Diverse User Groups Research Articles

Cloud-Based Automatic Configuration and Disaster Recovery of Communication Systems Applied in Engineering Training

Network management and troubleshooting require not only a grasp of advanced concepts but also the development of analytical and problem-solving skills. To bridge this gap, this paper introduces a novel network administration system, DRACSC (Spanish acronym for device for automatic recovery and configuration of communication systems), designed for the automatic configuration and disaster recovery of communication equipment. This system transcends the limitations of current hardware and software solutions by combining their advantages, boasting portability, automated functions, and a cloud-based repository as its main features. The DRACSC system, undergoing a comprehensive large-scale evaluation involving diverse user groups across multiple institutions, was tested with 89 users, including students and teachers at educational centers and ICT (Information and Communication Technology) professionals. The benefits of the system were evaluated through a training program based on simulated real-world ICT environments, focusing on both quantitative results on the reduction in time to complete user tasks, as well as qualitative results on the interface and usability of the system. Statistical analysis, including Welch’s t-test on opinion surveys, indicated a significant increase in knowledge and understanding, demonstrating the system’s potential to enhance education and practice. Moreover, the evaluation shed light on the user experience, with positive impacts observed for learning and teaching implications. As a result, the study has verified that the system has the potential to significantly influence network management practices, enhancing both learning and professional application through improved efficiency and usability.

Transforming Libraries: The Impact of Artificial Intelligence

Artificial intelligence (AI) is revolutionising library services and enhancing user experience, creating a new era of efficiency, accessibility, and innovation. This editorial explores how AI reshapes the library landscape, ushering in a new generation of efficiency, accessibility, and innovation. The AI’s most notable contribution to libraries is the automation of routine tasks, cataloguing and organising; librarians can now rely on AI algorithms to streamline. It saves librarians valuable time engaging in intellectually stimulating activities and ensures a more accurate and organised library system. AI-driven systems can efficiently analyse vast amounts of data, leading to improved search functionalities and more seamless information retrieval for library patrons. Moreover, AI is instrumental in the personalisation of library services. Through machine learning algorithms, libraries can analyse user behaviour, preferences, and historical data to provide customised recommendations. This enhances the user experience by offering tailored suggestions for reading materials, resources, and services, making libraries more relevant and engaging for diverse user groups. Another essential role of AI in libraries is the development of virtual assistants. These digital assistants, powered by natural language processing and machine learning, can help library patrons navigate the catalogue system, answer queries, and even provide Realtime language translation service. Virtual assistants help libraries become more inclusive and accessible, reaching more audiences with diverse language backgrounds and information needs.

SensorHUB – a Novel, Open-source Software Stack for Enhanced Accessibility and Secure Interoperability in IoT Project Management

Abstract. The Internet of Things (IoT) seeks to achieve seamless device connectivity and data sharing, thereby enhancing automation, efficiency, and insights in various fields of application. By delivering real-time data, IoT is essential for systems that aim to model and map the physical world to digital formats, such as digital twins or metaverses. In the recent years, there has been a surge in high-quality commercial IoT products available to various sectors. However, these solutions often come with high costs and proprietary interfaces, which hinder seamless interoperability. For users seeking cost-effective and flexible solutions, open-source software and international standards present viable alternatives. Nonetheless, despite technological progress, the adoption of open and standardized IoT software solutions is still predominantly seen among technology-affine groups or within research and development initiatives. We propose the sensorHUB, a novel IoT stack, which builds upon the Open Geospatial Consortium’s (OGC) data standard SensorThings API and enhances existing solutions towards more accessible, production-oriented solutions for diverse application domains and user groups. Key features include the provision of a new, state-of-the-art graphical user interface for managing data flows and the access to related software modules, and a secure and flexible user and access management.

Redefining Hospital Accessibility: A Service Design Framework for Inclusive Healthcare

Abstract In the framework of becoming a carbon neutral city by 2030, Bologna faces challenges related to enhancing the quality and accessibility of its built environment to improve the quality of life and well-being of its residents. The IRCCS Azienda Ospedaliero-Universitaria Sant’Orsola Polyclinic is a key agent of change within this initiative. The hospital has initiated a comprehensive renovation project aligned with its commitment to the United Nations Sustainable Development Goals (SDGs), particularly SDG 3, which addresses Good Health and Well-being, and SDG 10, which addresses Reduce Inequalities. To address these goals, the hospital has engaged a research team from the University of Bologna to apply Service Design methodologies. The research aims to reshape accessibility and user experience systematically and sustainably, adhering to the principles of Design for All. The study maps diverse user groups, analyses circulation paths, and identifies physical and procedural barriers affecting vulnerable individuals, especially those with disabilities. The research introduces a novel approach by developing a comprehensive strategy rather than isolated solutions, focusing on interconnected accessibility services across pavilions. Dedicated hubs within each pavilion facilitate resource and support device exchange, improving users’ experiences. A pilot project, initially targeting wheelchair accessibility hubs, employs innovative technologies to enhance independent tool usage and monitor distribution and maintenance efficiently. The project is now entering a testing phase, during which the solution will be refined based on user feedback.

Centering accessibility, increasing capacity, and fostering innovation in the development of international eDNA standards

Environmental DNA (eDNA) includes a set of rapidly emerging technologies that have the potential to support environmental monitoring and biodiversity conservation through novel, non-invasive, cost-effective and democratic methods and tools. Meanwhile, eDNA researchers are developing international standards for eDNA technologies, methods and data outputs. For eDNA technologies to be accessible, useful and appropriate, we must ensure that any standards developed include a broad conception of users from around the world, a diversity of ecological contexts and locations and, most importantly, a realistic outlook on research capacities and infrastructure. In this article, we assemble perspectives on international standardisation of eDNA from a diverse and global group of users and experts from Africa, South America and the Pacific Islands. The authors of this article collaborated by answering and discussing a set of open-ended questions aimed at eliciting hopes, concerns and experiences regarding eDNA standards. The result is a set of emergent themes and a generative consensus to highlight the need for the creation of adaptable standards, the development of regional capacity, increased sensitising to data sovereignty and the viewing of standardisation as a global capacity-building activity.

Transforming Academic Libraries into Hubs of Innovation and Entrepreneurship: A Case Study of a New Library Model

In a data-driven era, academic libraries must evolve beyond traditional roles as spaces for reading and storing information resources to become platforms promoting learning, research, innovation, future skills, and entrepreneurship. Based on the triple helix model of innovation, this paper highlights the new library model in a case study aimed at transforming traditional academic library services into enterprising, innovation-driven activities. For over ninety years, Thammasat University Library has been located on Rattanakosin Island, an historical area of Thailand. More recently, the library business model has evolved to meet modern needs. This qualitative research uses a case study to explore library strategies to create space meeting requirements of diverse user groups: students, faculty, staff, alumni, businesspeople and the community, including older residents. Service innovations responding to user demands are prioritized by drawing on the expertise of librarians. These changes generate new revenue for the library and enhance the space design and use through the Life Space concept. Co-working spaces, learning areas, inspirational corners, and performance venues make the library a platform for inspiring creativity, learning, life enhancement, and business ventures. The Thammasat University Library has also become an innovative bridge linking university research with small and medium-sized enterprises (SMEs), facilitating knowledge transfer and research commercialization. These findings may serve as guidelines for academic libraries seeking to adapt the Library of Life approach to be centres catering to readers of all generations and stations in life.

Toward a personalized autonomous transportation system: Vision, challenges, and solutions

The fragmented design of Intelligent Transportation Systems creates isolated intelligent systems. Resource competition and information gaps are fierce and widespread, worsening traffic issues and degrading overall service levels. Therefore, empowered by advanced technologies, an evolution towards Autonomous Transportation System (ATS) is observed. This evolution aims to develop a collaborative and sustainable ecosystem, prompting interoperability within the cloud-edge-device continuum. It can, accordingly, dismantle internal resource barriers and achieve a systematic balance between demand and supply with less human intervention. Despite the promising vision of ATS, it encounters three key challenges: disparate data, deficient models, and conflicting interests in supporting autonomous and personalized mobility. Hence, as an innovative solution, a trustworthy, private, and equal-serving framework called TPE is designed. It seamlessly integrates Blockchain, Federated Learning, and Large-scale Model to deploy a trustworthy operating environment, process private data for globally shareable knowledge, and develop a foundation model for personalized adaptation, respectively. Consequently, ATS empowered by TPE can serve diverse user groups both privately and equally.

Exploring the Effectiveness of Shallow and L2 Learner-Suitable Textual Features for Supervised and Unsupervised Sentence-Based Readability Assessment

Simplicity in information found online is in demand from diverse user groups seeking better text comprehension and consumption of information in an easy and timely manner. Readability assessment, particularly at the sentence level, plays a vital role in aiding specific demographics, such as language learners. In this paper, we research model evaluation metrics, strategies for model creation, and the predictive capacity of features and feature sets in assessing readability based on sentence complexity. Our primary objective is to classify sentences as either simple or complex, shifting the focus from entire paragraphs or texts to individual sentences. We approach this challenge as both a classification and clustering task. Additionally, we emphasize our tests on shallow features that, despite their simplistic nature and ease of use, seem to yield decent results. Leveraging the TextStat Python library and the WEKA toolkit, we employ a wide variety of shallow features and classifiers. By comparing the outcomes across different models, algorithms, and feature sets, we aim to offer valuable insights into optimizing the setup. We draw our data from sentences sourced from Wikipedia’s corpus, a widely accessed online encyclopedia catering to a broad audience. We strive to take a deeper look at what leads to greater readability classification in datasets that appeal to audiences such as Wikipedia’s, assisting in the development of improved models and new features for future applications with low feature extraction/processing times.

Gender Differences in Usage of Pathao’s Two-Wheeler Services

The study tests the significant difference in usage patterns of Pathao Services between two different groups: male and female. In this context, the Independent Samples t-Test has been used to test equality in the mean usage of Pathao Services for both groups with and without the assumption of equal and unequal variances. We tested the sample of 397 participants, and the variance between these groups was found to be unequal by the Levene's Test showing the significant difference. The results reveal a statistically significant mean difference in the use of Pathao Services between the two groups. Precisely, the average of difference for 0.199, at 95% confidence interval, falls within a range of 0.087 to 0.310 when variances are considered to be equal and within a range of 0.073 to 0.325 when variances are taken to be unequal. As a matter of fact, the p-values for both tests were below the conventional alpha level of 0.05, meaning the differences observed are significant. The results derived from unequal variances tests were considered more reliable because of the significant F-value obtained from Levene's Test. These results therefore indicate that one group is using Pathao Services more than the other. The significant differences of usage would require further examination of demographic, socio-economic, or even behavioral reasons responsible for these differences and might be useful in service provision and intervention. This thus calls for more research to find the root causes of such and perhaps inform strategies to help improve service engagement across diverse user groups.

Use of Generative AI for Improving Health Literacy in Reproductive Health: Case Study.

Patients find technology tools to be more approachable for seeking sensitive health-related information, such as reproductive health information. The inventive conversational ability of artificial intelligence (AI) chatbots, such as ChatGPT (OpenAI Inc), offers a potential means for patients to effectively locate answers to their health-related questions digitally. A pilot study was conducted to compare the novel ChatGPT with the existing Google Search technology for their ability to offer accurate, effective, and current information regarding proceeding action after missing a dose of oral contraceptive pill. A sequence of 11 questions, mimicking a patient inquiring about the action to take after missing a dose of an oral contraceptive pill, were input into ChatGPT as a cascade, given the conversational ability of ChatGPT. The questions were input into 4 different ChatGPT accounts, with the account holders being of various demographics, to evaluate potential differences and biases in the responses given to different account holders. The leading question, "what should I do if I missed a day of my oral contraception birth control?" alone was then input into Google Search, given its nonconversational nature. The results from the ChatGPT questions and the Google Search results for the leading question were evaluated on their readability, accuracy, and effective delivery of information. The ChatGPT results were determined to be at an overall higher-grade reading level, with a longer reading duration, less accurate, less current, and with a less effective delivery of information. In contrast, the Google Search resulting answer box and snippets were at a lower-grade reading level, shorter reading duration, more current, able to reference the origin of the information (transparent), and provided the information in various formats in addition to text. ChatGPT has room for improvement in accuracy, transparency, recency, and reliability before it can equitably be implemented into health care information delivery and provide the potential benefits it poses. However, AI may be used as a tool for providers to educate their patients in preferred, creative, and efficient ways, such as using AI to generate accessible short educational videos from health care provider-vetted information. Larger studies representing a diverse group of users are needed.

A novel affordable user interface for robotic surgery training: design, development and usability study.

The use of robotic systems in the surgical domain has become groundbreaking for patients and surgeons in the last decades. While the annual number of robotic surgical procedures continues to increase rapidly, it is essential to provide the surgeon with innovative training courses along with the standard specialization path. To this end, simulators play a fundamental role. Currently, the high cost of the leading VR simulators limits their accessibility to educational institutions. The challenge lies in balancing high-fidelity simulation with cost-effectiveness; however, few cost-effective options exist for robotic surgery training. This paper proposes the design, development and user-centered usability study of an affordable user interface to control a surgical robot simulator. It consists of a cart equipped with two haptic interfaces, a VR visor and two pedals. The simulations were created using Unity, which offers versatility for expanding the simulator to more complex scenes. An intuitive teleoperation control of the simulated robotic instruments is achieved through a high-level control strategy. Its affordability and resemblance to real surgeon consoles make it ideal for implementing robotic surgery training programs in medical schools, enhancing accessibility to a broader audience. This is demonstrated by the results of an usability study involving expert surgeons who use surgical robots regularly, expert surgeons without robotic surgery experience, and a control group. The results of the study, which was based on a traditional Peg-board exercise and Camera Control task, demonstrate the simulator's high usability and intuitive control across diverse user groups, including those with limited experience. This offers evidence that this affordable system is a promising solution for expanding robotic surgery training.

An Empirical Study for the Dynamic and Personalised Learning Experience of the AI Course Generator

In a world that is quickly evolving, the demand for continuous learning and upskilling is critical for personal and professional growth. However, many learners struggle to create personalised, efficient learning paths tailored to their unique needs due to the limitations of traditional course creation methods, which require significant human input and expertise. This project aims to address this problem by developing "modulo," an innovative platform designed to automate the creation of personalised and structured learning paths. The objectives of “modulo” are to leverage artificial intelligence and external APIs to generate customised study plans for any chosen subject, integrate curated YouTube tutorials and supplemental materials, and enhance the learning experience with adaptive quizzes tailored to user progress. The methodology follows an Iterative-Waterfall approach, combining structured phases with iterative cycles to incorporate feedback and adapt to emerging challenges. The system architecture is built on a microservices framework, with a frontend developed using React and Next.js, and a backend supported by Supabase with Prisma for database management, NextAuth for user authentication, and Stripe for payment processing. The result is a scalable and maintainable platform that empowers diverse user groups by enhancing education accessibility. “modulo” provides a dynamic and personalised learning experience, making a meaningful impact on self-directed learning

From whales to minnows: The impact of crypto-reward fairness on user engagement in social media

In an era where user-generated content drives social media growth, effectively incentivizing contributions remains a challenge. This study explores the empirical impact of a crypto-integrated platform, Steemit, focusing on a system transition designed to enhance fairness in reward distribution. We assess how this shift affects user engagement, specifically through the volume of posts. Our findings indicate that a fairer crypto-reward distribution boosts user-generated posts, though the increase is less pronounced for users with higher capital or reputation. Further analysis reveals the complex dynamics of cryptocurrency rewards and their role in fostering individual contributions and platform growth, while offering financial incentives. The effects of fair distribution are consistent across diverse user groups, highlighting novel incentivization strategies in social media and the transformative potential of integrating cryptocurrencies into reward systems.

Exploring Emotional Intelligence in Jordan’s Artificial Intelligence (AI) Healthcare Adoption: A UTAUT Framework

The integration of Artificial Intelligence (AI) has been reshaping healthcare globally. However, the AI adoption in Jordan is met with cautious progress. AI has shown substantial potential to enhance healthcare services and foster Emotional Intelligence (EI), especially in advanced economies. Despite its proven effectiveness elsewhere, the Jordanian populace is reluctant to adopt AI in the healthcare sector, with predictions for hospitalizations, medical consultations, and treatment recommendations being sluggish to gain acceptance. This study investigates the combination of Emotional Intelligence and AI adoption in the healthcare system in Jordan, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) model. While UTAUT typically considers performance expectancy, effort expectancy, social influence, and facilitating conditions as key determinants of technology acceptance, this study argues that emotional intelligence, including self-regulated, self-awareness, motivation, empathy, and social skills, should be integrated as direct determinants of behavioural intention. In this study, a quantitative approach has been employed, whereby questionnaires were delivered through email and messaging apps to evaluate the impact of emotional intelligence on Jordanians’ willingness to adopt AI technology in the healthcare sector. The findings suggested that the UTAUT model should be further expanded to encompass emotional intelligence as its fifth construct, particularly in developing countries like Jordan, where user models for AI adoption are less explored. The implications of the study extend to healthcare planners and developers in Jordan, providing insights into factors, which influence the successful adoption of AI technologies among diverse user groups. This study has provided valuable recommendations for developers of AI-based healthcare systems, enabling them to align their assistance with the perceptions and behaviours of Middle Eastern users. By doing so, they can foster increased acceptance of AI-based healthcare systems in the Middle East and other developing regions to improve healthcare services.

Assessing experiential performance in basketball halls: a comparative measure through post-occupancy evaluation

ABSTRACT Designing architectural spaces that effectively cater to the dynamic and evolving needs of diverse user groups is a complex and challenging task. This complexity is especially pronounced in public spaces like basketball halls, which must accommodate a wide range of user needs and have specific spatial requirements to ensure optimal functionality and user satisfaction. This study introduces a novel measure for comparing qualitative data obtained from Post-Occupancy Evaluation (POE) studies in basketball halls. POE is a powerful tool for assessing how well a building meets its intended purpose and user needs after a period of occupancy. However, comparing the success of different buildings can be challenging when evaluations are based on qualitative data. To address this issue, our measure incorporates the perspectives of key decision-makers involved in different stages of the building's lifecycle: the designer, facility manager, and sports manager. These perspectives are integrated using the Multi-Criteria Decision Making (MCDM) method SWARA. The validity of the proposed measure was tested through a field study. Results demonstrate its effectiveness in enabling the comparison of user-based qualitative data, offering a valuable tool for evaluating the experiential performance of basketball halls, a building type underrepresented in POE studies to date.

Human-AI interaction research agenda: A user-centered perspective

The rapid growth of artificial intelligence (AI) has given rise to the field of Human-AI Interaction (HAII). This study meticulously reviewed the research themes, theoretical foundations, and methodological frameworks of the HAII field, aiming to construct a comprehensive overview of this field and provide robust support for future investigations. HAII research themes include human-AI collaboration, competition, conflict, and symbiosis. Theories drawn from communication, psychology, and sociology support these studies, while the employed methods include both self-reporting and observational approaches commonly utilized in user studies. It is suggested that future research should broaden its focus to encompass diverse user groups, AI roles, and tasks. Moreover, it is necessary to develop multi-disciplinary theories and integrate multi-level research methods to support the sustained development of the field. This study not only furnishes indispensable theoretical and practical insights for forthcoming research endeavors but also catalyzes the realization of a future distinguished by seamless interaction between humans and AI.

Urban walkability and tour bus travel

Urban walkability is receiving increasing research attention due to the environmental and health benefits of walking in comparison to driving, yet little is known regarding the walking behaviors of urban visitors who arrive by tour bus. The purpose of this study is to investigate the walking behaviors of diverse tour bus user groups visiting a spatially complex urban destination to better understand urban walkability, barriers to walking, and the derived benefits to walking for tour bus participants. Using an immersive mixed-methods approach, researchers collected eight days of on-bus/off-bus data to document information specific to walking activities, site-to-site transport, tour bus cruising/idling, operational efficiency, mobility, access, and safety. Four target visitor groups included school age, adults, international, and senior citizen veterans. Pedestrian miles traveled ranged from 2.0 to 10.5 miles during tours that lasted between 4.30 and 14.15 h, while primary barriers to walking included itineraries, weather, and safety considerations. Addressing the psychology of walking to evolve from utilitarian to a purposefully integrated leisure activity within tour bus itineraries is the key to decreasing dependency on tour buses for site-to-site transport in urban destinations. Management implications•Spatially complex urban park designs should consider walkability factors such as access, connectivity, path quality, safety, and aesthetics.•Policies that highlight and reward smart mobility should be prioritized to increase utilitarian and leisure walking in urban parks.•Tour mode bundles should purposefully embed walking activities in itineraries to increase physical benefits and participant satisfaction.

Prototype Biodiversity Digital Twin: Phylogenetic Diversity

Phylogenetic diversity (PD) represents a fundamental measure of biodiversity, encapsulating the extent of evolutionary history within species groups. This measure, pivotal for understanding biodiversity's full dimension, has gained recognition by major environmental and scientific organisations, including the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Unlike traditional taxonomic richness, PD offers a comprehensive, evolutionary perspective on biodiversity, essential for conservation planning and biodiversity management. This manuscript describes the development of a BioDT (Biodiversity Digital Twin) prototype, aimed at facilitating the calculation and visualisation of biodiversity metrics from global, dynamic data sources. By utilising the PhyloNext pipeline and integrating with global phylogenetic and species occurrence databases like the Open Tree of Life (OToL) and the Global Biodiversity Information Facility (GBIF), the prototype aims to significantly reduce computation time and enhance user interaction. This enables dynamic visualisation and potentially hypothesis testing, making it a valuable tool for researchers, monitoring initiatives, policy-makers and the public. The prototype's development focuses on improving the PhyloNext pipeline's scalability and creating a more intuitive user interface, expanding its utility for conservation efforts and biodiversity exploration. Our work illustrates the potential impact of the BioDT prototype in supporting diverse user groups in visualising and exploring PD, thus contributing to more informed decision-making in conservation and biodiversity management.

Quantitative Interpretation of Universal Design Features in Shopping Malls: A Case Study in Kolkata, India

United Nations Sustainable Development Goal 11 indicates the need for and importance of inclusive public spaces as a prerequisite towards sustainable cities. Shopping malls in urban India attract a significantly large population daily, making them an important typology of urban structures which deserve universal design. Thus, in this paper, universal design features of shopping malls in Kolkata have been considered. Despite a significant increase in the number of elderly and specially-abled people, civic administration in Kolkata has not been able to successfully implement the national guidelines on inclusiveness in its shopping malls. Five shopping malls from the Kolkata Municipal Corporation were considered case areas for the fieldwork. The accessibility audit checklist included in the ‘Harmonized Guidelines and Standards for Universal Accessibility in India 2021’ published by the Ministry of Housing and Urban Affairs, Government of India, has been used in this paper. It was found that the accessibility percentage of shopping malls ranges between 14.4% and 44.8%, indicating the lack of universal design considerations. Pearson’s correlation between the year of establishment and the accessibility percentage of each case area was found to be −0.66, indicating an alarming deterioration in universal design considerations over the years. On comparing the accessibility performance with the diverse user groups, it was found that individual wheelchair users are likely to face the most difficulty in the case areas with a median accessibility value of 41.46%. This research indicated that accessible continuity in shopping malls in Kolkata can be imparted only by implementing case-specific universal design assessment through a primary survey.

Exploration of a method for insight into accessibility design flaws based on touch dynamics

The widespread use of smartphones implies that intelligent systems must address the negative emotions experienced by a diverse user group when encountering usability difficulties. Therefore, exploring the relationship between users’ emotions and operational behaviors is crucial for further enhancing the accessibility of intelligent systems. Touch dynamics, as a method of dynamic touch data monitoring, has already provided many models for emotion recognition, which are beneficial in gaining insight into users’ accessibility needs for smartphones and exploring intelligent solutions to design issues. This paper validates this aspect through interviews and experimental studies. The study first conducted an open-ended interview, and then used a touch behavior experiment with emotional labels and a questionnaire to validate the association between accessibility design flaws in intelligent systems and user emotions. The interview results show that middle-aged and older smartphone users have difficulty activating accessibility tools independently. Consequently, this paper establishes a dataset for emotion classification based on touch gesture data, which is used to gain insight into implicit difficulties in the interaction process through negative emotions. From a touch experiment and questionnaire survey of 57 sample users, there is approximately a 78.57% match between the accessibility needs of intelligent systems and users’ negative emotions, with interaction fluency and interface cognition being the main reasons for this phenomenon. Therefore, touch dynamics, as a non-invasive method of emotion recognition, can use negative emotional feedback to gain insights into user needs that are difficult to detect by other methods. This has application value for enhancing users’ emotional experience and promoting a transformation in interaction design thinking.