Interactive User Experience Research Articles

Emotional dialogue generation model of electronic commerce intelligent customer service based on topic expansion

Current electronic commerce (e-commerce) customer service systems often rely on retrieval-based methods, resulting in impersonal and emotionally flat responses. These systems struggle to handle diverse expressions and emotional nuances in user queries, leading to poor user experience. In this paper, we applied artificial intelligence techniques, notably the Gated Recurrent Unit model, to generate emotionally resonant dialogues in e-commerce customer service systems. We integrate intent recognition, emotion recognition, and topic expansion for accurate intent identification and nuanced responses. The model is trained on a customer service dataset from Jing Dong, a leading Chinese e-commerce platform. Through extensive experiments, we conducted comparative analyses against benchmark model Gated Recurrent Unit neural network. The results demonstrate that our model significantly outperforms existing approaches, achieving fluency, rationality, and emotionality scores of 62%, 58% and 61% respectively. These findings indicate that our approach generates responses with greater consistency to user intent and richer emotional content. The significance of these results lies in their potential to enhance user experience in e-commerce customer service interactions by providing more personalized and emotionally resonant automated responses.

Design and implementation of a multifunctional desktop robot for computer peripherals

Abstract As an important component of the intelligent machinery field, desktop robots not only enrich people’s entertainment lives but are also gradually expanding into applications in education, healthcare, and other fields. However, existing products often struggle to meet the increasingly diverse needs due to short battery life and limited computing resources. In response to this challenge, this study designs a multifunctional desktop robot that can be used as a computer peripheral, which significantly improves power supply and computing capabilities. The design uses the STM32F4 series microcontroller as the main control chip, combined with high-performance servos and their self-developed driver boards, to achieve precise motion control. By integrating USB-HS PHY and USB-CDC protocol, the communication efficiency with the computer is greatly improved, and new screen-driving technology is developed using open-source routines, thus optimizing the user interaction experience. In addition, an innovative adaptive algorithm is incorporated into the firmware program, enhancing the robot’s working stability in different environments. Through systematic hardware debugging and software testing, the robot can achieve efficient performance and stable response when executing complex tasks. This research will promote the expansion of desktop robot technology into broader application fields and support future intelligent work and lifestyle.

Human body features recognition based adaptive user interface for extra-large touch screens

With the widespread use of extra-large touch screens (eLTS) in various settings such as work and education, interaction efficiency and user experience have garnered increased attention. The current user interface (UI) layouts of eLTS are primarily categorized into two modes: fixed position and manual adjustment. The fixed UI layout fails to accommodate users of different heights and sizes, while the manual adjustment mode involves cumbersome steps and lacks sufficient flexibility. This study proposes an adaptive UI for eLTS. The optimal operational area on the eLTS is determined based on users’ height, eye level, arm length, face orientation, and distance from the screen. The eLTS menu is then positioned and displayed within this optimal area. Simulations involving users of various heights (P1 female, P50 male and female, and P99 male) were conducted to evaluate fatigue using the rapid upper limb assessment (RULA) method. The results indicate that the proposed adaptive UI significantly reduces user fatigue.

Pengelolaan Cache pada Aplikasi Pencatatan Penjualan Menggunakan Fuzzy Page Replacement Algorithm

The challenges faced in website development are becoming increasingly diverse, particularly in delivering a responsive website that aligns with user preferences. Progressive Web App (PWA) is an advanced web technology that combines the advantages of mobile applications with the ease of access provided by browsers. With features such as offline access and responsiveness across various devices through the utilization of web caching, PWA can offer a better and more interactive user experience. This study aims to develop a sales recording application based on PWA, optimized using an algorithm with a fuzzy approach, namely the Fuzzy Page Replacement Algorithm (FPRA) in cache management. FPRA is applied to enhance cache efficiency through the clustering of pages based on recency, access frequency, and page reference levels using the Fuzzy C-Means algorithm. The research was conducted with a case study on the sales recording application for a fried chicken business, employing the Rapid Application Development (RAD) method for the design and construction of the application. The results indicate that FPRA successfully reduced page load time significantly, achieving up to 37% faster performance based on the average results of five tested scenarios. The implementation of FPRA in the service worker also increased the average performance score of the application by 15 points, from 56 to 71, as evaluated using the Lighthouse testing tool. Thus, the utilization of caching and the application of FPRA in cache management have been proven to enhance application performance.

Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges.

A large language model (LLM) is an artificial intelligence (AI) model that uses natural language processing (NLP) to understand, interpret, and generate human-like language responses from unstructured text input. Its real-time response capabilities and eloquent dialogue enhance the interactive user experience in human-AI communication like never before. By gathering several sources on the internet, LLM chatbots can interact and respond to a wide range of queries, including problem solving, text summarization, and creating informative notes. Since ophthalmology is one of the medical fields integrating image analysis, telemedicine, AI, and other technologies, LLMs are likely to play an important role in eye care in the near future. This review summarizes the performance and potential applicability of LLMs in ophthalmology according to currently available publications.

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.

Legal Liaison

The Legal Liaison system is an innovative web-based application designed to transform the landscape of legal practice and management. By incorporating essential functionalities for various stakeholders including clients, advocates, law students, junior advocates, and administrative staff, this system significantly enhances the efficiency and effectiveness of legal services. This application facilitates easy interaction and management for users by providing a centralized platform for all legal activities. It supports client engagement, advocate-client communication, case management, and administrative oversight, ensuring a streamlined workflow for legal professionals. Additionally, it promotes the professional development of emerging legal talents through structured mentorship and resource sharing. By leveraging modern technology, the Legal Liaison system aims to simplify complex legal processes, foster better collaboration, and improve resource utilization, ultimately providing a more accessible and efficient legal service environment. This holistic approach ensures that all participants in the legal ecosystem can benefit from enhanced coordination and optimized legal practices The front end of the Legal Liaison system is built using React.js, ensuring a responsive and interactive user experience. The backend employs Express.js and Node.js to create a robust and scalable server-side environment. MongoDB acts as the database, offering flexible and scalable data storage. Combined, these technologies form a seamless and efficient platform for contemporary legal practice

Adaptive Chatbots: Real-Time Sentiment Analysis for Customer Support

In the era of digital transformation and increasing online interactions, customer support is a critical aspect of business success. This paper investigates the development of adaptive customer support chatbots that use real-time sentiment analysis to generate contextually appropriate responses. By leveraging advanced sentiment detection techniques, the system aims to enhance user interaction, satisfaction, and overall customer service experience. This innovation is particularly relevant in today's fast-paced, digitally connected world where personalized and empathetic customer service can significantly impact brand loyalty and customer retention. The proposed approach addresses the growing demand for more intelligent and emotionally aware chatbots, aligning with current trends in artificial intelligence and consumer expectations.

Exploring the impact of HCI on smart buildings: A comprehensive literature review on user experience and sustainability

This paper provides insights into the application of human-computer interaction (HCI) principles in the field of smart building design, particularly their impact on improving occupant comfort, building energy efficiency, and the user interaction experience. The research context focuses on advances in HCI and the importance of smart buildings in enhancing quality of life and sustainability. The research theme focuses on how HCI principles can be utilized to improve the user interface design of smart buildings in order to promote more effective user-building system interactions. Through an extensive review of existing literature in the area of HCI and smart buildings, including recent research papers, case study reports, and technical overviews, this study concentrates on analyzing examples of HCI applications in smart lighting, temperature control systems, and energy management. Through this comprehensive literature review, this paper aims to illustrate how HCI principles can provide theoretical and practical guidance for the design of more humanized, interactive and environmentally friendly smart buildings, thereby providing insights and recommendations for future smart building design and research.

Enhancing emotional expression in cat-like robots: strategies for utilizing tail movements with human-like gazes.

In recent years, there has been a significant growth in research on emotion expression in the field of human-robot interaction. In the process of human-robot interaction, the effect of the robot's emotional expression determines the user's experience and acceptance. Gaze is widely accepted as an important media to express emotions in human-human interaction. But it has been found that users have difficulty in effectively recognizing emotions such as happiness and anger expressed by animaloid robots that use eye contact individually. In addition, in real interaction, effective nonverbal expression includes not only eye contact but also physical expression. However, current animaloid social robots consider human-like eyes as the main emotion expression pathway, which results in a dysfunctional robot appearance and behavioral approach, affecting the quality of emotional expression. Based on retaining the effectiveness of eyes for emotional communication, we added a mechanical tail as a physical expression to enhance the robot's emotional expression in concert with the eyes. The results show that the collaboration between the mechanical tail and the bionic eye enhances emotional expression in all four emotions. Further more, we found that the mechanical tail can enhance the expression of specific emotions with different parameters. The above study is conducive to enhancing the robot's emotional expression ability in human-robot interaction and improving the user's interaction experience.

Design of Human–Computer Interaction Gesture Recognition System Based on a Flexible Biosensor

The continuous development of high-speed Internet technology has made the application of robots increasingly widespread. Current robots and human–computer interaction systems mostly use rigid materials, such as metals and semiconductors, which have limitations in terms of deformability and flexibility. In addition, the biocompatibility and user comfort of these materials are also an issue. Therefore, research into new flexible biosensors is essential to improve the flexibility, comfort, and interactivity of these systems. This research will select polymer hydrogel as the electrode material of the sensor and polydimethylsiloxane as the base material of the sensor to design a resistance flexible biosensor to solve the poor flexibility. The research will use a template-matching method to verify the feasibility of gesture recognition of the flexible sensor. The remote control system of the robot finger is designed by a proportional-integral differential controller tuned by aradial basis function neural network. The feasibility of the research system is verified by simulation and scene experiments. The flexible sensor studied and prepared had a sensitivity of 0.7269, a tensile limit of 300%, and a thickness of 0.16 mm, showing good sensitivity and stability. The recognition accuracy of the sensor designed in the study was 92.8%, which was 8.1% higher than that of the data glove. Compared with traditional proportional-integral derivative (PID) controllers, the improved controller system error was within 10 to 3 rad, which had better adaptability and stability. Key information includes the design method of the flexible biosensor, its high sensitivity and stability under multiple stretches, and the proposal and validation of a new RBFNN–PID control model. These results showed that using this new sensor and control model significantly improved the control accuracy of mechanical fingers and the effect of gesture recognition. These results have important implications for the development of more advanced human–computer interaction systems. They not only improve the performance and reliability of the system, but also improve the user's interactive experience. These technologies are particularly promising in the fields of prosthetics for disabled people, advanced game controllers, and remotely controlled robots operating in hazardous environments. The research results are expected to lead to the development of advanced prosthetics, augmented reality devices, advanced game controllers, and automated robots. The main contribution of the research is to design a resistive flexible biosensor, which improves the traditional sensor's poor flexibility and large size and improves the sensor's ability to sense small changes. Future research may focus on further improving the sensor's long-term stability and performance under a variety of environmental conditions. In addition, commercializing these technologies and making them universal is also an important direction for the future.

서비스형 버추얼 휴먼의 감성적 디자인 분석 및 UX평가

As the digitization of museums accelerates, service-oriented virtual humans are leading the museum industry's entry into the metaverse. However, compared to other countries, the application of service-oriented virtual humans in Chinese museums is still in its early stages. This study explores ways to enhance the user experience of service-oriented virtual humans in museums through emotional design and UX evaluation. Firstly, the study identifies emotional design elements and UX evaluation factors through prior research. Secondly, it discusses seven elements—visual, auditory, storytelling, interaction, pleasure, satisfaction, and convenience—across the three levels of emotional design(instinctive, behavioral, and reflective) using representative cases from Chinese museums. Thirdly, based on prior research, the study establishes UX evaluation criteria and selects expert interview subjects, identifying key factors affecting user experience: meaningful, pleasurable, convenient, usable, reliable, and interaction. Finally, the study synthesizes insights from case analysis and interview results. From an emotional design perspective, virtual humans are modeled after real people and incorporate traditional Chinese cultural elements in their appearance, using natural dialogue and emotional expression. They explain the background and history of artifacts and enhance participation through diverse interaction methods. Rich knowledge and engaging interactions attract visitor attention and enhance enjoyment. In terms of UX evaluation, diverse interactions increase immersion, while natural language and visual/auditory elements stimulate curiosity and engagement. Concise information delivery and voice interaction improve convenience. Functions such as inquiry response and route planning meet individual needs. Natural voice interaction and data security enhance trust, while improved voice recognition accuracy and facial expression consistency enhance user immersion and interaction experience.

Designing and evaluation of a mixed reality system for crime scene investigation training: a hybrid approach

Police investigation in real-life crime scenes is an essential aspect of forensic science education. However, the practicality of bringing young investigators to actual crime scenes is often hindered by the costs and challenges involved. In order to overcome these obstacles, new technologies such as mixed reality (MR) are being explored as potential solutions. MR technology offers an interactive and cost-effective way to simulate real-life crime scenes, providing a valuable training experience for young investigators. This paper presents a novel design of a MR system using Microsoft HoloLens 2.0, which is tailored to work in a spatial 3D scanned and reconstructed crime scene using FARO point cloud 3D scanner X130 blended with photogrammetry techniques. The system was developed through the lens of Experiential Learning Theory and designed using a participatory approach, providing a cost-effective solution to help trained Kuwaiti police officers enhance their investigative skills. In order to evaluate the system’s user experience and user interaction, the Questionnaire of User Interaction Satisfaction and User Experience Questionnaire were utilised. Forty-four young police officers evaluated the system. Police students showed positive levels of satisfaction with user interaction and overall user experience with minimal negative feedback. Female students showed higher satisfaction with the overall impression compared to male students. Based on the positive feedback regarding the system expansion, the system will be taken into the commercialisation stage in the future to be provided as an essential tool for crime scene education and investigation practices.

Digital media entertainment technology based on artificial intelligence robot in art teaching simulation

The combination of digital media entertainment technology and artificial intelligence robots provides new possibilities for art teaching, providing students with a richer and more personalized learning experience. The aim of this study is to explore the application of artificial intelligence based digital media entertainment technology in art teaching simulation. By designing an intelligent digital media system, the interactivity, personalization, and effectiveness of art teaching can be improved. Research the use of digital media interactive technology to create an immersive art learning environment. Applying artificial intelligence recommendation algorithms to recommend personalized art teaching resources to students based on their learning history, interests, and abilities, in order to improve learning efficiency and outcomes. Combining artificial intelligence recommendation algorithms, intelligently recommend suitable art teaching resources for different students’ needs and levels. Through teaching interaction simulation testing, evaluate the interaction effect and user experience of the system in simulated art teaching scenarios, identify and fix potential problems. By utilizing digital media interaction technology and personalized recommendation algorithms, designing an intelligent digital media system can effectively enhance the interactivity, personalization, and effectiveness of art teaching, providing students with a better learning experience.

Research on Human Computer Interaction Technology in Virtual Reality Scenes

This paper discusses the current status, challenges and development trends of human computer interaction technology in virtual reality scenarios. Virtual reality technology has gradually become a frontier field of human computer interaction research. This paper analyzes virtual reality technology and human computer interaction technology. By introducing the commonly used human computer interaction hardware equipment and software technology in current virtual reality scenarios, it reveals the actual application of human computer interaction in virtual reality environments. From the three aspects of technology, user experience, and security and privacy protection, this paper analyzes the challenges faced by human computer interaction technology in virtual reality scenarios. In the future, with the continuous advancement of technological innovation, new human-computer interaction technologies will continue to emerge, and the integration of artificial intelligence technology will further enhance the intelligence level of human-computer interaction, making the user interaction experience more natural and convenient.

Social robots based on sensor technology simulate user music interaction experience

Social robots, as an important research object in the field of human–computer interaction, have enormous potential in simulating human social behavior and providing personalized services. This study aims to enhance the user experience of music interaction with social robots by constructing a social robot interaction model and combining sensor technology. The study sorted out relevant social psychology theories and methods of emotional computing, as well as theories related to music perception and expression in social robot design. By designing experimental scenarios, the interaction behavior between participants and social robots was observed, combined with gesture sensing processing and speech interaction enhancement processing, to improve the quality and effectiveness of interaction with social robots. We used simulation experiments to simulate the music interaction between users and social robots, in order to verify the reliability and stability of the social robot interaction model. Finally, human–machine electronic music interaction simulation was achieved, and user emotion collection and interaction simulation were carried out. By collecting physiological signals and emotional feedback from users, we have gained a deeper understanding of their emotional experience in music interaction, and through interaction simulation, we have regulated and guided their emotions.

The Influence of Response Time and Feedback Type on the User Experience of Voice Interaction among Older Adults

With the maturity and development of digital technology, voice interaction has been widely used in different devices or scenarios. However, older adults have low satisfaction and acceptance levels when using voice interaction. To improve older adults’ user experience of voice interaction, the current study explored the effect of response time and feedback type on the user experience of voice interaction among older adults. A Xiaodu smart speaker was used as the experimental device, and the response time was recorded using artificial breakpoints. Our study consisted of two experiments that explored the voice wake-up and voice dialogue stages under different combinations of response time and feedback type and older adults rated their satisfaction, comfort, anthropomorphism, and perceived speed level. The results showed that: (1) the optimal wake-up response time for older adults is 250–1000 ms, and the optimal dialogue response time is 600–1500 ms. (2) As response time increases, older adults’ satisfaction, comfort, and anthropomorphism toward smart speakers decrease. In the wake-up stage, the scores in the time period >2000 ms is significantly lower than those shorter response times. In the dialogue stage, the scores in the time periods >3000 ms are significantly lower than those shorter response times. (3) In the wake-up stage, the voice-based prompt “Hello, I’m Xiaodu” scores highest among all kinds of feedback types. In the dialogue stage, the social-oriented feedback scores higher in satisfaction and comfort than task-oriented feedback. The results of the current study could provide implications for age-friendly voice interaction design.

The Influence of Interactivity, Aesthetic, Creativity and Vividness on Consumer Purchase of Virtual Clothing: The Mediating Effect of Satisfaction and Flow

With the rapid global growth of digital fashion, virtual clothing has recently become a hot research topic. However, there is still little literature exploring the mutual influence between virtual clothing design features and consumer purchase intentions. This study delves into the dynamic relationship between virtual clothing design attributes and consumer purchase tendencies, seeking to foster a balanced development of the virtual clothing industry. Following a literature review, this study formulated a theoretical model that includes seven key latent factors: Interactivity, Aesthetic, Creativity, Vividness, Satisfaction, Flow experience, and Purchase Intention. Anchored in the Stimulus-Organism-Response (SOR) paradigm, the study conducted offline trials where respondents tried on virtual clothing using AR as a stimulus, carefully examining data from 295 respondents. The analysis shows that while Interactivity and Aesthetics significantly increase the likelihood of consumer purchases, Creativity and Vividness lack a direct and substantial impact on this intent. Satisfaction and Flow experience are important mediating variables that profoundly influence the purchasing decisions for virtual clothing. The findings of this study provide new insights into virtual clothing design and marketing strategies, emphasizing the importance of optimizing user interaction and Aesthetic experiences in enhancing consumer purchase intentions.

AutoRL X: Automated Reinforcement Learning on the Web

Reinforcement Learning (RL) is crucial in decision optimization, but its inherent complexity often presents challenges in interpretation and communication. Building upon AutoDOViz — an interface that pushed the boundaries of Automated RL for Decision Optimization — this paper unveils an open-source expansion with a web-based platform for RL. Our work introduces a taxonomy of RL visualizations and launches a dynamic web platform, leveraging backend flexibility for AutoRL frameworks like ARLO and Svelte.js for a smooth interactive user experience in the front end. Since AutoDOViz is not open-source, we present AutoRL X, a new interface designed to visualize RL processes. AutoRL X is shaped by the extensive user feedback and expert interviews from AutoDOViz studies, and it brings forth an intelligent interface with real-time, intuitive visualization capabilities that enhance understanding, collaborative efforts, and personalization of RL agents. Addressing the gap in accurately representing complex real-world challenges within standard RL environments, we demonstrate our tool's application in healthcare, explicitly optimizing brain stimulation trajectories. A user study contrasts the performance of human users optimizing electric fields via a 2D interface with RL agents’ behavior that we visually analyze in AutoRL X, assessing the practicality of automated RL. All our data and code is openly available at: https://github.com/lorifranke/autorlx .

A 92 fps and 2.56 mJ/Frame Computing-In-Memory-Based Human Pose Estimation Accelerator With Resource-Efficient Macro for Mobile Devices

Human pose estimation (HPE) is a promising solution for accurately understanding the state and context of human actions in virtual reality (VR). A high frame rate with low-power HPE processing is required for a realistic user interaction experience in battery-limited mobile devices. The proposed HPE accelerator is a computing-in-memory (CIM) based accelerator that computes depth-wise separable convolution (DWSC) of a lightweight HPE network. Three key features contribute to a resource-efficient CIM accelerator: 1) Dual-mode CIM computes DWSC with a reconfigurable homogenous architecture, resulting in 2.68 times higher throughput than previous analog CIMs. 2) Effective layeraware unrolling performs bit-parallel computation on dualmode CIM with fewer ADC operations, achieving 46 times higher throughput than before. 3) Adaptive fused inter-macro balancing improves latency balance in layer fusion execution, leading to a 57.0 % higher frame rate than before. The proposed HPE accelerator is implemented in 28nm CMOS technology. It achieves higher computation resource utilization and operates HPE with a low energy-delay product of 27.6 uJ7s in mobile VR devices.