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Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Spatial olfactory design in the library appears to be a practical approach to enhance the coordination between architectural spaces and user behaviors, shape immersive activity experiences and shape immersive activity experiences. Therefore, this study aims to explore the association between the olfactory elements of library space and users’ olfactory perception, providing a foundation for the practical design of olfactory space in libraries.

Using the olfactory perception semantic differential experiment method, this study collected feedback on the emotional experience of olfactory stimuli from 56 participants in an academic library. From the perspective of environmental psychology, the dimensions of pleasure, control and arousal of users’ olfactory perception in the academic library environment were semantically and emotionally described. In addition, the impact of fatigue state on users’ olfactory perception was analyzed through statistical methods to explore the impact path of individual physical differences on olfactory perception.

It was found that users’ olfactory perception in the academic library environment is likely semantically described from the dimensions of pleasure, arousal and control. These dimensions mutually influence users’ satisfaction with olfactory elements. Moreover, there is a close correlation between pleasure and satisfaction. In addition, fatigue states may impact users’ olfactory perception. Furthermore, users in a high-fatigue state may be more sensitive to the arousal of olfactory perception.

This article is an empirical exploration of users’ perception of the environmental odors in libraries. The experimental results of this paper may have practical implications for the construction of olfactory space in academic libraries.

Tourism via virtual reality (VR) technology has become an interesting option for consumers to “travel.” The best approaches to optimizing the VR tourism environment, improving the interactive experience of tourists and encouraging tourists to adopt VR are not yet fully understood. This study explores the willingness of tourists to adopt VR tourism from the dual aspects, richness and dynamics, of virtual social cues.

To examine the effects of richness (multiple vs. few cues) and dynamic (changeable vs. static cues) on consumers' willingness to adopt VR tourism, three virtual tourism scenes were designed and presented by head-mounted displays. The data were collected for participants in the VR laboratory and tested by ANOVA and partial least squares–structural equation modeling.

Virtual social cues can generate mental imagery through interactivity, vividness and parasocial interactions, thus increasing the consumer's likelihood of adopting VR tourism. It was also found that imagination moderates mental imagery and adoption intention. When the consumer's imagination is stronger, their mental imagery stimulates a stronger willingness to adopt VR tourism.

The authors innovatively utilize concepts of parasocial interaction and mental imagery and discuss the various influences and mediation mechanisms of social cue characteristics on consumers' adoption of VR tourism. The conclusions may provide new insights for VR tourism managers and tourism scholars.

This study aims to investigate the effect of virtual reality experience quality on destination visit intention and virtual reality travel intention through the technology acceptance model (TAM).

Quantitative data gathered from questionnaires applied to 198 people after undertaking an imaginary three-dimensional (3D) destination experience were analyzed with PLS-SEM.

Virtual reality experience quality influences perceptions and intentions. The perceived ease of use affects perceived usefulness, perceived usefulness effects attitude and destination visit intention, while perceived risk affects only virtual reality travel intention. Attitude affects both intentions.

The main limitation of the study relates to the quality of the experience offered, which is limited to the technical capacity of the virtual reality glasses used. Virtual reality can be used as a new economic offering and create a realistic destination experience. Virtual reality experience quality is an important determinant of intention in physical and imaginary travels, in shaping perceptions and minimizing travel risks. The explanatory power of the model can be increased by adding the perceived risk variable to TAM. The study has brought new perspectives, new insights and suggestions for developing tourism.

In the study, a 3D imaginary destination with its mise-en-scène and story, which includes more than one destination type, was designed. This study contributes to the literature by analyzing real and virtual visit intentions, combining the fields of the experience economy, risk perception and TAM.

本研究通过应用技术接受模型, 探讨虚拟现实体验质量对目的地参访意愿和虚拟现实旅游意愿的影响。旨在识别这些变量之间存在的关系, 并解释这些关系的因果链接。

本研究从198名参与虚拟三维目的地体验后填写的问卷中获得定量数据并通过PLS-SEM方法进行分析。

虚拟现实体验的质量影响用户的感知和意愿。虚拟现实旅游意愿仅受感知风险的影响。感知易用性影响感知有用性。意愿受态度影响, 但感知有用性不影响虚拟现实旅游。

本研究的主要局限性与提供的体验质量有关, 该质量受到虚拟现实眼镜技术能力的限制。虚拟现实可以作为一种新的经济提供方式进行开发。通过将感知风险变量添加到技术接受模型中, 可以增加模型的解释力。本研究为旅游业的发展提供了新的视角、见解和建议, 并解释了虚拟现实提供的真实目的地体。

为了研究的目的, 本研究设计了一个虚拟的三维目的地, 包含多个目的地类型。该目的地有自己的布景和故事情节。本研究通过分析真实和虚拟参访意愿的领域, 将体验经济、风险感知和技术接受模型领域相结合, 为文献做出了贡献。

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

In order to encourage customers to try experience virtual tourism, researchers and practitioners pay more attention on how to improve customers' perception of authenticity.

Using the theory of cross-sensory compensation, through 4 experiments, this study examines the impact of social interaction and cross-sensory strategies on the relationship between virtual reality (VR) and improving customers' perception of authenticity and customer experience.

Through experimental research, this paper finds that (1) VR immersion has a significant positive impact on perception of authenticity, which in turn acts on customers' virtual tourism experience. (2) In addition, social interaction strengthens the relationship between VR immersion and customers' perception of authenticity. (3) The cross-sensory compensation has a positive effect on VR immersion to enhance customers' perception of authenticity.

The research conclusion provides a direction for further discussion on how to improve customers' perception of authenticity and provides theoretical guidance and reference for the virtual tourism industry.

The goal of the study is to underline “Cinematic Architecture” as another source of architectural thinking and research. This study is also a response to the shortage in empirical research on architecture in the cinema. Moreover, the study introduces the architectural components that qualify the cinematic spaces to be influential cinematic experience. This is in addition to investigating the impact of these components on the viewers' cognitive and emotional experience of films.

In the reported study, an empirical experiment examined scenes from three different movies as experienced by a selected group of audience of movies fans (architects and laypersons). The audience was asked to report feelings the audience had about each scene using a questionnaire that was designed for this purpose, and the audience was asked to write down the aspects that affected the audience's emotions. The experiment evaluated selected emotional states and could specify the architectural features and/or objects that significantly contributed in inducing these emotions.

This study's findings concluded that emotions, which exist in the positive margin of the emotions “circumplex model,” were influenced by architectural components that were different from those that influenced emotions which lie in the negative margin of the model.

As for filmmakers, the study contributes in developing filmmakers' knowledge about the role of architecture in scenic creation and thus how that knowledge enhances filmmakers' film narrative and the narrative's spatial imagery. As for academia, this study contributes in developing the knowledge about film cognition as related to architectural semiotics. In the context of behavioral approach to architectural design, a behavior setting which is the basic element in environmental design can be dramatized by applying a cinematic narrative to a human activity system within a milieu of architectural design elements.

This study is important for architects, as the study provides architects with an alternative tool for fictional experience and for testing architectural ideas through cinematic architecture. This study also helps in developing new venues for the practice of architecture into the world of fiction. This study also contributes in developing the trend that architectural design thinking can learn from cinematic thinking and practice.

This study introduces an empirical approach to evaluate architectural entities as part of cinematic experience. This study also comes as a response to the shortage in empirical research on architecture in the cinema.

While the main emotional labor strategies are well-documented, the manner in which professionals navigate emotional rules within the workplace and effectively perform emotional labor is less understood. With this contribution, I aim to unveil “the good, the bad and the ugly” of emotional labor as a dynamic theatrical performance.

Focusing on three geriatric long-term care units within a French public hospital, this qualitative study relies on two sets of data (observation and interviews). Deeply rooted within the field of study, the chosen methodological approach substantializes the subtle hues of the emotional experience at work and targets resonance rather than generalization.

Using the theatrical metaphor, this research underlines the role of space in the practice of emotional labor in a unique way. It identifies the main emotionalized zones or emotional regions (front, back, transitional, mixed) and details their characteristics, before unearthing the nonlinearity and polyphonic quality of emotional labor performance and the versatility needed to that effect. Indeed, this research shows how health-care professionals juggle with the specificities of each region, as well as how space generates both constraints and resources. By combining static and dynamic prisms, diverse instantiations of hybridity and spatial in-betweens, anchored in liminality and trajectories, are revealed.

This research adds to the current body of literature on the concept of emotional labor by shedding light on its highly dynamic and interactional nature, revealing different levels of porosity between emotional regions and how the characteristics of each type of area can taint others and increase/decrease the occupational health costs of emotional labor. The study also raises questions about the interplay of emotional labor performance with the level of humanization/dehumanization of elderly people. Given the global demographics about an aging population, this gives food for thought at a social level.

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.