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With the increase of Internet users, the traditional music recommendation model cannot meet the increasing personalized needs of users. The single deep cross network model has some defects in music recommendation, such as poor stability and inability to process complex data. To overcome the shortcomings of existing models, a new hybrid music recommendation model combining CatBoost algorithm and deep cross network is constructed to improve the recommendation performance and better meet the individual needs of users. Then the performance of the hybrid model is compared with other algorithms. The results showed that the accuracy of the proposed hybrid algorithm was up to 92.7%, which was superior to the comparison algorithm. In comparison with other single model and hybrid model, it is found that the proposed model was more than 0.05% higher than other models in the four indices of AUC area, accuracy, precision and recall. The above results showed that the proposed hybrid music recommendation model could efficiently process data information and provide users with accurate personalized music recommendation. This study not only promoted the development of music consumption and creation, but also found that the CatBoost-DCN hybrid model was significantly effective in improving recommendation performance. This finding provides a more efficient recommendation strategy for music platforms and has far-reaching significance for improving user experience and satisfaction. [ABSTRACT FROM AUTHOR]

A new energy vehicle cab control platform based on human-computer interaction is proposed from control device design and control signal acquisition design. A driving mode conversion algorithm based on the threshold is combined with the existing intelligent vehicle driving mode conversion. The MATLAB and Python hybrid program is used to realize the simulation experiment of the driving control algorithm of new energy vehicles. The system can conduct interactive simulations of various typical driving scenarios. Data acquisition and dynamic display functions can present the operating status of new energy vehicles most directly and efficiently. The system can integrate and intelligently process vehicle driving data, road environment data and external data from multiple dimensions of the "vehicle-road-network". The experimental results show that the system enhances the user experience of new energy vehicles and improves the efficiency of human-computer interaction. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Ekonomi Manajemen Sistem Informasi (JEMSI) is the property of Dinasti Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

INTRODUCTION: The rapid development of virtual reality technology and the Internet of Things (IoT) has provided new possibilities for user experience, and a variety of new products have emerged, especially in the field of painting, where the combination of these two provides a new platform for innovative artistic expression. OBJECTIVES: This study takes IoT products in the art field as an example to analyze the user experience in virtual reality environments and the impact of technological innovations on IoT products, as well as to explore the potentials and limitations of this emerging form of products and forms of painting. METHODS: In this study, the author constructed a virtual reality painting environment, utilized IoT technology to collect data from the user's painting process, and combined quantitative and qualitative analysis methods to assess user experience and technological innovation comprehensively. RESULTS: In the virtual reality environment, the user experience was significantly improved, and the users were more immersed in the painting process and felt more robust creativity and expression. Meanwhile, the application of Internet of Things (IoT) technology also provides more possibilities for drawing; for example, using smartpens makes the drawing process more smooth and natural. CONCLUSION: IoT painting with user experience and technological innovation in a virtual reality environment can provide a new creative platform for artists and bring a richer artistic experience to the audience, showing the feasibility and broad prospect of IoT products based on a virtual reality environment. [ABSTRACT FROM AUTHOR]

ChatGPT, a large language model, has become increasingly popular, and students have begun to use it for the purpose of learning. The purpose of this research is to explore the experiences of undergraduate English language and literature students from Bangladesh who are using ChatGPT. Qualitative research methods were utilized for this study and the data were collected using semi-structured interviews. A thematic analysis technique was employed to analyze the data. The study reveals both positive and negative experiences associated with the use of ChatGPT by students from the English Language and Literature department. ChatGPT helps students to practice their reading and writing skills. It aids them to provide literary explanations of their texts and helps students to understand complex literary texts in lucid language. However, it sometimes provides confusing or wrong answers and provides wrong explanations regarding literary texts. As students possess some negative experiences along with many positive experiences, they are inclined to continue using it with heightened awareness of their use. However, users in this study believe that its use should be limited, and it should be used as a complement rather than a primary tool. The findings of this research may provide educators and policymakers with valuable insights that might help them integrate new aspects of artificial intelligence in education. [ABSTRACT FROM AUTHOR]

Communication technology plays a crucial role in facilitating remote collaborative work. This study investigated sex differences in Perceived Participation Equality and User Experience across different communication formats, i.e., face-to-face communication, conventional video conferences, and Virtual Reality (VR). An empirical study was conducted involving 15 groups, each comprising three participants, who engaged in a decision-making task. A research model was developed to evaluate the interplay between perceived participation equality, empathy, and immersion. This model was employed across three communication conditions and included both male and female participants. These findings on sex differences in user experience could help create a connected, cohesive, and productive remote collaborative work environment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With advancements in autonomous driving technology, the variety of activities that can be performed in a vehicle has increased. This improves the possibility of watching virtual reality (VR) content on a head-mounted display (HMD). However, unlike VR used in stationary environments, in-car VR can lead to discomfort and motion sickness due to the vehicle movements. Additionally, the obstruction of the outside view during driving may cause user anxiety. In this study, we investigated, for the first time, the effect of dynamic road environments, such as turns, stops, and speed bumps, on the in-car VR experience. Based on our findings, we included situational awareness (SA) cues in the in-car VR content to help users perceive their surroundings and improve the user experience. We conducted a user study with thirty participants to validate the impact of these cues. Consequently, we discovered that the Dynamics cue, which provides SA information while maintaining the context of the VR content, improves user immersion and trust while easing VR motion sickness. [ABSTRACT FROM AUTHOR]

The intense competition amongst travel apps, regardless of their popularity, has made repurchase intention a critical financial challenge for travel providers. By combining the Stimulus-Organism-Response (S-O-R) framework and the New Economic Geography (NEG) theory, this research examined how city tier disparities influence the experiential features of travel apps and user repurchase intentions. Survey data was acquired from 739 travel app users in China. The findings indicate that a set of context-based experiential features significantly influences utilitarian and hedonic values, and consequently leading to a notable increase in repurchase intentions. In addition, the outcomes of a multigroup analysis revealed that China's users located in tier 1 city (i.e. Beijing) and tier 3 city (i.e. Kunming) had distinct effects on the hypothesised relationships. Theoretically, the research provides extensive implications to information systems and tourism literatures; whilst offering some actionable insights to travel practitioners. [ABSTRACT FROM AUTHOR]

Essays are one of the most used exams to assess students. Universitas Terbuka Indonesia (Open University) conducts three online essay exams within a week for each first-year course, accounting for 30% of the mid-test score. The university has over 500.000 students and hundreds of courses. However, the limited number of correctors resulted in a time-consuming and ineffective process of checking and scoring each student's essay response. Even score results can be subjective, unfair, lack detailed feedback from students, miss contextual and creative aspects, and be less reliable with complex or non-standard writing. This research proposes a hybrid approach of deep learning models and natural semantic grammar to improve and optimize an AES system, with the following steps: First, the datasets are collected from hundreds of students' answers, each representing a single question. The datasets are pre-processed and augmented to enhance the quantity and variety of the original data and scores. Second, the BERT approach was utilized to transform each text dataset into vector feature spaces using pre-trained model weights. Finally, a prediction score model was generated using the BiLSTM method. The experiment's results show that the model had an average Cohen's Kappa score of 0.749 and the highest Cohen's Kappa score of 0.91. This BERT-BiLSTM optimization model also has a better Cohen's Kappa Score average (0.820) than the ATT-CNN-LSTM, BERT-XLNET, R2BERT, and CNNBiLSTM models. After conducting a test on 46 lecturers, the results showed that the average time taken to examine one course for each student decreased to 1 minute and 2 seconds. Additionally, 92.75% of the lecturers found the process of checking responses to be fairer and more objective. In the results of the trial with 200 students, the mean percentage of question indications related to UI/UX, fairness, responsiveness, rubric, feedback, and transparency across students was 93.72%. [ABSTRACT FROM AUTHOR]

This paper investigates the ramifications of information feed integration on user engagements and contributions in online content-sharing platforms by exploiting a natural experiment occurred in a leading knowledge-sharing platform that integrated informal social posts with professional knowledge content in one feed. Our results show that the juxtaposition of incongruous types of content increased mindset switching and cognitive strain, thus hurting user engagements. We also reveal a novel crowding-out effect, viz., the integration heightened concerns that posting informal social posts would dilute the contributor's professional image, thus inhibiting user contributions. Our findings hold important practical implications for all platforms that host (or are considering hosting) diverse types of user-generated content (UGC). Additional content curation tools can potentially enhance user engagement and retention, but their effectiveness hinges on a foundational and crucial element—the presentation format of heterogeneous content types. Essentially, the value of curating informal social posts in a knowledge-sharing platform would diminish when those content intrudes upon and conflict with the professional domain. This insight underscores that any UGC platforms, when adopting a diversity-oriented strategy, should pay close attention to heterogeneity between different content types for the purpose of optimizing user experiences and promoting user contributions. Many online communities that rely on effortful, voluntary content contributions offer additional content curation tools to facilitate social interactions and encourage user contributions. Any platform that offers two or more heterogeneous content types (e.g., expert knowledge and social posts) faces a choice about the presentation format: whether to display the content types separately or in an integrated information feed. We leverage a natural experiment on Zhihu, a Q&A platform that offers a social-interaction-oriented functionality called Ideas. Zhihu initially presented answers (expert knowledge content) and ideas (social posts) in two different information feeds, but the platform integrated ideas into the same information feed as answers in June 2019. We find that information feed integration significantly decreased user engagement with and contribution of both ideas and answers. We hypothesize that users decreased their engagement because the juxtaposition of incongruous types of content increased mindset switching and cognitive strain. This hypothesis is supported by an additional laboratory experiment. We also present evidence showing that contributions decreased both because of the decrease in engagement (weaker social recognition incentives) and because integration heightened concerns that posting ideas would dilute the contributor's professional image. Our findings have important theoretical and practical implications for any platform that hosts heterogeneous content. History: Xiaoquan (Michael) Zhang served as the senior editor and Yili (Kevin) Hong served as associate editor for this article. Funding: Z. Cao acknowledges this research was funded by National Natural Science Foundation of China [Grants 72201238, 72192823]. G. Li acknowledges this research was funded by National Natural Science Foundation of China [Grant 72102047] and Shanghai Pujiang Program [Grant 21PJC006]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2022.0043. [ABSTRACT FROM AUTHOR]

The healthcare sector has undergone a profound transformation, owing to the influential role played by Internet of Medical Things (IoMT) technology. However, there are substantial concerns over these devices' security and privacy-preserving mechanisms. The current literature on IoMT tends to focus on specific security features, rather than wholistic security concerning Confidentiality, Integrity, and Availability (CIA Triad), and the solutions are generally simulated and not tested in a real-world network. The proposed innovative solution is known as Secure-by-Design Real-Time IoMT Architecture for e-Health Population Monitoring (RTPM) and it can manage keys at both ends (IoMT device and IoMT server) to maintain high privacy standards and trust during the monitoring process and enable the IoMT devices to run safely and independently even if the server is compromised. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices' overheads, and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system, i.e., the CIA Triad, and conducts device authentication, protects from Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks, and prevents non-repudiation attacks in real time. A self-healing solution during the network failure of live e-health monitoring is also incorporated in RTPM. The robustness and stress of the system are tested with different data types and by capturing live network traffic. The system's performance is analysed using different security algorithms with different key sizes of RSA (1024 to 8192 bits), AES (128 to 256 bits), and SHA (256 bits) to support a resource-constraint-powered system when integrating with resource-demanding secure parameters and features. In the future, other security features like intrusion detection and prevention and the user's experience and trust level of such a system will be tested. [ABSTRACT FROM AUTHOR]

Progress in machine learning technology has truly impacted our lives by tailoring many of our daily experiences to be seamless and intuitive. This innovation has brought about changes in day-to-day routines; from suggesting music based on our emotions to offering recommendations for places to visit or meals to try out. This special issue explores various Machine Learning technologies. Among some are Machine Learning advances that improve human interaction, predict user behaviours, analyse user reviews, and optimize high-risk investments like Bitcoin trading. These technologies enhance user experiences, help businesses refine marketing strategies, and provide quick insights from vast amounts of information, elevating AI to new heights. With the rise of transformation into advanced technologies taking prominence in our lives, we expect to see these machine learning innovations being integrated across many sectors and uses. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the problem of monitoring network latency. Indeed, latency is a key network metric related to both network performance and quality of service, since it directly impacts on the overall user's experience. High latency leads to unacceptably slow response times of network services, and may increase network congestion and reduce the throughput, in turn disrupting communications and the user's experience. A common approach to monitoring network latency takes into account the frequently skewed distribution of latency values, and therefore specific quantiles are monitored, such as the 95th, 98th, and 99th percentiles. We present a comparative analysis of the speed of convergence of the sequential FRUGAL-1U, FRUGAL-2U, and EASYQUANTILE algorithms and the design and analysis of parallel, message-passing-based versions of these algorithms that can be used for monitoring network latency quickly and accurately. Distributed versions are also discussed. Extensive experimental results are provided and discussed as well. [ABSTRACT FROM AUTHOR]

Greenways are an important component of urban green infrastructure. User experiences and visual preferences are highly related to human well-being. The influencing factors of user experience and the relationship between environmental attributes with visual preference were explored by using the analytic hierarchy process method and questionnaire experiments. In this study, the analytic hierarchy process was conducted to construct the users' experience evaluation system, and three methods were used to reveal the influencing factors of the users' experience in the Mulan River greenway, China. The connection between visual perception and environmental attributes was also identified. The results show that the site leveling, plant landscape aesthetics, and air quality are the main factors affecting user experience. The most significant factor influencing visual preference is the green view index. The green view index can promote visual preference within 60%. Various environmental features contribute to visual preference, providing quantitative support for enhancing landscape quality. This research reveals the factors of visual preference that contribute to forming scientific recommendations for the management and quality improvement of the Mulan River greenway. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high production cost, low user experience satisfaction, and difficulty in meeting consumers' individual needs in traditional down garment sewing due to the time- consuming and time-consuming process and the difficulty in quickly and intuitively feeling the dressing effect, a down jacket was taken as the research object and 3D virtual sewing was completed with Style3D modeling software, the sewing technology was improved and optimized, and the effective and feasible virtual sewing technology measures for down garments were discussed. The results show that the method of directly generating the lining layer can effectively reduce the virtual sewing time; choosing the appropriate type sewing will result in a cleaner sewing effect for clothing; the convenient filling effect can be achieved by cutting the bottom hem of down jacket separately; the double-layer folding effect of the cuffs can reduce collision detection time and improve simulation fidelity by cutting into a single layer, and increasing the additional rendering thickness of the fabric. The research results aim to provide reference for virtual setting, efficient simulation, and realistic display of similar types of clothing. [ABSTRACT FROM AUTHOR]

Smartphones have emerged as ubiquitous platforms for people to consume content in a wide range of consumption contexts (C2), e.g., over cellular or WiFi, playing back audio and video directly on phone or through peripheral devices such as external screens or speakers. In this article, we argue that a user's specific C2 is an important factor to consider in Adaptive Bitrate (ABR) streaming. We examine the current practices of using C2 in five popular ABR players, and identify various limitations in existing treatments that have a detrimental impact on network resource usage and user experience. We then formulate C2-cognizant ABR streaming as an optimization problem and develop practical best-practice guidelines to realize it. Instantiating these guidelines, we develop a proof-of-concept implementation in the widely used state-of-the-art ExoPlayer platform and demonstrate that it leads to significantly better tradeoffs in terms of user experience and resource usage. Last, we show that the guidelines also benefit dash.js player that uses an ABR logic significantly different from that of ExoPlayer. [ABSTRACT FROM AUTHOR]

This article presents the results of an empirical study that aimed to investigate the influence of various types of audio (spatial and non-spatial) on the user quality of experience (QoE) of and visual attention in 360° videos. The study compared the head pose, eye gaze, pupil dilations, heart rate, and subjective responses of 73 users who watched ten 360° videos with different sound configurations. The configurations evaluated were no sound; non-spatial (stereo) audio; and two spatial sound conditions (first- and third-order ambisonics). The videos covered various categories and presented both indoor and outdoor scenarios. The subjective responses were analyzed using an ANOVA (Analysis of Variance) to assess mean differences between sound conditions. Data visualization was also employed to enhance the interpretability of the results. The findings reveal diverse viewing patterns, physiological responses, and subjective experiences among users watching 360° videos with different sound conditions. Spatial audio, in particular third-order ambisonics, garnered heightened attention. This is evident in increased pupil dilation and heart rate. Furthermore, the presence of spatial audio led to more diverse head poses when sound sources were distributed across the scene. These findings have important implications for the development of effective techniques for optimizing processing, encoding, distributing, and rendering content in virtual reality (VR) and 360° videos with spatialized audio. These insights are also relevant in the creative realms of content design and enhancement. They provide valuable guidance on how spatial audio influences user attention, physiological responses, and overall subjective experiences. Understanding these dynamics can assist content creators and designers in crafting immersive experiences that leverage spatialized audio to captivate users, enhance engagement, and optimize the overall quality of VR and 360° video content. The dataset, scripts used for data collection, ffmpeg commands used for processing the videos, and the subjective questionnaire and its statistical analysis are publicly available. [ABSTRACT FROM AUTHOR]

While the topic of investigating user experience with immersive services, such as Social Virtual Reality (VR), is starting to gain traction in the research community, the unique case of multiplayer VR games requires a more specific approach. Attempts to investigate user experiences with this complex, multidimensional service are hindered by the absence of specific standards and guidelines going beyond what we know about non-immersive gaming. In this article, we present the results of a user study (N = 32) exploring participants' experience of playing two competitive VR games of different genres (shooter, sports game), as we focus on three distinct facets of multiplayer VR gaming—network, interpersonal competitiveness, and social interaction. Furthermore, approaching the issue from the perspective of Quality of Experience researchers looking to conduct future user studies on the topic, we also present our findings as a way to shed light on factors that need further consideration, especially in the context of participant recruitment and methodology design, such as the choice of access network to be used for testing, and the issue of matchmaking study participants based on skill and prior relationship. [ABSTRACT FROM AUTHOR]

360-degree video is an emerging form of media that encodes information about all directions surrounding a camera, offering an immersive experience to the users. Unlike traditional 2D videos, visual information in 360-degree videos can be naturally represented as pixels on a sphere. Inspired by state-of-the-art deep-learning-based 2D image super-resolution models and spherical CNNs, in this article, we design a novel spherical super-resolution (SSR) approach for 360-degree videos. To support viewport-adaptive and bandwidth-efficient transmission/streaming of 360-degree video data and save computation, we propose the Focused Icosahedral Mesh to represent a small area on the sphere. We further construct matrices to rotate spherical content over the entire sphere to the focused mesh area, allowing us to use the focused mesh to represent any area on the sphere. Motivated by the PixelShuffle operation for 2D super-resolution, we also propose a novel VertexShuffle operation on the mesh and an improved version VertexShuffle_V2. We compare our SSR approach with state-of-the-art 2D super-resolution models and show that SSR has the potential to achieve significant benefits when applied to spherical signals. [ABSTRACT FROM AUTHOR]

This systematic literature review aimed to assess the methodological quality of user-centered usability evaluation of digital applications to promote citizens' engagement and participation in public governance by (i) systematizing their purposes; (ii) analyzing the evaluation procedures, methods, and instruments that were used; (iii) determining their conformance with recommended usability evaluation good practices; and (iv) identifying the implications of the reported results for future developments. An electronic search was conducted on Web of Science, Scopus, and IEEE Xplore databases, and after a screening procedure considering predefined eligibility criteria, 34 studies were reviewed. These studies performed user-centered usability evaluation of digital applications related to (i) participatory reporting of urban issues, (ii) environmental sustainability, (iii) civic participation, (iv) urban planning, (v) promotion of democratic values, (vi) electronic voting, and (vii) chatbots. In terms of the methodological quality of the included studies, the results suggest that there is a high heterogeneity of the user-centered usability evaluation. Therefore, there is a need for recommendations to support user-centered usability evaluations of digital applications to promote citizens' engagement and participation in public governance to improve the planning and conduction of future research. [ABSTRACT FROM AUTHOR]

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Smart home technologies have evolved significantly since the 1970s, with recent advancements in Internet of Things (IoT) and cloud computing revolutionizing home automation. However, current systems face challenges in achieving seamless cloud integration, ensuring interoperability, and maintaining robust security. This paper addresses these issues by proposing an innovative cloud-integrated smart home system designed for the Nigerian market. The research aimed at developing a system that optimizes energy consumption, enhances user experience, and implements robust security measures. Specific objectives included: creating a coded interface with a cloud database, designing a Wi-Fi-connected smart home system, and building a system with enhanced home security through user authentication. The methodology employed an ESP32 microcontroller for wireless connectivity and real-time functionality, integrated with the Arduino platform and a GSM system for SMS alerts. The system utilized Wi-Fi for interconnecting sensors and the database, allowing smartphone control through a user-friendly mobile application. Constrained Application Protocol (CoAP) was implemented for efficient data transfer between constrained devices. The results demonstrated significant improvements over traditional systems, including extended range and scalability, more reliable communication, stronger security through cloud storage and encryption, enhanced interoperability with various smart home devices and cost-effectiveness. The system showed substantial energy savings through intelligent control of home appliances. The paper concludes a well-rounded framework for the ongoing development and evaluation of smart home systems tailored to user needs, while fortifying security. The system's affordability, ease of use and energy efficiency make it particularly suitable for the Nigerian market and similar emerging markets. This study contributes valuable insights for developers, industry standards and policymakers, underpinning the vision of universally adopted, secure and sustainable smart homes. [ABSTRACT FROM AUTHOR]

ObjectivesMethodsResultsConclusionsClinical ImplicationsThis qualitative study examines the experiences of older adults with Empower@Home, an older adult-centered, layperson-supported internet-based cognitive behavioral therapy (iCBT) program for depression, with a focus on engagement-related factors.Adults aged 50 or older with at least mild depressive symptoms were recruited from multiple resources. A random subset of participants was invited for a semi-structured qualitative interview during a post-intervention assessment conducted over the phone (N = 148). Interviews were recorded and transcribed verbatim. Transcripts were coded in a multi-phase, team-based approach utilizing inductive coding techniques, followed by thematic analysis to identify key themes.Six key themes regarding engagement emerged: the importance of a structured, skills-based, and self-paced approach; the essential role of weekly coaching for accountability, web interface’s ease of use and accessibility; narrative engagement dynamics; enhanced learning through multimodal instruction; and tailoring challenges in iCBT.Older adult-centered, layperson-supported, and multimodal iCBT can effectively engage older adults in managing their mental health.iCBT programs can be integrated into various community aging settings. By leveraging each setting’s strengths and involving a range of professionals, these programs can play an important role in enhancing older adults’ mental health. [ABSTRACT FROM AUTHOR]

AbstractWomen are increasingly turning to mHealth apps as primary sources for breastfeeding education and support. The rising prevalence of mHealth apps presents a unique opportunity to explore their impact on women’s breastfeeding experiences. Understanding user perspectives of these apps, especially focusing on their persuasive design aspects, can offer valuable insights for enhancing maternal and child health outcomes. These insights can optimize these technologies to align with user values and promote sustained healthy behaviors. This study aimed to undertake an empirical exploration of users’ experiences with the persuasive design features employed in the Milky Way mHealth app and align the findings with human values within the value-sensitive design (VSD) framework. Semi-structured interviews were conducted with a group of women who had used the Milky Way app. Interview data were analyzed using an inductive thematic approach. To provide insight into users’ values mediated by the app, a deductive analysis complemented by a data-driven inductive approach was performed. Data analysis was supported by NVivo data-management software. Findings from the study demonstrate that the persuasive design elements in the Milky Way app significantly influence users’ experiences. The analysis provided four primary themes: Informative, Easy to use, Credible, and Social connection. Overall, participants praised the app’s trustworthy educational content and support features as valuable resources for addressing breastfeeding challenges and obtaining reliable support. Participants expressed concerns about information overload and emphasized the importance of personalized support and evidence-based tailored recommendations. The results demonstrated that users’ values were expressed and embedded within the app. The analysis indicated an alignment between the app design features and the values and opinions of the users within the VSD framework. This study interprets women’s perspectives utilizing the Milky Way app and highlights the significance of its evidenced-based educational and support features. Further investigation into potential user values like privacy, remains crucial for a comprehensive user-centered app design. The empirical insights gained from this study contribute to future research, informing the development and design of ethically considerate persuasive mHealth apps to maintain their relevance in promoting positive user experiences and facilitating meaningful behavior change. [ABSTRACT FROM AUTHOR]

Background: The principles of dynamic consent are based on the idea of safeguarding the autonomy of individuals by providing them with personalized options to choose from regarding the sharing and utilization of personal health data. To facilitate the widespread introduction of dynamic consent concepts in practice, individuals must perceive these procedures as useful and easy to use. This study examines the user experience of a dynamic consent-based application, in particular focusing on personalized options, and explores whether this approach may be useful in terms of ensuring the autonomy of data subjects in personal health data usage. Methods: This study investigated the user experience of MyHealthHub, a dynamic consent-based application, among adults aged 18 years or older living in South Korea. Eight tasks exploring the primary aspects of dynamic consent principles–including providing consent, monitoring consent history, and managing personalized options were provided to participants. Feedback on the experiences of testing MyHealthHub was gathered via multiple-choice and open-ended questionnaire items. Results: A total of 30 participants provided dynamic consent through the MyHealthHub application. Most participants successfully completed all the provided tasks without assistance and regarded the personalized options favourably. Concerns about the security and reliability of the digital-based consent system were raised, in contrast to positive responses elicited in other aspects, such as perceived usefulness and ease of use. Conclusions: Dynamic consent is an ethically advantageous approach for the sharing and utilization of personal health data. Personalized options have the potential to serve as pragmatic safeguards for the autonomy of individuals in the sharing and utilization of personal health data. Incorporating the principles of dynamic consent into real-world scenarios requires remaining issues, such as the need for powerful authentication mechanisms that bolster privacy and security, to be addressed. This would enhance the trustworthiness of dynamic consent-based applications while preserving their ethical advantages. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: While mobile-linked point-of-care diagnostics may circumvent geographical and temporal barriers to efficient communication, the use of such technology in community settings will depend on user experience. We conducted a scoping review to systematically map evidence on user experiences of mobile-linked point-of-care diagnostics in community healthcare settings published from the year 2016 up to the year 2022. Methodology: We conducted a comprehensive search of the following electronic databases: Scopus, Web of Science, and EBSCOhost (Medline, CINAHL, Africa-wide, Academic Search Complete). The inter-reviewer agreement was determined using Cohen's kappa statistic. Data quality was appraised using the mixed method appraisal tool version 2018, and the results were reported according to the preferred reporting items for systematic reviews and meta-analyses for scoping reviews (PRISMA-ScR). Results: Following the abstract and full article screening, nine articles were found eligible for inclusion in data extraction. Following the quality appraisal, one study scored 72.5%, one study scored 95%, and the remaining seven studies scored 100%. Inter-rater agreement was 83.54% (Kappa statistic = 0.51, p < 0.05). Three themes emerged from the articles: approaches to implementing mobile-linked point-of-care diagnostics, user engagement in community-based healthcare settings, and limited user experiences in mobile-linked point-of-care diagnostics. User experiences are key to the sustainable implementation of mobile-linked point-of-care diagnostics. User experiences have been evaluated in small community healthcare settings. There is limited evidence of research aimed at evaluating the usability of mobile-linked diagnostics at the community level. Conclusion: More studies are needed to assess the user experience of mobile-linked diagnostics in larger communities. This scoping review revealed gaps that need to be addressed to improve user experiences of mobile-linked diagnostics, including language barriers, privacy issues, and clear instructions. [ABSTRACT FROM AUTHOR]

Objective: Robotic arms are innovative assistive devices for ALS patients with progressive motor deficits of arms and hands. The objective was to explore the patients´ expectations towards a robotic arm system and to assess the actual experiences after the provision of the device. Methods: A prospective observational study was conducted at 9 ALS centers in Germany. ALS-related functional deficits were assessed using the ALS-Functional Rating Scale-revised (ALSFRS-R). Motor deficit of the upper limbs was determined using a subscore of three arm-related items of the ALSFRS-R (items 4–6; range 0–12 points). User expectations before provision (expectation group, n = 85) and user experiences after provision (experience group, n = 14) with the device (JACO Assistive Robotic Device, Kinova, Boisbriand, QC, Canada) were assessed. Results: In the total cohort, mean ALSFRS-R subscore for arm function was 1.7 (SD: 2.0, 0–9) demonstrating a severe functional deficit of the upper limbs. In the expectation group (n = 85), the following use cases of the robotic arm have been prioritized: handling objects (89%), close-body movements (88%), pressing buttons (87%), serving drinks (86%), and opening cabinets and doors (85%). In the experience group (n = 14), handling objects (79%), serving drinks (79%), near-body movements (71%), pushing buttons (71%), serving food (64%), and opening doors (64%) were the most frequent used cases. Most patients used the device daily (71.4%, n = 10), and 28.6% (n = 4) several times a week. All patients of the experience group found the device helpful, felt safe while using the device, and were satisfied with its reliability. NPS of the assistive robotic arm revealed 64% "promoters" (strong recommendation), 29% "indifferents" (uncertain recommendation) and 7% "detractors" (no recommendation). Total NPS was + 57 demonstrating strong patient satisfaction. Conclusions: Initiation of procurement with a robotic assistive arm was confined to patients with severe functional deficit of the upper limbs. User experience underlined the wide spectrum of use cases of assistive robotic arms in ALS. The positive user experience together with high satisfaction underscore that robotic arm systems serve as a valuable treatment option in ALS patients with severe motor deficits of the arms. [ABSTRACT FROM AUTHOR]

Real walking is considered as the best locomotion metaphor to explore virtual environments in terms of user experience. In addition to being intuitive for the user, walking captures the true feelings of motion since the visual and proprioceptive sensations are harmonized well. The major disadvantage of choosing walking over other locomotion metaphors involves the physical constraints of the available space, which is usually considerably smaller than the virtual environment. To address this issue, redirected walking (RDW) introduces slight mismatches between a user's visually perceived path and their actual walking pattern, compelling them to subconsciously compensate for the inconsistency by adjusting their walking trajectory. As a result, users are steered to a certain degree, and expansive virtual environments are effectively compressed into smaller physical spaces. Among others, particularly predictive RDW offers immense potential for growth since it unites various algorithmic systems, whereas many approaches from literature depend on drastic restrictions like single-user constraints or architectural limitations to ensure real-time performance. This work presents two novel predictive RDW systems that allow multiple physically colocated users to explore independent and unconstrained virtual environments. The systems rely on two new implementations of prediction systems based on clothoid trajectory generation combined with a cost-based planning concept built on nonharmonic artificial potential fields (APFs), which inherently allow non-convex and dynamic physical environments. Using the APFs, three additional RDW conditions popular in the literature are implemented for comparison purposes. The five RDW concepts are then validated in an extensive user study with 150 participants conducted in 75 pairs. The results indicate that the novel predictive RDW systems outperform the three systems from literature, except for particular sections of the virtual environment with specific architectural traits. [ABSTRACT FROM AUTHOR]

Background: Monitoring the recovery trajectory during and after hospitalization can be a valuable method to observe whether additional care is needed to optimize recovery. Hand grip strength tests are commonly used to measure an individual's physical condition. Eforto® is a system to monitor hand grip strength and grip work as measures of recovery. We examined the feasibility of daily repeated hand grip tests measured with Eforto® in geriatric inpatients, during hospitalization and at home after discharge. Methods: Geriatric inpatients (n = 191) were evaluated for grip strength and grip work with Eforto®, twice daily during their admission. We calculated attempt and success rates. Participants were divided into complete, high, moderate, and low attempt/success rate groups to study differences in patient characteristics. Reasons for non-attempt and unsuccessful tests were categorized and analyzed. Nine participants were interviewed about acceptability and user experience within the hospital setting. Four out of twenty participants accepted the invitation to continue the measurements after discharge at home for 4 weeks and were interviewed about acceptability and user experience. Results: Across the 191 participants, the attempt rate was 85% and 86% of the attempted tests was successful. The main reasons for non-attempt were that the patient felt physically unwell (41%), and that the patient was otherwise engaged, for example receiving care or undergoing medical tests (40%). Measurements were unsuccessful mostly because of the patient not having enough strength to reach the 80% threshold needed for the grip work test (60%). Participants in the complete and high attempt/success rate groups had a shorter length of stay (p<0.05) and a lower mortality (p<0.05) than participants in the moderate/low groups. The interview data showed good acceptability and user experience during hospitalization. The acceptability was strengthened by experienced usefulness. Self-monitoring at home resulted in low inclusion rate (20%) and low success rate (25%), with the uncertain time after discharge from the hospital as the main barrier. Conclusions: For most patients, the tests were feasible in the supervised hospital setting. At-home testing with Eforto® is challenging, primarily because of the uncertain time after discharge from the hospital. [ABSTRACT FROM AUTHOR]

AbstractSmart Predict is a novel two-tablet application developed to improve conversational efficiency for people who use augmentative and alternative communication (AAC) devices. The Smart Predict system consists of two distinct applications that were built for use with two Android tablets and/or phones with Bluetooth® capability. One application is referred to as the AAC User app and the second application is called the Partner app. Smart Predict integrates vocabulary supplementation from communication partners in real-time while persons who rely on AAC generate text and maintain full control to choose words within a word prediction line. Using single-case research designs with adapted alternating treatments under two counterbalanced treatment conditions (AAC User app alone versus AAC User app + Partner app), we examined message efficiency with persons who rely on switch scanning for on-screen keyboards. User experience questionnaires were administered to determine satisfaction and workload, and to provide feedback for future development efforts. Three adults with complex communication needs and motor impairments conversed with research staff about fourteen movie trailers. Characters per minute and switch selections per character produced by the person with complex communication needs and motor impairments were measured during 15-minute interviews to represent communication speed and effort. Results indicate that message efficiency increased with the dual-tablet Smart Predict, indicating faster message generation with the vocabulary supplementation system. User satisfaction increased and perceived effort decreased under the Smart Predict conditions. Given these results within a research and development framework, the Smart Predict concept is a viable feature that could be considered within smart AAC technologies. [ABSTRACT FROM AUTHOR]

In the vision of Industry 5.0, collaborative robots (or cobots) play a central supporting role in various industries, especially manufacturing. Close interaction with cobots requires special attention to user experience to fully exploit the benefits of this paradigm. Consequently, understanding the impact of a cobot's physical size on user experience becomes critical to optimizing human–robot collaboration (HRC). This research aims to investigate the relationship between cobot size (UR3e – small cobot vs. UR10e – large cobot) and user experience in HRC contexts, in conjunction with other factors (i.e., cobot movement speed and product assembly complexity). Through a series of controlled experiments involving 32 participants, user experience data were obtained by collecting physiological measures (i.e., electro-dermal activity, heart activity, eye-tracking metrics) and subjective responses with questionnaires (i.e., perceived workload, interaction quality, and affective state). Results showed that the large cobot was generally perceived to be safer, more natural, efficient, fluid, and trustworthy. With the large cobot, there was a decrease in dominance; however, it was offset by the learning effect. Perceived workload was mainly influenced by product complexity. No clear difference in terms of mental strain emerged from the physiological data comparing the cobot sizes. In addition, the interaction term between cobot size and cobot movement speed never emerged as significant. The results of this research can offer practical insights to improve the effectiveness and acceptance of cobots during the implementation phase. [ABSTRACT FROM AUTHOR]

Short video addiction refers to the uncontrollable desire of users to watch short videos, leading to significant behavioral loss of control or attention disorders, which in turn result in difficulties in social interaction, learning, and work adaptation. With the "invasion" of short videos into people's daily lives and their spread among underage groups, the issue of short video addiction has attracted widespread social attention. Firstly, based on the causes of short video addiction, this study analyzes it from four levels: algorithm design, content services, platform control, and user experience. Secondly, combining relevant scientific theories, the psychological mechanisms of short video addiction are explained from four levels: cognition, emotion, motivation, and social factors. Finally, in terms of coping strategies, on the theoretical level, further research on the occurrence mechanism of short video addiction should be deepened, and attention should be paid to the influence of recommendation algorithms on short video addiction. On the practical level, the obligations and responsibilities of relevant stakeholders such as short video producers, platforms, and regulators in preventing short video addiction should be clarified, aiming to promote prevention and management of short video addiction. [ABSTRACT FROM AUTHOR]

This study evaluates an innovative control approach to assistive robotics by integrating brain–computer interface (BCI) technology and eye tracking into a shared control system for a mobile augmented reality user interface. Aimed at enhancing the autonomy of individuals with physical disabilities, particularly those with impaired motor function due to conditions such as stroke, the system utilizes BCI to interpret user intentions from electroencephalography signals and eye tracking to identify the object of focus, thus refining control commands. This integration seeks to create a more intuitive and responsive assistive robot control strategy. The real-world usability was evaluated, demonstrating significant potential to improve autonomy for individuals with severe motor impairments. The control system was compared with an eye-tracking-based alternative to identify areas needing improvement. Although BCI achieved an acceptable success rate of 0.83 in the final phase, eye tracking was more effective with a perfect success rate and consistently lower completion times ( p < 0.001 ). The user experience responses favored eye tracking in 11 out of 26 questions, with no significant differences in the remaining questions, and subjective fatigue was higher with BCI use ( p = 0.04 ). While BCI performance lagged behind eye tracking, the user evaluation supports the validity of our control strategy, showing that it could be deployed in real-world conditions and suggesting a pathway for further advancements. [ABSTRACT FROM AUTHOR]

Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly. [ABSTRACT FROM AUTHOR]

User experience can change with time, and achieving a positive long-term user experience is an important goal in a successful product design. The long-term user experience of the interactive loading screen in Honor of Kings was studied by using two evaluation methods, UX Curve and QUIS questionnaire. The experiment included valid responses from a total of 23 participants. The results show that an interactive human-computer interface can achieve a good long-term waiting experience. It is also necessary to make changes to the UI or functions of the interactive screen after a period of time to ensure a good user experience. A toolbox including the QUIS questionnaire and UX Curve was proven effective in measuring the temporal aspects of user experience of the computer interface. The findings obtained in the experiments help understand the long-term user experience of human-computer interfaces. They may also provide a reference for developing different long-term user experience evaluation methods in different product contexts. [ABSTRACT FROM AUTHOR]

The wearable device market is growing rapidly, as evidenced by the growth in sales of smartwatches. However, these have a tiny touch screen so users cannot perform complex operations with a smartwatch. Few studies address the user experience of gestures to interact with wearable devices. This study uses a bone-conduction smartwatch to study the user experience of gestures for interaction with a wearable device in terms of four dimensions: pragmatic quality, hedonic quality–identification and hedonic quality–stimulation and attractiveness. Task loads ae also evaluated for further analysis of the user experience This study determines the relationship between these factors to determine the effect of using hand gestures to interact with wearable devices. The results of this study show that all of the users easily accept gesture interaction with wearable devices. Pragmatic quality, hedonic quality–identification and hedonic quality–stimulation are positively associated with attractiveness. A higher level of attractiveness reduces the perceived task load. Attractiveness has a significant positive effect on performance and task load has a significant negative effect on performance. [ABSTRACT FROM AUTHOR]

With the economy and 5G technology, users increasingly seek a good user experience. The latency issue of data transmission is a key concern for Application Vendor (AV). AV usually deploy data copies on Edge Server (ES) closer to the user's end to provide more convenient services. However, ensuring the integrity and detecting unauthorized data modification or data corruption in time is the key to the scheme. First, the EDI-A scheme is proposed to achieve multi-copy authentication for a single file. Then, the EDI- A is extended to allow AV to validate batch audits of multiple raw data simultaneously. Second, the use of I -SLT to enable EDI-A to support complete data dynamics. Finally, the security assessment proves that EDI-A is secure. [ABSTRACT FROM AUTHOR]

With the development of the Internet and mobile Internet, live streaming e-commerce has become an emerging e-commerce force. However, traditional recommendation algorithms have shortcomings in terms of accuracy and personalization of recommendation results, and more intelligent and personalized recommendation algorithms need to be applied. This article aimed to achieve personalized product recommendations and enhance the shopping experience of users by analyzing their historical behavioral data, real-time interests and needs, combined with big data and artificial intelligence technology. The collaborative filtering recommendation algorithm based on live streaming had an average recommendation accuracy of over 80% for user groups 1, 2, and 3. The research results of this article had important practical significance for promoting the healthy development of live streaming e-commerce platforms, improving user experience, and enhancing platform competitiveness. [ABSTRACT FROM AUTHOR]

The comprehensive performance and user experience of large-scale distributed video conference systems are constrained by network traffic, and conventional network services are difficult to ensure the stability and reliability of the above data transmission activities. This article combines conference video transmission and congestion control related technologies to propose a conference video traffic prediction model based on the large neural network GRU algorithm, and constructs a large-scale distributed video conference transmission congestion control mode on this basis. The simulation experiments on the real-time congestion control model of research results show that it effectively avoids system fluctuations and significantly improves the user experience, providing a feasible method for improving the comprehensive performance of large-scale distributed video conference systems. [ABSTRACT FROM AUTHOR]

With the rapid development of science and technology, especially the rapid progress of the Internet, the e-commerce industry has ushered in unprecedented development opportunities. However, existing e-commerce platforms still have many problems in terms of user experience and functionality, such as the lack of accuracy in the recommendation system, inconsistency in product descriptions, and lack of reliability in user reviews. In this paper, we design and implement an online shopping mall system based on Spring Boot and Vue framework, aiming to improve user experience through advanced information technology and optimization algorithms. The system is developed in Java language, and the architecture is divided into Filter/Interceptor Layer, Controller Layer, Service Layer, and Dao Layer, which ensures the efficiency and maintainability of the system. The introduction of collaborative filtering algorithms significantly improves the accuracy of product recommendations, provides personalized services, and improves the user shopping experience. Meanwhile, the dynamically updated sensitive word filtering mechanism safeguards the healthy environment of the comment area and improves user trust. The experimental results show that the system achieves the expected goals in terms of functionality and performance, which provides a reference and reference for the development of future e-commerce platforms. [ABSTRACT FROM AUTHOR]

Brain-computer interfaces (BCI) enable users to control devices through their brain activity. Motor imagery (MI), the neural activity resulting from an individual imagining performing a movement, is a common control paradigm. This study introduces a user-centric evaluation protocol for assessing the performance and user experience of an MI-based BCI control system utilizing augmented reality. Augmented reality is employed to enhance user interaction by displaying environment-aware actions, and guiding users on the necessary imagined movements for specific device commands. One of the major gaps in existing research is the lack of comprehensive evaluation methodologies, particularly in real-world conditions. To address this gap, our protocol combines quantitative and qualitative assessments across three phases. In the initial phase, the BCI prototype's technical robustness is validated. Subsequently, the second phase involves a performance assessment of the control system. The third phase introduces a comparative analysis between the prototype and an alternative approach, incorporating detailed user experience evaluations through questionnaires and comparisons with non-BCI control methods. Participants engage in various tasks, such as object sorting, picking and placing, and playing a board game using the BCI control system. The evaluation procedure is designed for versatility, intending applicability beyond the specific use case presented. Its adaptability enables easy customization to meet the specific user requirements of the investigated BCI control application. This user-centric evaluation protocol offers a comprehensive framework for iterative improvements to the BCI prototype, ensuring technical validation, performance assessment, and user experience evaluation in a systematic and user-focused manner. [ABSTRACT FROM AUTHOR]

Human–Machine Interaction (HMI) systems are integral to various domains and rely on human operators for effective performance. The sense of agency (SoA) is crucial in these systems, as it influences the operator's concentration and overall efficiency. This review explores the SoA in HMI systems, analyzing its definition, key influencing factors, and methods for enhancement. We provide a comprehensive examination of SoA-related research and suggest strategies for measuring and improving the SoA. Two key research directions are highlighted: the impact of user experience on the SoA, and the role of the SoA in enabling unconscious communication between humans and machines. We propose a development route for HMI systems, outlining a progressive structure across three stages: machine-centric, human-centric, and human–machine integration. Finally, we discuss the potential of gaming platforms as tools for advancing SoA research in HMI systems. Our findings aim to enhance the design and functionality of HMI systems, ensuring improved operator engagement and system performance. [ABSTRACT FROM AUTHOR]

The commercialisation of virtual reality (VR) headsets has made them more affordable and popular in gaming and entertainment. The natural interaction between the VR environment and users can maximise immersion and is crucial to VR gaming. Despite their growing popularity, educational VR games prioritise learning over immersion and require users to learn to interact with and play games using tutorials. Herein, we developed a game named Numverse with an accompanying tutorial. After selecting the tutorial content, we programmed the user interface and proposed a delivery method for the tutorial. We evaluated the user experience based on the effects of the presence or absence of the tutorial and its mode of delivery. The tutorials were of three types: no tutorial, instruction-screen tutorial, and context-sensitive tutorial, with the latter being the most preferred. The evaluation results show that presence, ability to learn controls, intrinsic motivation, and learning effectiveness are higher for the instruction-screen and context-sensitive tutorials than for no tutorial. On average, users experienced more motion sickness in the no-tutorial case, with a significant difference in nausea items. This study asserts the importance of tutorials in VR games, and its findings could improve user experience in future VR games. [ABSTRACT FROM AUTHOR]

The introduction of exoskeletons by many companies has often resulted in potential users not wanting to wear them. Evaluations of the exoskeleton reveal benefits of use, including ergonomic advantages and a reduction of work-related musculoskeletal disorders. How can this contradiction be explained? By searching the available literature, we can identify the methods used to develop these devices and the methods employed to evaluate their acceptance and benefit. By looking at the product from different viewpoints and involving different disciplines, we will get to the root of this discrepancy. Our findings indicate that the product definition, development focus, and evaluation methods do not sufficiently and adequately address the primary goal of exoskeletons. The development of such devices should be prioritized not only for the delivery of support but also for the motivation of the user. Finally, we put forward the proposal to discuss the establishment of a novel development method for the prospective elaboration of exoskeletons. [ABSTRACT FROM AUTHOR]

Featured Application: Featured Application: The presented solution can allow for automated video quality assessment and quick and effective modelling of the video quality experienced by the user. The classical objective methods of assessing video quality used so far, apart from their advantages, such as low costs, also have disadvantages. The need to eliminate these defects results in the search for better and better solutions. This article proposes a video quality assessment method based on machine learning using a linear regression model. A set of objective quality assessment metrics was used to train the model. The results obtained show that the prediction of video quality based on a machine learning model gives better results than the objective assessment based on individual metrics. The proposed model showed a strong correlation with the subjective user assessments but also a good fit of the regression function to the empirical data. It is an extension and improvement of the efficiency of the classical methods of objective quality assessment that have been used so far. The solution presented here will allow for a more accurate prediction of the video quality perceived by viewers based on an assessment carried out using a much cheaper, objective method. [ABSTRACT FROM AUTHOR]

Recently, business sectors have focused on offering a wide variety of services through utilizing different modern technologies such as super apps in order to fulfill customers' needs and create a satisfactory user experience. Accordingly, studying the user experience has become one of the most popular trends in the research field due to its essential role in business prosperity and continuity. Thus, many researchers have dedicated their efforts to exploring and analyzing the user experience across social media, blogs, and websites, employing a variety of research methods such as machine learning to mine users' reviews. However, there are limited studies concentrated on analyzing super app users' experiences and specifically mining Arabic users' reviews. Therefore, this paper aims to analyze and discover the most important topics that affect the user experience in the super app environment by mining Arabic business sector users' reviews in Saudi Arabia using biterm topic modeling, CAMeL sentiment analyzer, and doc2vec with k-means clustering. We explore users' feelings regarding the extracted topics in order to identify the weak aspects to improve and the strong aspects to enhance, which will promote a satisfactory user experience. Hence, this paper proposes an Arabic text annotation framework to help the business sector in Saudi Arabia to determine the important topics with negative and positive impacts on users' experience. The proposed framework uses two approaches: topic modeling with sentiment analysis and topic modeling with clustering. As a result, the proposed framework reveals four important topics: delivery and payment, customer service and updates, prices, and application. The retrieved topics are thoroughly studied, and the findings show that, in most topics, negative comments outweigh positive comments. These results are provided with general analysis and recommendations to help the business sector to improve its level of services. [ABSTRACT FROM AUTHOR]

Background: The rise of a new generation of intelligent neuroprostheses, brain-computer interfaces (BCI) and adaptive closed-loop brain stimulation devices hastens the clinical deployment of neurotechnologies to treat neurological and neuropsychiatric disorders. However, it remains unclear how these nascent technologies may impact the subjective experience of their users. To inform this debate, it is crucial to have a solid understanding how more established current technologies already affect their users. In recent years, researchers have used qualitative research methods to explore the subjective experience of individuals who become users of clinical neurotechnology. Yet, a synthesis of these more recent findings focusing on qualitative methods is still lacking. Methods: To address this gap in the literature, we systematically searched five databases for original research articles that investigated subjective experiences of persons using or receiving neuroprosthetics, BCIs or neuromodulation with qualitative interviews and raised normative questions. Results: 36 research articles were included and analysed using qualitative content analysis. Our findings synthesise the current scientific literature and reveal a pronounced focus on usability and other technical aspects of user experience. In parallel, they highlight a relative neglect of considerations regarding agency, self-perception, personal identity and subjective experience. Conclusions: Our synthesis of the existing qualitative literature on clinical neurotechnology highlights the need to expand the current methodological focus as to investigate also non-technical aspects of user experience. Given the critical role considerations of agency, self-perception and personal identity play in assessing the ethical and legal significance of these technologies, our findings reveal a critical gap in the existing literature. This review provides a comprehensive synthesis of the current qualitative research landscape on neurotechnology and the limitations thereof. These findings can inform researchers on how to study the subjective experience of neurotechnology users more holistically and build patient-centred neurotechnology. [ABSTRACT FROM AUTHOR]