Interaction Design Research Articles

A Recycling and Measurement of Floodwater Using Arduino, Potassium Alum and River Stone

Flood disasters can occur unexpectedly, causing significant damage to homes or office buildings and their contents. Moreover, they pose a serious threat to health, and the recovery process can take 3-7 days. As a result, many flood victims face challenges in accessing clean water for essential needs, which can be especially difficult in urgent situations. There is a pressing need for solutions that can improve and support flood victims. This project aims to address this need by proposing a system for recycling floodwater. It also seeks to highlight the potential usefulness of floodwater for various purposes. The project utilizes the ADDIE model to develop a tool, specifically a smart indicator called ArduPoSt, which utilizes Arduino technology in conjunction with potassium alum and river stone to monitor and enhance the quality of floodwater. The product was tested with two samples, potassium alum with and without river stone, to gauge the accuracy of water turbidity measurement. The results demonstrated thatwater turbidity measurement was more accurate and faster when river stones were included. This product is designed to be flexible and valuable for addressing urgent needs of flood victims. Additionally, there are plans to further enhance its usability through the development of a more interactive design with mobile applications in future iterations.

Implementing social and affective touch to enhance user experience in human-robot interaction.

In this paper, we discuss the potential contribution of affective touch to the user experience and robot performance in human-robot interaction, with an in-depth look into upper-limb prosthesis use as a well-suited example. Research on providing haptic feedback in human-robot interaction has worked to relay discriminative information during functional activities of daily living, like grasping a cup of tea. However, this approach neglects to recognize the affective information our bodies give and receive during social activities of daily living, like shaking hands. The discussion covers the emotional dimensions of affective touch and its role in conveying distinct emotions. In this work, we provide a human needs-centered approach to human-robot interaction design and argue for an equal emphasis to be placed on providing affective haptic feedback channels to meet the social tactile needs and interactions of human agents. We suggest incorporating affective touch to enhance user experience when interacting with and through semi-autonomous systems such as prosthetic limbs, particularly in fostering trust. Real-time analysis of trust as a dynamic phenomenon can pave the way towards adaptive shared autonomy strategies and consequently enhance the acceptance of prosthetic limbs. Here we highlight certain feasibility considerations, emphasizing practical designs and multi-sensory approaches for the effective implementation of affective touch interfaces.

A training and assessment system for human-computer interaction combining fNIRS and eye-tracking data

In the domain of engineering interactive product design, the optimization of Human-Computer Interaction (HCI) is central to enhancing user experience and system efficiency. Notably, the application of cognitive load theory holds significant prominence in this field. Efficient evaluation of cognitive load not only facilitates the optimization of resource management and task allocation, but is also the key to creating a fluent interactive experience. With the advancement of Artificial Intelligence (AI) and physiological measurement technologies, new methodologies have emerged to measure and understand cognitive load. This research introduces a system for HCI training and assessment. The system, through the development of digital memory paradigms, induces and verifies varying levels of cognitive load with precision, thereby providing data-driven insights for HCI design. Specifically, this study constructs an AI-assisted multimodal cognitive load assessment framework, integrating physiological data collected from Functional Near-Infrared Spectroscopy (fNIRS) and eye-tracking technologies. By extracting and analyzing 29 physiological features, including channel features, graph-theoretic features, and features pertaining to eyelid and iris movements, we propose an innovative multimodal recognition approach to classify cognitive load across individuals. The experimental results not only verified the validity of the method, but also revealed changes in physiological patterns at different levels of cognitive load. In particular, the significant potential of the fNIRS feature in band I. This discovery suggests that we can monitor and predict cognitive load with greater precision through physiological signals, hence optimizing the design of HCI systems to alleviate user strain, prevent information overload, and enhance the naturalness and intuitiveness of interaction.

Enhancing Reflective and Conversational User Engagement in Argumentative Dialogues with Virtual Agents

In their process of information seeking, human users tend to selectively ignore information that contradicts their pre-existing beliefs or opinions. These so-called “self-imposed filter bubbles” (SFBs) pose a significant challenge for argumentative conversational agents aiming to facilitate critical, unbiased opinion formation on controversial topics. With the ultimate goal of developing a system that helps users break their self-imposed filter bubbles (SFBs), this paper aims to investigate the role of co-speech gestures, specifically examining how these gestures significantly contribute to achieving this objective. This paper extends current research by examining methods to engage users in cooperative discussions with a virtual human-like agent, encouraging a deep reflection on arguments to disrupt SFBs. Specifically, we investigate the agent’s non-verbal behavior in the form of co-speech gestures. We analyze whether co-speech gestures, depending on the conveyed information, enhance motivation, and thus conversational user engagement, thereby encouraging users to consider information that could potentially disrupt their SFBs. The findings of a laboratory study with 56 participants highlight the importance of non-verbal agent behaviors, such as co-speech gestures, in improving users’ perceptions of the interaction and the conveyed content. This effect is particularly notable when the content aims to challenge the user’s SFB. Therefore, this research offers valuable insights into enhancing user engagement in the design of multimodal interactions with future cooperative argumentative virtual agents.

VoiceBack: Design of Artificial Intelligence-Driven Voice-Based Feedback System for Customer-Agency Communication in Online Travel Services

Online travel booking has become increasingly popular; however, most travel websites do not yet offer voice interaction. This study introduces VoiceBack, an artificial intelligence (AI)-driven voice-based feedback system conceptualized to support both customers and online travel agencies during the booking process. It proposes a theoretically and empirically underpinned design concept that involves a voice user interface (VUI) for customer feedback. This feedback, collected by an AI agent, is analyzed and converted into actionable statistics, which are then presented to online travel agencies through a visual interface. The interface is designed to highlight problem areas and usability issues during the booking process. This study contributes to the field of human-centered AI, by offering insight into the complex process of designing and integrating voice, emotion, and feedback within user interfaces. This integrated approach can enrich the user experience of customers when booking travel online, and pave the way for more intuitive and responsive interaction designs in the future.

Rancang Bangun Aplikasi Edukasi Interaktif Untuk Jogging Berbasis Android

The design of an interactive educational application for jogging based on Android, is an application created to make it easier for people to know about the definition of jogging and the health benefits of jogging, this application was created with a smart apps creator and the Canva application which aims to make it easier for writers to create educational applications This interactive, the final result of this interactive educational application design project will use mobile device media, namely Android-based. The author raised this title because the author saw a lack of public awareness about exercising, especially jogging, therefore the author took the initiative to raise the title of creating this interactive educational application so that people know the importance of jogging.

Enhancing User Perception of Reliability in Computer Vision: Uncertainty Visualization for Probability Distributions

Non-expert users often find it challenging to perceive the reliability of computer vision systems accurately. In human–computer decision-making applications, users’ perceptions of system reliability may deviate from the probabilistic characteristics. Intuitive visualization of system recognition results within probability distributions can serve to enhance interpretability and support cognitive processes. Different visualization formats may impact users’ reliability perceptions and cognitive abilities. This study first compared the mapping relationship between users’ perceived values of system recognition results and the actual probabilistic characteristics of the distribution when using density strips, violin plots, and error bars to visualize normal distributions. The findings indicate that when density strips are used for visualization, users’ perceptions align most closely with the probabilistic integrals, exhibiting the shortest response times and highest cognitive arousal. However, users’ perceptions often exceed the actual probability density, with an average coefficient of 2.53 times, unaffected by the form of uncertainty visualization. Conversely, this perceptual bias did not appear in triangular distributions and remained consistent across symmetric and asymmetric distributions. The results of this study contribute to a better understanding of user reliability perception for interaction designers, helping to improve uncertainty visualization and thereby mitigate perceptual biases and potential trust risks.

Unpacking Human-AI interactions: From Interaction Primitives to a Design Space

This article aims to develop a semi-formal representation for Human-AI (HAI) interactions, by building a set of interaction primitives which can specify the information exchanges between users and AI systems during their interaction. We show how these primitives can be combined into a set of interaction patterns which can capture common interactions between humans and AI/ML models. The motivation behind this is twofold: firstly, to provide a compact generalization of existing practices for the design and implementation of HAI interactions; and secondly, to support the creation of new interactions by extending the design space of HAI interactions. Taking into consideration frameworks, guidelines, and taxonomies related to human-centered design and implementation of AI systems, we define a vocabulary for describing information exchanges based on the model’s characteristics and interactional capabilities. Based on this vocabulary, a message passing model for interactions between humans and models is presented, which we demonstrate can account for existing HAI interaction systems and approaches. Finally, we build this into design patterns which can describe common interactions between users and models, and we discuss how this approach can be used toward a design space for HAI interactions that creates new possibilities for designs as well as keeping track of implementation issues and concerns.

Application of intelligent internet of things and interaction design in Museum Tour

The rapid development of information technology and the continuous improvement of human spiritual and cultural level have made people's acquisition of knowledge and information increasingly urgent. The information transmission method of traditional navigation systems is single and passive. This study aims to improve user experience and enhance the interactivity of museum visits. This article combines interactive technology in the Internet of Things to conduct in-depth research on the tour guide system in museums. By utilizing IoT technology, optimize the interaction design of the intelligent navigation system, and enhance the convenience and experience of visitors. In the experimental analysis, this article compared the main ticket purchasing methods of tourists, the level of understanding of museum staff about the collection, the amount of information obtained by tourists, and the satisfaction of tourists. The comparison results show that the proportion of electronic ticket purchases has increased by 35 % in terms of ticket purchasing methods. The staff's understanding of the collection has increased by 19 %, the amount of information received by tourists has increased by 12.7 %, and tourist satisfaction has also increased by 24.3 %. The conclusion indicates that the interactive design navigation system based on intelligent Internet of Things and interactive design can effectively meet the needs of different users and provide the public with a richer and deeper cultural experience.

A frequency selection network for medical image segmentation

Existing medical image segmentation methods may only consider feature extraction and information processing in spatial domain, or lack the design of interaction between frequency information and spatial information, or ignore the semantic gaps between shallow and deep features, and lead to inaccurate segmentation results. Therefore, in this paper, we propose a novel frequency selection segmentation network (FSSN), which achieves more accurate lesion segmentation by fusing local spatial features and global frequency information, better design of feature interactions, and suppressing low correlation frequency components for mitigating semantic gaps. Firstly, we propose a global-local feature aggregation module (GLAM) to simultaneously capture multi-scale local features in the spatial domain and exploits global frequency information in the frequency domain, and achieves complementary fusion of local details features and global frequency information. Secondly, we propose a feature filter module (FFM) to mitigate semantic gaps when we conduct cross-level features fusion, and makes FSSN discriminatively determine which frequency information should be preserved for accurate lesion segmentation. Finally, in order to make better use of local information, especially the boundary of lesion region, we employ deformable convolution (DC) to extract pertinent features in the local range, and makes our FSSN can focus on relevant image contents better. Extensive experiments on two public benchmark datasets show that compared with representative medical image segmentation methods, our FSSN can obtain more accurate lesion segmentation results in terms of both objective evaluation indicators and subjective visual effects with fewer parameters and lower computational complexity.

THE IMPORTANCE OF MODELING CLUSTER COOPERATION RELATIONS IN CONTINUOUS EDUCATION

This article describes the dynamic landscape of continuous education increasingly necessitates innovative approaches to enhance collaboration and effectiveness among educational institutions and stakeholders. This paper explores the significance of modeling cluster cooperation relations as a strategy to optimize the functioning and impact of educational clusters. Clusters, defined as networks of interconnected institutions and organizations, are pivotal in fostering collaborative practices that support ongoing professional development, resource sharing, and innovative pedagogical practices. Modeling cluster cooperation relations involves the systematic analysis and design of interactions and relationships within educational clusters to promote synergy and achieve shared goals. This study highlights how structured collaboration models can address challenges such as resource allocation, curriculum alignment, and quality assurance. By employing case studies and theoretical frameworks, the paper demonstrates thateffective cluster cooperation can lead to improved educational outcomes, enhanced professional development opportunities, and greater institutional resilience.

Application of Artificial Intelligence in the Design of 2D Escape From Pirates Game with A Star Algorithm Search Method

This research is designed to provide a challenging gaming experience by integrating strategy and problem-solving elements. The A* algorithm was chosen due to its efficient ability to find the shortest path in a complex search space. The implementation of this algorithm allows the main character to dynamically avoid obstacles and pirate threats and reach the destination in an optimal way. The test results show that the A* algorithm not only improves game performance but also provides a more realistic and challenging experience for the player. For testing this application, using obstacles and measured based on the value of nodes on the game map. Based on the test results, the A Star algorithm was successfully applied when comparing the computations in the game and manual calculations in the Escape from Pirates game in the test. Thus, this research contributes to the development of artificial intelligence-based games and opens opportunities for further innovation in interactive game design.

Designing visual hierarchies for the communication of health data.

Visual hierarchy underlies all visual design decisions related to information presentation. This manuscript describes the experience of a multidisciplinary health data visualization and software design team in using visual hierarchy to redesign a hereditary colorectal cancer lab report. A series of interviews with representative users were conducted to identify target user groups and determine information hierarchy for each user type. Visual elements (eg, size, color, contrast, etc.) were then assigned to mirror the information hierarchy and workflow for each user type. User research identified 2 distinct user groups as consumers of the redesigned lab report. An interactive design employing a 2-level page hierarchy was developed, which stratified the content to support the needs of each user type. The challenges related to displaying the complex nature of digital and personal health data can be addressed by applying foundational design methods such as visual hierarchy. Visual hierarchy, a foundational design principle, can be used by visualization teams to clearly and efficiently present complex datasets associated with healthcare.

Study on the Communication Strategy of Macao Music CultureTaking the Interaction Design of City Walk as an Example

As a city where East meets West, Macau has a rich historical and cultural heritage, and its music culture, based on its historical background, has a long history of development, with colourful and diverse genres. However, as a tourist city, the publics understanding of Macau is basically confined to the gaming industry. The dissemination of its music is faced with the problems of small scope of dissemination and lack of popularity, etc. Therefore, how to better inherit and protect the music culture of Macau? Therefore, how to better pass on and protect Macaus local culture has become an issue of wide concern to the Macau society nowadays. With the development of the Internet and the changing needs of the public, interactive design came into being, the interactivity of this design can provide a better user experience and increase the attractiveness of the project. As a popular way of travelling nowadays, city walking can make the public feel the city culture better. This design study will conduct fieldwork research on Macaos music culture through fieldwork method, literature research method and data collection method, analyse the form of its integration with urban micro-tourism, and finally design it interactively. In this way, the dissemination of Macaus music culture will be increased and the cultural participation of the public will be strengthened. In addition, the form of city walk can attract tourists of all ages, which is a good guide for the dissemination of Macaus music culture. Moreover, this design can provide the public with a vivid understanding of Macaus music culture, enhance Macaus cultural attractiveness, promote socialisation and interaction in the city, and improve the publics physical and mental health and quality of life. Therefore, this study aims to provide methodological ideas for the communication strategy of Macaus music culture and to provide innovative perspectives for the inheritance of Macaus excellent traditional culture.

Can GPT Help Improve Robo-advisory? The Construction of Robo-advisor for Users with Low Investment Experience Based on LLM

Robo-advisors have emerged as a significant innovation in investment management, offering automated financial advice to investors. However, user acceptance remains a challenge, particularly among those with limited investment experience. This paper explores the potential of large language models (LLMs) to enhance the interaction attributes of robo-advisor products and increase acceptance among novice investors. The study contributes to the existing literature by exploring the application of LLMs in robo-advisors, supplementing the exploration of interaction design, and systematically reviewing the service processes of current robo-advisor products. Findings suggest that existing robo-advisor products have room for improvement in interaction attributes and algorithmic mechanisms. Through theoretical exploration, this paper proposes methods for optimizing robo-advisor products by integrating LLMs. In conclusion, this research lays the groundwork for designing robo-advisor products with integrated LLM functionality, offering theoretical references for practitioners and researchers in financial technology. Future research directions include exploring user expectations and conducting controlled experiments to analyze the impact of LLM integration on user decisions.

Research on Information Fusion Method for Human Computer Interaction Interface of Command and Control System in MR Environment

In response to the challenge of high cognitive pressure and difficulty for commanders in cross-layer operations during the transition from traditional two-dimensional command and control system interfaces to mixed reality human-computer interaction interfaces, this paper conducts research on the information fusion display method for the human-computer interaction interface of the mixed reality command and control system. First, based on the findings of previous research, we developed a five-layer human-computer interaction interface for a mixed reality command and control system in typical combat scenarios. An evaluation experiment was designed and the resulting data analyzed. This analysis revealed that there are problems with low work efficiency and high cognitive load in the information acquisition process in cross-layer interaction operations. Consequently, we conducted research into the methods of integrating and displaying interactive interface information, integrating and displaying interactive and display interface information, and integrating and displaying complex situation interface information. The research findings indicate that: (1) The optimal display ratio for mixed reality 2D interface integration is 3:2. (2) The optimal display scheme for mixed reality 2D interface fusion is a combination of the main and secondary interfaces, with the main interface table displaying global information and the secondary interface displaying accurate information. (3) The optimal display scheme for mixed reality 2D and 3D interface fusion is the display of overall class information in 2D and the accurate identification of class information in 3D. The findings of this research can be applied to the design of human-computer interaction interfaces for mixed reality command and control systems in complex battlefield environments.

Application of artificial intelligence in turbomachinery aerodynamics: progresses and challenges

Turbomachinery plays a vital role in energy conversion systems, with aerodynamic issues being integral to its entire lifecycle, spanning the period of design, validation, and maintenance. Conventionally, the reliance on skilled aerodynamic engineers has been pivotal in the successful development of turbomachines. However, in the current era of burgeoning artificial intelligence (AI) technology, researchers are increasingly turning to AI to replace human expertise and decision-making in these aerodynamic issues and to solve previously intractable aerodynamic problems. This paper presents a systematic literature review of the latest advancements in applying AI to turbomachinery aerodynamics, encompassing the design, validation, and maintenance of compressors and turbines. It underscores how AI is revolutionizing the research paradigm of turbomachinery aerodynamics. AI’s powerful learning capability facilitates more precise and convenient aerodynamic analyses and inspires innovative aerodynamic design ideas that go beyond the capabilities of classical design techniques. Additionally, AI’s autonomous decision-making capability can be employed for aerodynamic optimization and active flow control of turbomachines, generating optimal aerodynamic solutions and complex control strategies that surpass human brains. As a main contribution, we provide a detailed exposition of the future intelligent turbomachinery research and development (R &D) system, along with highlighting potential challenges such as physics embedding, interactive 3D design optimization, and real-time prognoses. It is anticipated that harnessing AI’s full potential will lead to a comprehensive AI-based turbomachinery R &D system in the future.

Application of Interactive Object Model in Sports Teaching

Traditional physical education is just repeated training without quantitative teaching and training data results. Multimedia information analysis and retrieval technology can make repeated research on the content of competition or training, and increase the quantitative analysis of training indicators. Therefore, this paper proposes an interactive compressed domain key video object model to realize the design and production of physical education video, so as to quantify the effect of physical education. This paper discusses the interactive design and application of PE teaching video from three aspects: static, dynamic, and semantic. The interactive object model proposed in this paper can formulate corresponding strategies for different key sports video objects. The distortion rate of the complete key video object is 2.3%, which is 0.09% lower than the distortion rate of the Kim2002 scheme. From a usage perspective, through the scheme proposed in this article, coaches can obtain teaching videos with simple initial extreme values on an interactive interface, and the distortion rate of the video object is lower than that of traditional schemes.

Green landscape 3D reconstruction and VR interactive art design experience using digital entertainment technology and entertainment gesture robots

With the rapid development of digital entertainment technology, people’s demand for green landscape reconstruction and virtual reality (VR) interactive art design is increasing. This study aims to explore the use of digital entertainment technology and entertainment gesture robots, combined with green landscape 3D reconstruction and VR interactive art design, to provide a new art experience. This paper uses digital entertainment technology to reconstruct the green landscape in 3D, and combines the interactive function of entertainment gesture robot to enable users to interact with the virtual environment. Then VR technology is used to present the reconstructed landscape to the user, and through immersive experience, users can feel the immersive art design. Through experimental evaluation and user survey, 3D reconstruction of green landscape and VR interactive art design using digital entertainment technology and entertainment gesture robots can provide a new entertainment experience. Users are more satisfied with the immersive art design expression, and experience the interaction and connection with the natural environment, which provides users with a unique and immersive art experience, further enriching the form and content of digital entertainment.

Data-driven personas creation based on the CHARLS database: analyzing the interaction design of mobility aid for the Chinese elderly with difficulty in indoor transferring

Data-driven personas creation based on the CHARLS database: analyzing the interaction design of mobility aid for the Chinese elderly with difficulty in indoor transferring