: understanding the interconnections amongst visual and verbal multimodal communication strategies used in food discourse; identifying the themes of celebrity chef's food discourse with respect to pro-environmental behaviour; and providing a methodological framework to visually analyse food-themed videos.

This study uses mise-en-scène and critical discourse and multimodal analyses to gain insights on food discourse from 20 videos shared by a Michelin starred chef on social media platforms.

Results show that a pro-environmental cooking philosophy challenges the normative discourse on food and educates general audiences and foodies alike. Mise-en-scène and discourse analyses of Instagram visual content reveal that leftovers are central to the ethical message and are intertwined – through the aesthetic of the videos-with concepts of inclusivity, diversity and nourishment.

Chefs, and restaurants, are encouraged to recognise their responsibility as role models, thus able to influence the societal production of food discourse.

The findings provide new insights into the role of a celebrity chef in promoting sustainable food preparation and consumption.

This chapter focuses on how to leverage public transport infrastructure to produce walk-friendly environments, positioning public transport as a walk-enhancing mode. What are the steps that public transport operators can take to create walk-friendly environments? Do more comfortable waiting conditions result in stronger loyalty from the existing customer base and stronger buyout from new customers? This novel approach stemmed from a partnership with the public transport operator Transdev on a real-life experiment in Grenoble to provide a more comfortable walking and resting experience for public transport users. Named Carrefour de Mobilité (‘the crossroads of mobility’), the experiment prototyped urban design interventions to enhance the access and waiting experience of users engaged in mixed-mode commuting. An ex ante/ex post evaluation was deployed to ascertain whether walk-friendlier environments encourage a more intensive use of public space and easier shifting between public transport modes. The findings show that when users perceive dedicated infrastructure as walk-friendly, they consider it more visible and more attractive, and find it comfortable enough to spend longer waiting times there. The evaluation would have benefited from an extension of the perimeter covered by the sensor technology measuring system which was not feasible because of budget constraints. The experiment reached out beyond the initial target public and captured children and older women as well, providing an amenity which was lacking for these groups and resulting in a livelier and more diverse environment for everyone. This lean and low-cost experiment shows that activating public space near public transport hubs enhances their attractiveness in the eyes of the public transport users.

YouTube allows its users to upload and view videos on its platform. YouTube provides notification to the subscribers whenever a channel uploads a new video thereby making the channel subscribers the potential viewers of the video. And thus, they are the first to come to know about any new offering. But later on, the view count also increases due to virality, that is, mass sharing of the content by the users on different social media platforms similar to word-of-mouth in the field of marketing. Therefore, the purpose of this paper is to examine different diffusion patterns as they can help to inflate traffic and generate revenue.

YouTube's view count grows majorly through virality. The pattern of view count growth has generally been considered unimodal in most of the available research in the field of YouTube. In the present work, the growth process due to views through the subscribers and views due to word-of-mouth (virality) is presented. Considering that the impact of virality in view count growth comes later in the video life cycle; the viewing patterns of both the segments have been mathematically modeled; independently.

Different models have been proposed to capture the view count growth pattern and how the impact of virality changes the view count growth curve and thereby results in a multimodal curve structure. The proposed models have been verified on various view count data sets of YouTube videos using SPSS (Statistical Package for the Social Sciences), and their ranks have been determined using a weighted criteria–based approach. The results obtained clearly depict the presence of many modes in the life cycle of view counts.

Till now, the literature is evident of the video life cycle following a bell shape curve. This study claims that the initial thrust is by subscribers and then the contribution in the view count by people watching via word-of-mouth comes into picture and brings in another hump in the growth curve.