This paper introduces WORLD+, a lightweight, Vision Transformer-based model designed for enhanced scene understanding with a specific focus on accessibility-aware image analysis. Building on the foundational WORLD model, WORLD+ eliminates multimodal complexity by using only visual inputs and integrates an object-driven tagging system to support both scene classification and contextual labeling. A key feature of WORLD+ is its ability to detect accessibility-related elements (e.g., ramps, stairs) and incorporate them into a simple yet effective recommender system. This system enables inclusive suggestions for Points of Interest (POIs) based on visual similarity and mobility needs. Experimental results demonstrate strong classification performance and competitive multi-label tagging, highlighting WORLD+ as a scalable, inclusive solution for real-world applications in e-society contexts.
This study investigates social media users’ intention to engage in user correction, that is, challenging others who post misinformation; whether this intention translates into actual behaviour; their choice of communication styles (direct or indirect) when doing so; and the influence of psychological and competency factors on that. It specifically examines the influence of the personal factors of altruism (viewing user correction as a pro-social act), empathy (as it involves correcting someone and protecting others), self-esteem (as it requires taking a stand), and social media use competency across two distinct cultural contexts: the United Kingdom (UK) and Arab Peninsula countries. Data were collected through an online survey, supported by vignettes, of 686 participants (367 British and 319 Arabs). The findings revealed a significant intention–behaviour gap in user correction across both samples. Participants in both cultural groups showed a stronger preference for indirect communication styles over direct ones. Multivariate Multiple Regression (MMR) analysis indicated that altruism and social media use competency consistently predicted both the intention to participate in and actual participation in user correction in both cultural groups. However, self-esteem significantly predicted actual participation only among UK participants, while empathy showed no significant association in either sample. Further MMR analysis revealed cultural differences in the predictors of communication style choice. In the UK, both altruism and self-esteem predicted preferences for both direct and indirect styles. In the Arab sample, social media use competency predicted a preference for the direct style, while both altruism and social media use competency predicted a preference for the indirect style. These findings highlight the critical role of cultural and psychosocial nuances in designing socio-technical interventions to promote user correction and combat the spread of misinformation.
People with motor disabilities have always struggled to utilize technology in the same way that an able-bodied person does. That is because traditional technology designs have not been very inclusive of people with disabilities. Given that using human–computer interfaces (HCIs) has become part of our everyday life, human-computer interface design should change by becoming more inclusive of people who cannot use them in the “traditional” way. Haptic feedback in Human-Computer Interfaces could reduce this deficiency inherent to traditional human-computer interface usage by providing alternative ways for users to interact with a computer interface. Using a systematic literature review (SLR), the researcher scrutinised 44 articles to understand how haptic feedback can make computer interfaces more usable and accessible for users with various motor disabilities. In addition, the investigation considered alternative input devices and methods and how they could enhance user experience with computer interfaces. The review found that haptic feedback can significantly impact the usability of a computer interface for people with various motor disabilities. From using vibrations and haptic textures to inform the user when and where to click on the interface to applying constant force from the alternative input device to reduce strain on weakened or spasming muscles, haptic feedback has proven its ability to provide a better experience for people with differing types of motor disabilities.
Accurate estimation of travel time is a crucial challenge in modern navigation systems, where real-time traffic conditions constantly change. Traditional shortest path algorithms, such as Dijkstra's algorithm, provide optimal solutions under static conditions but fail to account for dynamic congestion, leading to inaccurate estimated times of arrival (ETAs). In this study, we propose a Smart Real-Time Estimation method that incorporates predictive modeling of future traffic congestion to enhance ETA accuracy. Our approach utilizes a traffic simulation framework to evaluate the effects of congestion evolution on route optimization. We conducted simulations on different road networks under varying traffic conditions, comparing our method to the standard Dijkstra algorithm. The results indicate that in medium-traffic scenarios, our predictive model significantly improves ETA precision by anticipating congestion buildup. However, in highly congested environments, while our approach reduces systematic prediction errors, it introduces variability due to the complexity of traffic interactions. Additionally, the presence of traffic signals impacts both methods, with our approach demonstrating better adaptability when congestion patterns are predictable. Overall, our findings suggest that incorporating future traffic estimations into routing algorithms enhances the accuracy and realism of travel time predictions. This method provides a more dynamic and adaptive solution for navigation applications, particularly in environments where traffic conditions fluctuate frequently. By leveraging predictive modeling, our approach offers a viable improvement over conventional shortest path algorithms, making it a promising direction for optimizing real-time route planning.
Designing processes that align with strategic goals has become increasingly challenging in today's fast-paced business environment. Business Process Architecture (BPA) plays a vital role in achieving this strategic alignment and ensuring that processes are coherent both in design and implementation. To tackle these challenges, companies can utilize their dynamic capabilities to adapt to rapid changes. One well-known method for enterprise architecture that includes BPA development is The Open Group Architecture Framework (TOGAF). We applied design science research to integrate dynamic capabilities theory with the TOGAF framework. We developed and evaluated a BPA method suitable for strategic renewal in unpredictable environments. As a result, we have created and evaluated a BPA development method that provides practical guidance for applying dynamic capabilities theory in a real-world business context.
