21,503 results on '"human computer interaction"'
Search Results
2. Towards Interaction Design with Active Inference: A Case Study on Noisy Ordinal Selection
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Stein, Sebastian, Williamson, John H., Murray-Smith, Roderick, Li, Gang, Series Editor, Filipe, Joaquim, Series Editor, Xu, Zhiwei, Series Editor, Buckley, Christopher L., editor, Cialfi, Daniela, editor, Lanillos, Pablo, editor, Pitliya, Riddhi J., editor, Sajid, Noor, editor, Shimazaki, Hideaki, editor, Verbelen, Tim, editor, and Wisse, Martijn, editor
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- 2025
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3. S2Net: Skeleton-Aware SlowFast Network for Efficient Sign Language Recognition
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Yang, Yifan, Min, Yuecong, Chen, Xilin, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cho, Minsu, editor, Laptev, Ivan, editor, Tran, Du, editor, Yao, Angela, editor, and Zha, Hongbin, editor
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- 2025
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4. EEGMobile: Enhancing Speed and Accuracy in EEG-Based Gaze Prediction with Advanced Mobile Architectures
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Liang, Teng, Damoah, Andrews, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kurosu, Masaaki, editor, Hashizume, Ayako, editor, Mori, Hirohiko, editor, Asahi, Yumi, editor, Schmorrow, Dylan D., editor, and Fidopiastis, Cali M., editor
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- 2025
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5. Augmented Reality-Assisted Environment for Medical Education: An Experience of Interactive and Immersive Learning
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Puthannadathil Reghunatha Kumar, Vikas, Kujur, Anurag, Ganguly, Bishnu, Behera, Santosh Kumar, Dash, Ajaya Kumar, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Antonacopoulos, Apostolos, editor, Chaudhuri, Subhasis, editor, Chellappa, Rama, editor, Liu, Cheng-Lin, editor, Bhattacharya, Saumik, editor, and Pal, Umapada, editor
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- 2025
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6. Advanced Speech Emotion Recognition in Malayalam Accented Speech: Analyzing Unsupervised and Supervised Approaches
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Thandil, Rizwana Kallooravi, Jalala, P. V., Zahid, Rahbar, Preethi, M., Ghosh, Ashish, Editorial Board Member, Dev, Amita, editor, Sharma, Arun, editor, Agrawal, S. S., editor, and Rani, Ritu, editor
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- 2025
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7. Adapting User Interfaces for Urban Data Platforms: A Research Study
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Tajja, Yasmina, Martin, Ludger, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Yang, Xin-She, editor, Sherratt, R. Simon, editor, Dey, Nilanjan, editor, and Joshi, Amit, editor
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- 2025
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8. XR-Menu: Food Ordering System in Extended Reality Application
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Ismail, Ajune Wanis, Fadzli, Fazliaty Edora, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Weber, Gerhard-Wilhelm, editor, Martinez Trinidad, Jose Francisco, editor, Sheng, Michael, editor, Ramachand, Raghavendra, editor, Kharb, Latika, editor, and Chahal, Deepak, editor
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- 2025
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9. Expecting politeness: perceptions of voice assistant politeness.
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Duffau, Elise and Fox Tree, Jean E.
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COGNITIVE psychology , *AUDITORY perception , *POSITIVE psychology , *COURTESY , *USER interfaces - Abstract
We examined how politeness perception can change when used by a human or voice assistant in different contexts. We conducted two norming studies and two experiments. In the norming studies, we assessed the levels of positive politeness (cooperation) and negative politeness (respecting autonomy) conveyed by a range of politeness strategies across task (Norming Study 1) and social (Norming Study 2) request types. In the experiments, we tested the effect of request type and imposition level on the perception of written requests (Experiment 1) and requests spoken by a voice assistant (Experiment 2). We found that the perception of politeness strategies varied by request type. Positive politeness strategies were rated as very polite with task requests. In contrast, both positive and negative politeness strategies were rated as very polite with social requests. We also found that people expect agents to respect their autonomy more than they expect them to cooperate. Detailed studies of how request context interacts with politeness strategies to affect politeness perception have not previously been reported. Technology designers might find Tables 4 and 5 in this report especially useful for determining what politeness strategies are most appropriate for a given situation as well as what politeness strategies will evoke the desired feeling (autonomy or cooperation). [ABSTRACT FROM AUTHOR]
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- 2024
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10. A Conversational Assistant for Democratization of Data Visualization: A Comparative Study of Two Approaches of Interaction.
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Bhattacharya, Abari, Di Eugenio, Barbara, Grosso, Veronica, Johnson, Andrew, Tabalba, Roderick, Kirshenbaum, Nurit, Leigh, Jason, and Zellner, Moira
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NATURAL language processing , *COLLOQUIAL language , *NATURAL languages , *DATA visualization , *SOCIAL interaction - Abstract
Data visualization is an important aspect of exploratory data analysis which requires expertise, posing a challenge to many users. In this work, we present a conversational system designed to make data visualization accessible, where users can generate visualizations of data by natural language conversational interaction with the system. We conducted a between‐subject study to compare two versions of our system, where users were asked to perform data exploration tasks. We did not find significant differences as concerns user assessments of their interactions with the system; however, we uncovered that users explore different properties of the data and reach different conclusions when using the two systems. We will discuss the general implications of our findings as regards the usage of conversational interfaces for visualization. [ABSTRACT FROM AUTHOR]
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- 2024
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11. مستوى تفاعل طلاب الجامعة الإسلامية بالمدينة المنورة مع خدمات الاتصال الإداري الرقمي بالجامعة.
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إبراهيم بن خالد ا
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MUSLIM students , *BUSINESS communication , *DIGITAL communications , *DIGITAL transformation , *ARTIFICIAL intelligence - Abstract
The study aimed to measure the level of interaction of Islamic University students in Madinah with the university's digital administrative communication services and the obstacles that limit their interaction. To achieve this goal, the descriptive survey approach was followed, and the questionnaire was used as a tool for collecting data. It was applied to a sample of (381) students from the Islamic University in Madinah who were randomly selected. The study came out with the following results: The level of interaction of Islamic University students in Madinah with the university's digital administrative communication services from the students' point of view was high with an arithmetic mean (3.83), and the obstacles that limit the interaction of Islamic University students in Madinah with the university's digital administrative communication services from the students' point of view were high with an arithmetic mean (3.82), and that there were no statistically significant differences between the responses of the study sample members attributed to the variable of the academic stage. The study also recommended several recommendations, the most important of which are: benefiting from artificial intelligence programs and applications and introducing them into the university's digital administrative communication services, and conducting a periodic evaluation of digital administrative communication services. [ABSTRACT FROM AUTHOR]
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- 2024
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12. Aircraft human‐machine interaction assistant design: A novel multimodal data processing and application framework.
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Wu, Ao, Jin, Yang, Lv, Maolong, Li, Huanyu, Li, Leyan, and Yang, Rennong
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PROGRAMMING languages , *SPEECH perception , *MILITARY airplanes , *ELECTRONIC data processing , *LANGUAGE & languages , *MULTIMODAL user interfaces - Abstract
During aircraft operations, pilots rely on human‐machine interaction platforms to access essential information services. However, the development of a highly usable aerial assistant necessitates the incorporation of two interaction modes: active‐command and passive‐response modes, along with three input modes: voice inputs, situation inputs, and plan inputs. This research focuses on the design of an aircraft human‐machine interaction assistant (AHMIA), which serves as a multimodal data processing and application framework for human‐to‐machine interaction in a fully voice‐controlled manner. For the voice mode, a finetuned FunASR model is employed, leveraging private aeronautical datasets to enable specific aeronautical speech recognition. For the situation mode, a hierarchical situation events extraction model is proposed, facilitating the utilization of high‐level situational features. For the plan mode, a multi‐formations double‐code network plan diagram with a timeline is utilized to effectively represent plan information. Notably, to bridge the gap between human language and machine language, a hierarchical knowledge engine named process‐event‐condition‐order‐skill (PECOS) is introduced. PECOS provides three distinct products: the PECOS model, the PECOS state chart, and the PECOS knowledge description. Simulation results within the air confrontation scenario demonstrate that AHMIA enables active‐command and passive‐response interactions with pilots, thereby enhancing the overall interaction modality. [ABSTRACT FROM AUTHOR]
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- 2024
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13. Human-Browser Interaction: Investigating Whether the Current Browser Application's Design Actually Make Sense for Its Users?
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Carroll, Fiona
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WEB browsers , *WEB-based user interfaces , *USER interfaces , *INTERNET safety , *TRUST - Abstract
As a society, we can get so engrossed in using the World Wide Web (WWW) also known as the web. We look for, read about and interact with different people, text, images, videos etc. that we often take for granted how we are doing this. We all use a web browser, we must, to get around the web. Yet, do we ever stop to give much thought to this gateway to the web? The web browser can be fittingly described as a transparent technology. This is in the sense that we don't really stop to think about the browser and its features, we just unconsciously absorb and use it. This paper reports on a study that explores just how effectively we understand and use our web browser applications. The study was focused on people's perceived awareness of desktop web browser functionality, what features they are using/aware of and most importantly what understanding they take from these? The findings show that the majority (69%) of the five hundred and twenty-eight participants studied do not fully understand what the padlock feature on their web browsers represents. In fact, the findings highlight that many of the participants feel that the padlock represents a safe website which it clearly does not. This paper succinctly draws attention to the fact that the current desktop web browser application design is not fit for purpose. In summary, the research pushes for more effective web browser application designs; it provides design recommendations aimed at achieving web browser consistency and creating designs that promote safety, trust, and confidence. [ABSTRACT FROM AUTHOR]
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- 2024
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14. Enhanced Presence Evaluation in Virtual Reality Feedback System with TOPSIS Model.
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Li, Shuo, Zheng, Hongtao, Han, Ting, Hu, Jun, Zhang, Chenqi, and Yu, Cong
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ANALYTIC hierarchy process , *TOPSIS method , *VIRTUAL reality , *SOCIAL interaction , *RESEARCH personnel - Abstract
Researcher has been trying to optimize the method for evaluating presence in virtual reality (VR) to address variability and uncertainty in quick evaluations using questionnaires. We recommend using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model to calculated the iGroup Presence Questionnaire to measure users' overall presence in VR prototyping, instead of the weighted sum approach. The effects of two presence factors (scene density and motion trajectory technology) on a self-developed VR swimming virtual system were tested using the TOPSIS model with 20 participants each 12 tasks in a user experiment. The results were compared using two different weighting methods, fuzzy hierarchical analysis and uniform weighting methods. TOPSIS had a narrower range of data within the 95% confidence interval and a significantly lower coefficient of variation (CV). This indicates enhanced precision in evaluating presence and can be used to compare different technique setting of virtual systems. [ABSTRACT FROM AUTHOR]
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- 2024
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15. Design Strategies to Minimize Mobile Usability Issues in Navigation Design Patterns.
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Umar, Muhammad, Hussain, Ibrar, Mahmood, Toqeer, Mirza, Hamid Turab, and Faisal, C. M. Nadeem
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MOBILE apps , *USER-centered system design , *OLDER people , *USER experience , *SATISFACTION - Abstract
Recent development in mobile technology has significantly improved the quality of life. Everyday life is increasingly becoming dependent on mobile devices as mobile applications are targeting the needs of the end users. However, many end users struggle with navigating mobile applications, leading to frustration, especially with sophisticated and unfamiliar interfaces. This study focuses on addressing specific usability issues in mobile applications by investigating the impact of introducing a floating action button (FAB) and icons with names at the bottom in popular applications such as YouTube, Plex, and IMDb. The current research includes three studies: Study-1 explores the navigation issues that users face; Study-2 measures the experiences of the users with improved navigation designs; and Study-3 compares the results of Study-1 and Study-2 to evaluate user experience with both existing and improved navigation designs. A total of 147 participants participated and the systems usability scale was used to evaluate the navigation design. The experiments indicated that the existing design patterns are complex and difficult to understand leading to user frustration compared to newly designed and improved navigation designed patterns. Moreover, the proposed newly designed navigation patterns improved the effectiveness, learnability, and usability. Consequently, the results highlight the imperativeness of effective navigation design in improving user satisfaction and lowering frustration with mobile applications. [ABSTRACT FROM AUTHOR]
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- 2024
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16. Human teleoperation - a haptically enabled mixed reality system for teleultrasound.
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Black, David, Oloumi Yazdi, Yas, Hadi Hosseinabadi, Amir Hossein, and Salcudean, Septimiu
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MIXED reality , *REMOTE control , *ULTRASONIC imaging , *MEASUREMENT errors , *LOCAL mass media - Abstract
Current teleultrasound methods include audiovisual guidance and robotic teleoperation, which constitute tradeoffs between precision and latency versus flexibility and cost. We present a novel concept of "human teleoperation" which bridges the gap between these two methods. In the concept, an expert remotely teloperates a person (the follower) wearing a mixed-reality headset by controlling a virtual ultrasound probe projected into the person's scene. The follower matches the pose and force of the virtual device with a real probe. The pose, force, video, ultrasound images, and 3-dimensional mesh of the scene are fed back to the expert. This control framework, where the actuation is carried out by people, allows more precision and speed than verbal guidance, yet is more flexible and inexpensive than robotic teleoperation. The purpose of this paper is to introduce this concept as well as a prototype teleultrasound system with limited haptics and local communication. The system was tested to show its potential, including mean teleoperation latencies of 0.32 ± 0.05 seconds and steady-state errors of 4.4 ± 2.8 mm and 5.4 ± 2.8 $^ \circ $ ∘ in position and orientation tracking respectively. A preliminary test with an ultrasonographer and four patients was completed, showing lower measurement error and a completion time of 1:36 ± 0:23 minutes using human teleoperation compared to 4:13 ± 3:58 using audiovisual teleguidance. [ABSTRACT FROM AUTHOR]
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- 2024
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17. UPPER LIMB REHABILITATION ROBOTS TRAINING ANALYSIS BASED ON MULTI-SENSOR TRAJECTORY DATA AND HUMAN-COMPUTER INTERACTION.
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YANYU LIU and XIANQIAN LAO
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CONSTRAINT algorithms ,IMAGE reconstruction ,HUMAN-computer interaction ,SYSTEMS design ,IMAGE sensors - Abstract
Upper limb rehabilitation robots have important practical significance in helping patients recover their motor function, but traditional training methods often lack real-time and accurate evaluation of patient movement status and intention and have low interactive participation. Therefore, the study proposes a training system for upper limb rehabilitation robots based on multi-sensor trajectory data and human-computer interaction. The system is designed from three aspects: inertial sensor trajectory tracking, Kinect sensor image restoration, and interaction system design. A polynomial joint zero value constraint algorithm is introduced to correct errors, and variable parameter pixel filtering combined with a weighted average moving algorithm is used to improve image quality. The training results showed that the robot trajectory tracking accuracy significantly improved, and the improvement in motion trajectory error was greater than 20%. Compared with traditional training methods, interactive training had a recognition accuracy of over 85% in rehabilitation actions, and the system had better stability. This rehabilitation robot can effectively meet the feasibility and effectiveness of improving the interaction system, providing new technological means for intelligent medical services. [ABSTRACT FROM AUTHOR]
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- 2024
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18. The impacts of situational visual impairment on usability of touch screens.
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Hosseini, Masoumehsadat, Hamidi, Hamid Reza, and Kermanshahani, Shokooh
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TOUCH screen interfaces ,VISION disorders ,SOCIAL interaction ,USER interfaces ,GEOMETRIC shapes - Abstract
Using a touchscreen mobile device while walking in sunlight glare limits the visual attention. This situational visual impairment could affect the usability of these devices. This work focuses on the user interaction in situational visual impairment regarding touch gestures and no-visual feedbacks. We performed two user studies. In the first study, we modified the user interface of the two most used applications, phone calling and text messaging, using touch gesture and audio feedback while these features were not used before. Then a user study performed to extract the user preferences of modified applications in visual impairment situation. Our findings indicate that participants preferred gestures, but did not clearly indicate a preference for audio feedback. In the second study, we employed the computational evaluation to explore the distinctions between the made gestures by individuals in two different situations: with and without visual impairment. The outcomes show that in situations with visual impairment: (1) the people draw bigger and broader gestures, (2) there is higher error in features related to geometric shape, (3) familiarity of the user with gestures changes the speed and time for drawing them, and (4) there is not a critical distinctive conduct in how to apply strokes. The user interaction in situational visual impairment could be improved using touch gesture without audio feedback. This situation needs a wider area to make the gestures. [ABSTRACT FROM AUTHOR]
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- 2024
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19. An analysis of perfume packaging designs on consumer's cognitive and emotional behavior using eye gaze tracking.
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Modi, Nandini and Singh, Jaiteg
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CONSUMER behavior ,PUPIL (Eye) ,ECONOMIC competition ,PACKAGING design ,INTERNET content ,GAZE ,EYE tracking - Abstract
With increasing competition between the products in the market, packaging design is getting maximum attention in product sale. In order to sell any product, manufacturers use marketing strategies and effective communication. The aim of this study is to perform a product packaging analysis on perfume bottles, using eye gaze tracking technology to identify most viewed and consumer-friendly packaging design. To examine visual attention and emotional arousal in reaction to packaging design features in an ecommerce environment, we had conducted an eye gaze tracking experiment with 75 female participants. In this research, we analyzed pupil and eye monitoring metrics to identify emotional and cognitive processes, with an emphasis on emotional arousal, visual attention and cognitive effort. Our findings identified prominent packaging designs that sellers can use to display product advertisements according to consumer preferences to further enhance sales and revenue for their business. This study's empirical application could be extremely beneficial to marketers, content managers and advertisers in terms of managing and designing web content. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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20. Mobile payment services in hospitality and tourism sector: technology determinism, social constructivism, and technology ecosystem.
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Dang, Aditi and Khanra, Sayantan
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SOCIAL constructivism ,CONSUMER behavior ,MOBILE commerce ,BIBLIOMETRICS ,TECHNOLOGICAL innovations ,SUSTAINABLE tourism - Abstract
In the post-COVID-19 era, consumer behavior in hospitality and tourism has markedly shifted, favoring human-contactless services such as mobile payments. However, the utilization of mobile payment services in this sector remains erratic and disjointed. To highlight the current relevance of mobile payment services, this study undertakes a comprehensive bibliometric analysis of 572 articles to structure the existing literature on mobile payment services in hospitality and tourism. The study identifies three thematic areas through co-citation analysis: technology determinism, social constructivism, and the technology ecosystem in the hospitality and tourism sector. The analysis demonstrates a shift in literature, from technology determinism and social constructivism to the more systemic view of mobile payment services within a technological ecosystem. The thematic areas are not mutually exclusive, exhibiting overlaps through co-citation network. The study findings add to the evolving landscape of mobile payment services, within the broader technology ecosystem in hospitality and tourism sector. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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21. Designing Collective Empowerment to Support Bottom-Up City-Making.
- Author
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Schouten, Ben A. M., Klerks, Gwen, and Cazacu, Sivia
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ROLEPLAYING games ,HUMAN-computer interaction ,COLLECTIVE efficacy ,SELF-efficacy ,BEHAVIORAL sciences ,COMMUNITY psychology - Published
- 2024
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22. Collaborative Decision Making with Responsible AI: Establishing Trust and Load Models for Probabilistic Transparency.
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Wang, Xinyue, Li, Yaxin, and Xue, Chengqi
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ARTIFICIAL intelligence ,SOCIAL interaction ,DECISION making ,PSYCHOLOGY ,COMPUTERS - Abstract
In responsible AI development, the construction of AI systems with well-designed transparency and the capability to achieve transparency-adaptive adjustments necessitates a clear and quantified understanding of user states during the interaction process. Among these, trust and load are two important states of the user's internal psychology, albeit often challenging to directly ascertain. Thus, this study employs transparency experiments involving multiple probabilistic indicators to capture users' compliance and reaction times during the interactive collaboration process of receiving real-time feedback. Subsequently, estimations of trust and load states are established, leading to the further development of a state transition matrix. Through the establishment of a trust–workload model, probabilistic estimations of user states under varying levels of transparency are obtained, quantitatively delineating the evolution of states and transparency within interaction sequences. This research lays the groundwork for subsequent endeavors in optimal strategy formulation and the development of transparency dynamically adaptive adjustment strategies based on the trust–workload state model constraints. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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23. Inspiration
- Subjects
artifical intelligence ,computer networks ,software engineering ,human computer interaction ,internet of things ,microcontrollers ,Information technology ,T58.5-58.64 ,Electronic computers. Computer science ,QA75.5-76.95 - Published
- 2025
24. A multimodal expert system for the intelligent monitoring and maintenance of transformers enhanced by multimodal language large model fine‐tuning and digital twins
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Xuedong Zhang, Wenlei Sun, Ke Chen, and Renben Jiang
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control system synthesis ,data analysis ,decision making ,fault diagnosis ,human computer interaction ,industrial robots ,Manufactures ,TS1-2301 ,Technological innovations. Automation ,HD45-45.2 - Abstract
Abstract The development of multimodal large models and digital twin technology is set to revolutionise the methods of intelligent monitoring and maintenance for transformers. To address the issues of low intelligence level, single application mode, and poor human–machine collaboration in traditional transformer monitoring and maintenance methods, an intelligent monitoring and maintenance digital twin multimodal expert reasoning system, fine‐tuned on visual language‐based large models, is proposed. The paper explores the modes and methods for implementing intelligent monitoring and maintenance of transformers based on multimodal data, large models, and digital twin technology. A multimodal language large model (MLLM) framework for intelligent transformer maintenance, grounded on the Large Language and Vision Assistant model, has been designed. To enable large models to understand and reason about image annotation areas, an adaptive grid‐based positional information processor has been designed. To facilitate the compatibility and learning of large models with transformer Dissolved Gas Analysis data, a heterogeneous modality converter based on the Gram–Schmidt angular field has been developed. For the unified modelling and management of multimodal reasoning and comprehensive resource integration in human–machine dialogue, a central linker based on an identity resolution asset management shell has been designed. Subsequently, a visual‐language multimodal dataset for transformer monitoring and maintenance was constructed. Finally, by fine‐tuning parameters, a multimodal expert reasoning system for intelligent transformer monitoring and maintenance was developed. This system not only achieves real‐time monitoring of the transformer's operational status but also generates maintenance strategies intelligently based on operational conditions. The expert system possesses robust human–machine dialogue capabilities and reasoning generation abilities. This research provides a reference for the deep integration of MLLM and digital twin in industrial scenarios, particularly in the application modes of intelligent operation and maintenance for transformers.
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- 2024
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25. Advancing human-computer interaction: AI-driven translation of American Sign Language to Nepali using convolutional neural networks and text-to-speech conversion application
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Biplov Paneru, Bishwash Paneru, and Khem Narayan Poudyal
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Human computer interaction ,gTTS ,American Sign Language, speech-to-text, OpenCV, Tkinter ,VGG16 ,Convolutional neural networks ,Information technology ,T58.5-58.64 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Advanced technology that serves people with impairments is severely lacking in Nepal, especially when it comes to helping the hearing impaired communicate. Although sign language is one of the oldest and most organic ways to communicate, there aren't many resources available in Nepal to help with the communication gap between Nepali and American Sign Language (ASL). This study investigates the application of Convolutional Neural Networks (CNN) and AI-driven methods for translating ASL into Nepali text and speech to bridge the technical divide. Two pre-trained transfer learning models, ResNet50 and VGG16, were refined to classify ASL signs using extensive ASL image datasets. The system utilizes the Python gTTS package to translate signs into Nepali text and speech, integrating with an OpenCV video input TKinter-based Graphical User Interface (GUI). With both CNN architectures, the model's accuracy of over 99 % allowed for the smooth conversion of ASL to speech output. By providing a workable solution to improve inclusion and communication, the deployment of an AI-driven translation system represents a significant step in lowering the technological obstacles that disabled people in Nepal must overcome.
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- 2024
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26. Assessing quality of experience for manipulation modes in virtual reality interaction
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Gangling Liu, Rusmadiah Bin Anwar, and Verly Veto Vermol
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Virtual reality ,interaction manipulation mode ,user experience ,quality of experience feature ,metaverse ,Human Computer Interaction ,Fine Arts ,Arts in general ,NX1-820 ,General Works ,History of scholarship and learning. The humanities ,AZ20-999 - Abstract
Driven by the concept of the metaverse, virtual reality technology has made significant advancements, thereby inspiring the academic community to delve into the quality of user experience (QoE) in VR. In reviewing the literature on VR interaction techniques and QoE evaluation methods, this study identified six key QoE features that impact VR interaction and manipulation experiences. It also identified three types of fundamental interaction tasks and their corresponding manipulation modes. Based on these findings, a within-subjects design experiment was conducted to evaluate the QoE of different VR manipulation modes. By using a combination of questionnaire and interview, data from 73 participants were collected and analyzed. The results showed that users preferred manipulation modes that simulate real-world operations due to their high realism, dependability, perspicuity, and operational comfort. The findings further indicated that appropriately integrating non-isomorphic operations can enhance efficiency without sacrificing comfort, while also adding fun and novelty to the experience. The results of this paper provide more accurate interaction design guidelines for designers and program developers working with VR manipulation modes.
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- 2024
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27. A review of telehealth during the COVID-19 emergency situation in the public health sector: challenges and opportunities
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Maleka, Ntibaneng Hunadi and Matli, Walter
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- 2024
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28. Small businesses and e-government participation: the role of personalisation preference and intermediaries
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Scutella, Maryanne, Plewa, Carolin, and Reaiche, Carmen
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- 2024
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29. Pedagogical AI conversational agents in higher education: a conceptual framework and survey of the state of the art
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Yusuf, Habeeb, Money, Arthur, and Daylamani-Zad, Damon
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- 2025
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30. Spatio‐temporal attention modules in orientation‐magnitude‐response guided multi‐stream CNNs for human action recognition
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Fatemeh Khezerlou, Aryaz Baradarani, Mohammad Ali Balafar, and Roman Gr. Maev
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convolutional neural nets ,feature extraction ,human computer interaction ,image motion analysis ,image representation ,video signal processing ,Photography ,TR1-1050 ,Computer software ,QA76.75-76.765 - Abstract
Abstract This paper introduces a new descriptor called orientation‐magnitude response maps as a single 2D image to effectively explore motion patterns. Moreover, boosted multi‐stream CNN‐based model with various attention modules is designed for human action recognition. The model incorporates a convolutional self‐attention autoencoder to represent compressed and high‐level motion features. Sequential convolutional self‐attention modules are used to exploit the implicit relationships within motion patterns. Furthermore, 2D discrete wavelet transform is employed to decompose RGB frames into discriminative coefficients, providing supplementary spatial information related to the actors actions. A spatial attention block, implemented through the weighted inception module in a CNN‐based structure, is designed to weigh the multi‐scale neighbours of various image patches. Moreover, local and global body pose features are combined by extracting informative joints based on geometry features and joint trajectories in 3D space. To provide the importance of specific channels in pose descriptors, a multi‐scale channel attention module is proposed. For each data modality, a boosted CNN‐based model is designed, and the action predictions from different streams are seamlessly integrated. The effectiveness of the proposed model is evaluated across multiple datasets, including HMDB51, UTD‐MHAD, and MSR‐daily activity, showcasing its potential in the field of action recognition.
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- 2024
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- View/download PDF
31. Enhancing interoceptive sensibility through exteroceptive–interoceptive sensory substitution
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Oran Goral, Iddo Yehoshua Wald, Amber Maimon, Adi Snir, Yulia Golland, Aviva Goral, and Amir Amedi
- Subjects
Body awareness ,Biofeedback ,Human Computer Interaction ,Interoception ,Respiration ,Sensory substitution ,Medicine ,Science - Abstract
Abstract Exploring a novel approach to mental health technology, this study illuminates the intricate interplay between exteroception (the perception of the external world), and interoception (the perception of the internal world). Drawing on principles of sensory substitution, we investigated how interoceptive signals, particularly respiration, could be conveyed through exteroceptive modalities, namely vision and hearing. To this end, we developed a unique, immersive multisensory environment that translates respiratory signals in real-time into dynamic visual and auditory stimuli. The system was evaluated by employing a battery of various psychological assessments, with the findings indicating a significant increase in participants' interoceptive sensibility and an enhancement of the state of flow, signifying immersive and positive engagement with the experience. Furthermore, a correlation between these two variables emerged, revealing a bidirectional enhancement between the state of flow and interoceptive sensibility. Our research is the first to present a sensory substitution approach for substituting between interoceptive and exteroceptive senses, and specifically as a transformative method for mental health interventions, paving the way for future research.
- Published
- 2024
- Full Text
- View/download PDF
32. Exploring the Nexus of User Interface (UI) and User Experience (UX) in the Context of Emerging Trends and Customer Experience, Human Computer Interaction, Applications of Artificial Intelligence
- Author
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Biplov Paneru, Bishwash Paneru, Ramhari Poudyal, and Krishna Bikram Shah
- Subjects
human computer interaction ,ui ,ux ,artificial intelligence ,Information technology ,T58.5-58.64 ,Computer engineering. Computer hardware ,TK7885-7895 - Abstract
The complexities of User Interface (UI) and User Experience (UX) design are explored in this research paper, along with their respective functions, areas of overlap, and the changing field of customer experience. In the digital age, where technology is developing at a rapid pace, designing innovative and user-focused digital products requires an understanding of the dynamic interplay between UI and UX. This research also examines how emerging trends in the UI/UX field will affect overall customer satisfaction. Additionally, this paper delves into applications of artificial intelligence (AI) in the domains of human-computer interaction (HCI), user experience (UX), and emerging trends in these fields
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- 2024
- Full Text
- View/download PDF
33. Botlitica: A generative AI-based tool to assist journalists in navigating political propaganda campaigns
- Author
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Elena Musi, Edgar Everardo Garcia Aguilar, and Lorenzo Federico
- Subjects
disinformation ,generative ai ,political communication ,human computer interaction ,fact-checking ,Communication. Mass media ,P87-96 ,Social Sciences - Abstract
The hype on generative AI has raised concerns about the spread of disinformation but also opened up new opportunities for hybrid journalism. The proliferation of political propaganda campaigns spread across digital media during election periods constitutes a challenge for journalists who struggle to exercise information gatekeeping. AI-based tools can in principle help, but journalists are resistant to using them since they are sceptical about their compliance with news values and their scarce user-friendliness. To cope with such issues, we present Botlitica, a GPT3-based chatbot able to answer users’ questions according to the information shared on different social media by a given political party which is, thus, embodied by the AI agent in the conversation. The back-end and front-design of the chatbot are devised to privilege transparency. We report the results of a preliminary evaluation of Botlitica which show that the tool fastens journalists’ capabilities to navigate propaganda campaigns inducing them to exercise critical thinking.
- Published
- 2024
- Full Text
- View/download PDF
34. Multifractality as a lens on embodied human computer interaction
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Bennett, Daniel T., Metatla, Oussama, and Roudaut, Anne
- Subjects
embodiment ,Human computer interaction ,Enactivism ,Dynamical systems ,Phenomenology ,Fractal dimension analysis - Abstract
This thesis investigates the application of multifractal analysis to user behaviour during interaction with technology. Multifractal analysis is an analysis technique which quantifies features in behavioural signals which have been connected to embodied, control structures which emerge from interactions between processes across brain, body and context. It has been widely observed in human movement and behaviour, and variation in multifractal signatures has been associated with a range of flexible adaptive behaviours. Through experiments and data analyses, I investigate the value of this approach for Embodied Interaction research, and HCI more broadly. I find the approach offers potential in operationalising key concepts in Embodied Interaction, which often rely on similar assumptions about the role of contextual interactions. In particular, my results show that multifractal signatures in behaviour are informative about dimensions of ready-to-hand tool use - an influential construct in Embodied Interaction, drawn from phenomenological philosophy, which describes fluid, engaged tool use, in which the tool "disappears" for the user. I also investigate the potential to apply multifractal analysis to understand behavioural constructs of wider interest in HCI, beyond Embodied Interaction. I find that the approach has significant potential as a convenient-to-deploy measure which can be used to infer behavioural constructs including fatigue, engagement and skill. To support future work, I develop a framework and make methodological contributions to which can guide future applications of multifractal analysis in HCI.
- Published
- 2023
35. Effectively exploiting immersive technologies for enhanced user interaction
- Author
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Brice, Daniel, Rafferty, Karen, and McLoone, Sean
- Subjects
Virtual reality ,virtual reality exposure therapy ,human computer interaction - Abstract
There have been major progressions in the field of immersive technology recently leading to the prospect of utilising virtual reality (VR), augmented reality (AR) and haptics as tools for productivity being realised by a wide range of industries. With the increased uptake in the adoption of immersive technologies it is essential that research be conducted to investigate how to effectively enhance user interactions and experiences. This thesis contains the dissemination of four novel proof of concept systems developed for a range of VR and AR applications with technologies such as the HTC VIVE, Microsoft HoloLens and Ultrahaptics. The concepts are developed and assessed through empirical user studies which demonstrate how effectively technology integrations can enhance user interactions. The research presented throughout the technical chapters highlights strengths and weaknesses of a wide range of technologies used in immersive workflows, from issues with the volume size for haptic platforms through to the effect VR can have on our emotions. The dissemination of the systems and findings during user studies are valuable for those interested in the development of applications for VR, AR and Haptics. The research presented in this thesis is also of relevance for stakeholders surrounding the implementation of VR / AR workflows in industry, with specific novel implementations of concepts, such as real time guidance of maintenance tasks in AR and a demonstrator of a multi-sensorial experience with virtual spiders for consideration in virtual reality exposure therapy (VRET) design.
- Published
- 2023
36. Real-Time Haptic Rendering: Perception, Optimization, and Multi-Modal Integration.
- Author
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Maheshwari, Shyam, Makwana, Hemant, and Lal, Devesh Kumar
- Subjects
ADAPTIVE control systems ,SURFACE texture ,VIRTUAL reality ,MULTISENSOR data fusion ,GENETIC algorithms ,HAPTIC devices - Abstract
This review explores the recent advancements, challenges, and future directions in real-time haptic rendering, a technology that enables users to experience touch sensations in virtual environments through precise tactile feedback. Real-time haptic rendering plays a critical role in enhancing user interaction in applications such as Virtual Reality (VR), Augmented Reality (AR), and teleportation by providing a realistic sense of touch. The paper discusses fundamental haptic rendering techniques, including force computation methods, perceptionbased models, and optimization strategies like genetic algorithms and adaptive control. It highlights the role of multi-modal feedback systems in delivering immersive experiences by integrating force, vibration, and tactile feedback. Key challenges, such as latency, computational complexity, and stability, are examined alongside potential solutions, including AI-driven adaptation, cloud-based rendering, and hardware innovations. The review also presents a detailed analysis of emerging applications in fields such as medical training, gaming, and remote collaboration. Looking forward, the integration of advanced AI models, hybrid rendering techniques, and new feedback modalities promises to further enhance the realism and scalability of haptic systems, paving the way for more accessible and interactive virtual experiences. [ABSTRACT FROM AUTHOR]
- Published
- 2024
37. Exploring Audio-Visual Correlation for Real-Time Texture Analysis.
- Author
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Maheshwari, Shyam, Makwana, Hemant, and Lal, Devesh Kumar
- Subjects
PEARSON correlation (Statistics) ,SURFACE texture ,EUCLIDEAN distance ,SURFACE properties ,HUMAN-robot interaction - Abstract
This study presents a novel exploration of the correlation between surface images and audio generated by linear movement over surfaces using three key similarity metrics: Euclidean Distance (ED), Cosine Similarity, and Pearson Correlation. A key contribution of this research is the application of these metrics to the LMT TUM Texture dataset, revealing new insights into their comparative effectiveness for multisensory fusion. The results demonstrate that Cosine Similarity and Pearson Correlation maintain high stability across varying surface textures, making them ideal for real-time applications in augmented reality (AR), human-robot interaction (HRI), and industrial monitoring. In contrast, Euclidean Distance exhibits greater sensitivity to texture changes, highlighting its utility for detecting subtle variations in surface properties, especially for fault detection and industrial applications. The study also identifies how increasing the Sigma value enhances similarity, as Euclidean Distance decreases while Cosine Similarity and Pearson Correlation approach near-perfect correlation. Although the analysis is insightful, the research is limited by the narrow range of surface textures and the absence of real-time implementation. Future research will expand the dataset and integrate machine learning techniques to enhance real-time performance. This work advances the field by offering a robust framework for understanding and optimizing multisensory fusion systems across practical applications. [ABSTRACT FROM AUTHOR]
- Published
- 2024
38. Looking fear in the eye: Gamified virtual reality exposure towards spiders for children using attention based feedback.
- Author
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Wechsler, Theresa F, Kocur, Martin, Schumacher, Sandra, Rubenbauer, Mirjam, Ruider, Andreas, Brockelmann, Martin, Lankes, Michael, Wolff, Christian, and Mühlberger, Andreas
- Subjects
- *
PHOBIAS treatment , *FEAR , *PILOT projects , *POSITIVE psychology , *DESCRIPTIVE statistics , *TREATMENT effectiveness , *EXPOSURE therapy , *GAMES , *ATTENTION , *MOTIVATION (Psychology) , *PRE-tests & post-tests , *RESEARCH methodology , *VIRTUAL reality therapy , *SPIDERS , *AFFECT (Psychology) , *ANXIETY disorders , *EYE movements - Abstract
Many children around the globe suffer from spider phobia. Virtual reality exposure therapy is an effective phobia treatment, but so far predominantly tailored for adults. A gamified approach utilizing gaze interaction would allow for a more child-friendly and engaging experience, and provide the possibility to foster working mechanisms of exposure therapy. We developed an application in which children make spiders change in positively connoted ways (e.g., make them dance or shrink) if sufficient visual attention towards them is captured via eye tracking. Thereby, motivation for and positive affects during exposure towards spiders are aspired. In this pilot study on 21 children without (n = 11) and with fear of spiders (n = 10), we examined positive and negative affect during exposure to a virtual spider and to different gaze-related transformations of the spider within a quasi-experimental design. Within a one-group design, we additionally examined fear of spiders in spider fearful children before and one week after the intervention. We found that significantly more positive than negative affect was induced by the spiders' transformations in children without and with fear of spiders. Fear of spiders was furthermore significantly reduced in spider-fearful children, showing large effect sizes (d >.80). Findings indicate eligibility for future clinical use and evaluation in children with spider phobia. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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39. Spatio‐temporal attention modules in orientation‐magnitude‐response guided multi‐stream CNNs for human action recognition.
- Author
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Khezerlou, Fatemeh, Baradarani, Aryaz, Balafar, Mohammad Ali, and Maev, Roman Gr.
- Subjects
- *
HUMAN activity recognition , *CONVOLUTIONAL neural networks , *FEATURE extraction , *WAVELET transforms , *SPACE trajectories , *DISCRETE wavelet transforms , *VIDEO processing , *IMAGE compression - Abstract
This paper introduces a new descriptor called orientation‐magnitude response maps as a single 2D image to effectively explore motion patterns. Moreover, boosted multi‐stream CNN‐based model with various attention modules is designed for human action recognition. The model incorporates a convolutional self‐attention autoencoder to represent compressed and high‐level motion features. Sequential convolutional self‐attention modules are used to exploit the implicit relationships within motion patterns. Furthermore, 2D discrete wavelet transform is employed to decompose RGB frames into discriminative coefficients, providing supplementary spatial information related to the actors actions. A spatial attention block, implemented through the weighted inception module in a CNN‐based structure, is designed to weigh the multi‐scale neighbours of various image patches. Moreover, local and global body pose features are combined by extracting informative joints based on geometry features and joint trajectories in 3D space. To provide the importance of specific channels in pose descriptors, a multi‐scale channel attention module is proposed. For each data modality, a boosted CNN‐based model is designed, and the action predictions from different streams are seamlessly integrated. The effectiveness of the proposed model is evaluated across multiple datasets, including HMDB51, UTD‐MHAD, and MSR‐daily activity, showcasing its potential in the field of action recognition. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
40. Dual Learning for Conversational Emotion Recognition and Emotional Response Generation.
- Author
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Zhang, Shuhe, Hu, Haifeng, and Xing, Songlong
- Abstract
Emotion recognition in conversation (ERC) and emotional response generation (ERG) are two important NLP tasks. ERC aims to detect the utterance-level emotion from a dialogue, while ERG focuses on expressing a desired emotion. Essentially, ERC is a classification task, with its input and output domains being the utterance text and emotion labels, respectively. On the other hand, ERG is a generation task with its input and output domains being the opposite. These two tasks are highly related, but surprisingly, they are addressed independently without making use of their duality in prior works. Therefore, in this article, we propose to solve these two tasks in a dual learning framework. Our contributions are fourfold: (1) We propose a dual learning framework for ERC and ERG. (2) Within the proposed framework, two models can be trained jointly, so that the duality between them can be utilised. (3) Instead of a symmetric framework that deals with two tasks of the same data domain, we propose a dual learning framework that performs on a pair of asymmetric input and output spaces, i.e., the natural language space and the emotion labels. (4) Experiments are conducted on benchmark datasets to demonstrate the effectiveness of our framework. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
41. An interactive task-based method for the avoidance of metal artifacts in CBCT.
- Author
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Rohleder, Maximilian, Thies, Mareike, Riedl, Sophie, Bullert, Benno, Gierse, Jula, Privalov, Maxim, Mandelka, Eric, Vetter, Sven, Maier, Andreas, and Kreher, Bjoern
- Abstract
Purpose: Intraoperative cone-beam CT imaging enables 3D validation of implant positioning and fracture reduction for orthopedic and trauma surgeries. However, the emergence of metal artifacts, especially in the vicinity of metallic objects, severely degrades the clinical value of the imaging modality. In previous works, metal artifact avoidance (MAA) methods have been shown to reduce metal artifacts by adapting the scanning trajectory. Yet, these methods fail to translate to clinical practice due to remaining methodological constraints and missing workflow integration. Methods: In this work, we propose a method to compute the spatial distribution and calibrated strengths of expected artifacts for a given tilted circular trajectory. By visualizing this as an overlay changing with the C-Arm's tilt, we enable the clinician to interactively choose an optimal trajectory while factoring in the procedural context and clinical task. We then evaluate this method in a realistic human cadaver study and compare the achieved image quality to acquisitions optimized using global metrics. Results: We assess the effectiveness of the compared methods by evaluation of image quality gradings of depicted pedicle screws. We find that both global metrics as well as the proposed visualization of artifact distribution enable a drastic improvement compared to standard non-tilted scans. Furthermore, the novel interactive visualization yields a significant improvement in subjective image quality compared to the state-of-the-art global metrics. Additionally we show that by formulating an imaging task, the proposed method allows to selectively optimize image quality and avoid artifacts in the region of interest. Conclusion: We propose a method to spatially resolve predicted artifacts and provide a calibrated measure for artifact strength grading. This interactive MAA method proved practical and effective in reducing metal artifacts in the conducted cadaver study. We believe this study serves as a crucial step toward clinical application of an MAA system to improve image quality and enhance the clinical validation of implant placement. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
42. Receive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles.
- Author
-
Cui, Can, Ma, Yunsheng, Cao, Xu, Ye, Wenqian, and Wang, Ziran
- Abstract
The fusion of human-centric design and artificial intelligence capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond traditional transportation. These vehicles can dynamically interact with passengers and adapt to their preferences. This article proposes a novel framework that leverages large language models (LLMs) to enhance the decision-making process in autonomous vehicles. By utilizing LLMs’ contextual understanding abilities with specialized tools, we aim to integrate the language and reasoning capabilities of LLMs into autonomous vehicles. Our research includes experiments in HighwayEnv, a collection of environments for autonomous driving and tactical decision-making tasks, to explore LLMs’ interpretation, interaction, and reasoning in various scenarios. We also examine some well-defined real-time personalized driving tasks, demonstrating how LLMs can influence driving behaviors based on drivers’ verbal commands. Our empirical results highlight the substantial advantages of utilizing chain-of-thought prompting, leading to improved driving decisions and showing the potential for LLMs to enhance personalized driving experiences through ongoing verbal feedback. The proposed framework aims to transform autonomous vehicle operations, offering personalized support, transparent decision making, and continuous learning to enhance safety and effectiveness. We achieve user-centric, transparent, and adaptive autonomous driving ecosystems supported by the integration of LLMs into autonomous vehicles. Experiment videos are available at https://youtube.com/playlist?list=PLgcRcf9w8BmLJi_fqTGq-7KCZsbpEIE4a&si=dhH9lgaeSmB5K94t. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
43. Enhancing interoceptive sensibility through exteroceptive–interoceptive sensory substitution.
- Author
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Goral, Oran, Wald, Iddo Yehoshua, Maimon, Amber, Snir, Adi, Golland, Yulia, Goral, Aviva, and Amedi, Amir
- Subjects
- *
INTEROCEPTION , *PSYCHOLOGICAL tests , *FLOW theory (Psychology) , *VISUAL perception , *AUDITORY perception , *MENTAL health - Abstract
Exploring a novel approach to mental health technology, this study illuminates the intricate interplay between exteroception (the perception of the external world), and interoception (the perception of the internal world). Drawing on principles of sensory substitution, we investigated how interoceptive signals, particularly respiration, could be conveyed through exteroceptive modalities, namely vision and hearing. To this end, we developed a unique, immersive multisensory environment that translates respiratory signals in real-time into dynamic visual and auditory stimuli. The system was evaluated by employing a battery of various psychological assessments, with the findings indicating a significant increase in participants' interoceptive sensibility and an enhancement of the state of flow, signifying immersive and positive engagement with the experience. Furthermore, a correlation between these two variables emerged, revealing a bidirectional enhancement between the state of flow and interoceptive sensibility. Our research is the first to present a sensory substitution approach for substituting between interoceptive and exteroceptive senses, and specifically as a transformative method for mental health interventions, paving the way for future research. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
44. Beyond the Screen With DanceSculpt: A 3D Dancer Reconstruction and Tracking System for Learning Dance.
- Author
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Lee, Sanghyub, Kang, Woojin, Hong, Jin-Hyuk, and Kong, Duk-Jo
- Subjects
- *
DANCE , *STREAMING video & television , *DANCERS , *INTERACTIVE learning , *INSTRUCTIONAL systems , *AVATARS (Virtual reality) , *POSE estimation (Computer vision) - Abstract
AbstractDance learning through online videos has gained popularity, but it presents challenges in providing comprehensive information and personalized feedback. This paper introduces DanceSculpt, a system that utilizes 3D human reconstruction and tracking technology to enhance the dance learning experience. DanceSculpt consists of a dancer viewer that reconstructs dancers in video into 3D avatars and a dance feedback tool that analyzes and compares the user’s performance with that of the reference dancer. We conducted a comparative study to investigate the effectiveness of DanceSculpt against conventional video-based learning. Participants’ dance performances were evaluated using a motion comparison algorithm that measured the temporal and spatial deviation between the users’ and reference dancers’ movements in terms of pose, trajectory, formation, and timing accuracy. Additionally, user experience was assessed through questionnaires and interviews, focusing on aspects such as effectiveness, usefulness, and satisfaction with the system. The results showed that participants using DanceSculpt achieved significant improvements in dance performance compared to those using conventional methods. Furthermore, the participants rated DanceSculpt highly in terms of effectiveness (avg. 4.27) and usefulness (avg. 4.17) for learning dance. The DanceSculpt system demonstrates the potential of leveraging 3D human reconstruction and tracking technology to provide a more informative and interactive dance learning experience. By offering detailed visual information, multiple viewpoints, and quantitative performance feedback, DanceSculpt addresses the limitations of traditional video-based learning and supports learners in effectively analyzing and improving their dance skills. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
45. Advancements in Gaze Coordinate Prediction Using Deep Learning: A Novel Ensemble Loss Approach.
- Author
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Kim, Seunghyun, Lee, Seungkeon, and Lee, Eui Chul
- Subjects
EYE tracking ,DEEP learning ,GAZE ,COMPUTATIONAL complexity ,FORECASTING - Abstract
Recent advancements in deep learning have enabled gaze estimation from images of the face and eye areas without the need for precise geometric locations of the eyes and face. This approach eliminates the need for complex user-dependent calibration and the issues associated with extracting and tracking geometric positions, making further exploration of gaze position performance enhancements challenging. Motivated by this, our study focuses on an ensemble loss function that can enhance the performance of existing 2D-based deep learning models for gaze coordinate (x, y) prediction. We propose a new function and demonstrate its effectiveness by applying it to models from prior studies. The results show significant performance improvements across all cases. When applied to ResNet and iTracker models, the average absolute error reduced significantly from 7.5 cm to 1.2 cm and from 7.67 cm to 1.3 cm, respectively. Notably, when implemented on the AFF-Net, which boasts state-of-the-art performance, the average absolute error was reduced from 4.21 cm to 0.81 cm, based on our MPIIFaceGaze dataset. Additionally, predictions for ranges never encountered during the training phase also displayed a very low error of 0.77 cm in terms of MAE without any personalization process. These findings suggest significant potential for accuracy improvements while maintaining computational complexity similar to the existing models without the need for creating additional or more complex models. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
46. Augmented reality as an educational tool in higher education: A literature survey.
- Author
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Kokkinidis, Konstantinos-Iraklis and Folina, Maria-Theodora
- Subjects
- *
AUGMENTED reality , *HIGHER education , *HUMAN-computer interaction , *MACHINE learning , *PUBLICATIONS - Abstract
Augmented Reality (AR) represents a promising technological advancement that this paper explores as a potential new educational tool. The integration of augmented reality applications into mobile devices facilitates interactive learning experiences for users. This integration transforms traditional printed educational materials into dynamic, interactive resources, aiming to enhance learner engagement, motivation, and overall educational outcomes. However, comprehending research trends and decision-making in this rapidly evolving field presents significant challenges. To address these challenges, this paper employs Bibliometrics, a method involving statistical and quantitative analysis of publications. Although augmented reality holds significant potential for higher education, limited studies have focused on its application, and scant attention has been given to bibliometric visualization. To bridge this gap, the paper utilizes VOSViewer, a bibliometric visualization software incorporating advanced machine learning techniques. The objective is to delineate the evolving landscape of augmented reality research from 2002 to the present and identify key research categories. Following an overview of the software's functionality, artificial intelligence, and machine learning concepts, the study progresses to its practical stage. The research involves the retrieval of publications related to augmented reality from the Scopus bibliographic database, resulting in the identification of 730 relevant publications. After their retrieval, the paper conducts a comprehensive statistical analysis and employs VOSViewer for further processing. The culmination of the study involves the construction of bibliometric maps, visualizing keywords and terms extracted from the titles and abstracts of international scientific journal publications. The analysis of these maps yields valuable insights, observations, and conclusions, contributing to a better understanding of the current state and trends within the augmented reality research landscape. This approach facilitates informed decision-making and provides a foundation for future developments in the educational sector leveraging augmented reality technology conclusions. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
47. Empowering customer satisfaction chatbot using deep learning and sentiment analysis.
- Author
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Merizig, Abdelhak, Belouaar, Houcine, Bakhouche, Mohamed Mghezzi, and Kazar, Okba
- Subjects
CHATBOTS ,NATURAL language processing ,DEEP learning ,SENTIMENT analysis ,MACHINE learning ,CUSTOMER satisfaction - Abstract
The rapid advancement of technology holds great promise for various types of users, clients, or service providers. Intelligent robots, whether virtual or physical, can simplify the reservation process. With the development of machines and processing tools, natural language processing (NLP) and natural language understanding (NLU) have emerged to help people comprehend spoken language through machines. In order to facilitate seamless human-machine interaction, we aim to address customer needs through a chatbot. The objective of this paper is to incorporate sentiment analysis techniques with deep learning algorithms to cater to customers' needs during message exchanges. This study aims to create an intelligent chatbot to engage customers during their routine operations and offer support. In addition, it offers to companies a manner to detect sarcastic messages. The proposed chatbot utilizes deep learning techniques to predict users' intentions based on the questions asked and provide a helpful and convenient answer. A new chatbot for the customer is presented to overcome with challenges related to a wrong statement like sarcastic one and feedback towards user messages. A comparison between deep and transfer learning gives a new insight to include sentiments and sarcasm detection in the conversion process. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
48. پیشنهاد چهارچوب مفهو می براي زیباییشناسی ی ک وبسایت با بهرهگیر ي از رویکردهاي فراترکیب و آنتروپی شانون بر پایه نظریه لایبنیتس
- Author
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مریم طاوسی, نادر نقشینه, محمد زرهساز, and سیامک محبوب
- Abstract
Introduction: User experience is a higher-order construct than user interface. Nielsen's 1994 checklist, comprising ten factors including aesthetics, has endured for three decades. However, the precise dimensions of beauty within the web Porpose: environment remain elusive and inadequately defined. This study was designed to mitigate the aforementioned ambiguity. It aims to identify the aesthetic components of a single website based on Leibniz's theory and to rank these components according to the criteria's significance. A conceptual framework for the 'aesthetics of a single website' is proposed. Methodology: This study employed a systematic review methodology incorporating metasynthesis and Shannon's qualitative content analysis approach. A targeted keyword search was executed across six databases: Google Scholar, Emerald, Web of Science, IRANDOC, ISC, and SID. An initial pool of 1110 sources was identified. Subsequently, 64 documents were selected for the meta-synthesis study in accordance with the PRISMA statement. Leibniz's aesthetic theory underpins the qualitative coding framework for this study. The aesthetic factors delineated by Lavie and Tractinsky and the website analysis conducted by Guo and Hall served as foundational references for code development. Subsequently, an importance coefficient was computed for each identified aesthetic code, employing Shannon's qualitative content analysis method as outlined by Azar (2000). The aforementioned method conceptualizes each code within the source data as an exchanged communication. The sources themselves comprise the interviewees or experts who provided responses to the research query. Findings: A meta-synthesis yielded two categories, four concepts, and seventy-five aesthetic codes. The primary categories of website beauty were identified as the overarching levels of "objective aesthetics" and "subjective aesthetics." The subjective level pertains to the user and their perception (subject), while the objective level relates to the website design (object). Two primary concepts emerged within each category: semantic aesthetics and classical aesthetics. Within the objective aesthetics category, the codes of "typography" and "order" were deemed most important under the concept of classical aesthetics. Within the domain of subjective aesthetics, the principles of "attractive color combination," "intuitive navigation," and "moderate visual complexity," derived from classical aesthetic theory, were determined to be of paramount importance. A total of forty-three aesthetic codes for websites were identified as possessing a non-zero importance coefficient. Forty-three codes with a non-zero importance coefficient were identified and ranked from one to sixteen. The remaining thirtytwo codes, from a total of seventy-five, exhibited a zero Shannon entropy significance coefficient (indicating a single repetition in previous studies) and were consequently assigned to the seventeenth rank of Shannon's significance. The top twelve codes, prioritized as follows, were: observance of typography techniques in website content design, orderliness and cleanliness of website content, observance of symmetry in website content design, nonvisual complexity, and attractive website color combination. From the perspective of the website user's mind, "Coherence in website content design", "Intuitive website content navigation", "Adherence to organizational structure, sequence, and hierarchy in website design", "Optimal complexity for the website user", "Evoking a sense of richness and diversity for the website user", "Diverse website content design", "Visual appeal and engagement for the website user". Adherence to the Gestalt principle and the golden ratio in website design are among the other codes identified. Conclusion: Website administrators should consider both objective and subjective aesthetic factors to optimize user experience. While various studies have explored website aesthetics, this research is unique in its application of meta-synthesis and Shannon's entropy coding, constituting a pioneering effort both domestically (Iran) and internationally. Interdisciplinary collaboration between computer science and social science is recommended for advancing this field. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
49. Indian Cross Corpus Speech Emotion Recognition Using Multiple Spectral-Temporal-Voice Quality Acoustic Features and Deep Convolution Neural Network.
- Author
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Kawade, Rupali and Jagtap, Sonal
- Subjects
CONVOLUTIONAL neural networks ,SPEECH perception ,EMOTION recognition ,ONLINE social networks ,ARCHITECTURAL acoustics ,FEATURE selection - Abstract
Speech Emotion Recognition (SER) is very crucial in enriching next generation human machine interaction (HMI) with emotional intelligence capabilities by extracting the emotions from words and voice. However, current SER techniques are developed within the experimental boundaries and faces major challenges such as lack of robustness across languages, cultures, age gaps and gender of speakers. Very little work is carried out for SER for Indian corpus which has higher diversity, large number of dialects, vast changes due to regional and geographical aspects. India is one of the largest customers of HMI systems, social networking sites and internet users, therefore it is crucial for SER that focuses on Indian corpuses. This paper presents, cross corpus SER (CCSER) for Indian corpus using multiple acoustic features (MAF) and deep convolution neural network (DCNN) to improve the robustness of the SER. TheMAF consists of various spectral, temporal and voice quality features. Further, Fire Hawk based optimization (FHO) technique is utilized for the salient feature selection. The FHO selects the important features from MAF to minimize the computational complexity and improve feature distinctiveness based in inter class and inter class variance of the features. The DCNN algorithm provides the better correlation, higher feature representation, better description of variation in timbre, intonation and pitch, superior connectivity in global and local features of the speech signal to characterize the corpus. The outcomes of suggested DCNN based SER is evaluated on Indo-Aryan language family (Hindi and Urdu) and Dravidian Language family (Telugu and Kannada). The proposed scheme results in improved accuracy for the various cross corpus and multilingual SER and out performs the traditional techniques. It provides an accuracy of 58.83%, 61.75%, 69.75% and 45.51% for Hindi, Urdu, Telugu and Kannada language for multilingual training. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
50. Utilizing Multiple Regression Analysis and Entropy Method for Automated Aesthetic Evaluation of Interface Layouts.
- Author
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Wang, Xinyue, Tong, Mu, Song, Yukun, and Xue, Chengqi
- Subjects
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MULTIPLE regression analysis , *TECHNOLOGY assessment , *ENTROPY , *AESTHETICS , *HUMAN-computer interaction - Abstract
Aesthetic evaluation of increasingly complex and personalized human–computer interaction interfaces serves as a critical bridge between humans and machines, fundamentally enhancing various interaction factors. This study addresses the challenges in aesthetic evaluation by adjusting existing methodologies to incorporate seven aesthetic metrics: density, symmetry, balance, proportionality, uniformity, simplicity, and sequence. These metrics were effectively integrated into a composite evaluation metric through both multiple regression analysis and entropy methods, with the efficacy of both fitting methods validated. Leveraging automatic segmentation and recognition technology for interface screenshots, this research enables rapid, automated acquisition of evaluations for the seven metrics and the composite index, leading to the development of a prototype system for interface layout aesthetic assessment. Aimed at reducing the time, manpower, and resources required for interface evaluation, this study enhances the universality, compatibility, and flexibility of layout assessments. It promotes integration at any stage of the design process, significantly benefiting lightweight rapid evaluation and iterative design cycles, thereby advancing the field of interface aesthetic evaluation. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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