Digital

This pilot study explores the efficacy of an AI-powered gamified chatbot integrated with an Online-Merge-Offline (OMO) strategy to enhance parental nutrition knowledge. Conducted in a Taiwanese public childcare setting, the intervention comprised eight weekly nutrition seminars delivered by registered dietitians, supplemented by a LINE-based chatbot providing interactive, gamified learning experiences. Pre-test and post-test evaluations were administered via the chatbot to assess knowledge acquisition. The results from 20 unique participants, including 9 with complete data, indicated a statistically significant improvement in nutritional knowledge (p < 0.0001, Cohen’s d = 2.50), suggesting a substantial educational impact. The integration of gamification elements—such as level completion, community rankings, and personalized feedback—with OMO modalities allowed for sustained engagement, knowledge reinforcement, and seamless transition between digital learning and physical application. This study provides empirical evidence supporting the feasibility and pedagogical value of OMO-gamified chatbots in health promotion and lays the groundwork for future large-scale, longitudinal investigations. Full article

The advent of transformer technology and large language models (LLMs) has further broadened the already extensive application field of artificial intelligence (AI). A large portion of medical records is stored in text format, such as clinical trial texts. Part of these texts is information regarding eligibility criteria. We aimed to harness the immense capabilities of an LLM by fine-tuning an open-source LLM (Llama-2) to develop a classifier from the clinical trial data. We were interested in investigating whether a fine-tuned LLM could better decide the eligibility criteria from the clinical trial text and compare the results with a more traditional method. Such an investigation can help us determine the extent to which we can rely on text-based applications developed from large language models and possibly open new avenues of application in the medical domain. Our results are comparable to the best-performing methods for this task. Since we used state-of-the-art technology, this research has the potential to open new avenues in the field of LLM application in the healthcare sector. Full article

Students with disabilities often face challenges in participating in classroom activities with normal students. Assistive technologies powered by Artificial Intelligence (AI) or Machine Learning (ML) can provide vital support to ensure inclusive and equitable learning environments. In this paper, we identify AI or ML-powered inclusive education tools and technologies, explore the factors required for developing personalized learning plans using AI, and propose a real-time personalized learning framework. We have identified inclusive education tools and technology driven by AI or ML as well as factors impacting the creation of AI-based personalized learning based on our exploration of Google Database, blog sites, company sites, tools, and techniques used in different centers. This study proposes a system model that includes engagement and adaptive learning components. The system uses Bloom’s taxonomy to continuously track the learner’s development. We identified a comprehensive list of AI- or ML-powered inclusive education tools and technologies and determined key factors for developing personalized learning plans, including emotional state, student progress, preferences, learning styles, and outcomes. Based on this research, AI-based inclusive education has the potential to improve educational experiences for students with disabilities by creating a more equitable and inclusive learning environment. Full article

Background: As digital health resources become increasingly prevalent, assessing the quality of information provided by publicly available AI tools is vital for evidence-based patient education. Objective: This study evaluates the accuracy and readability of responses from four large language models—ChatGPT 4.0, ChatGPT 3.5, Google Bard, and Microsoft Bing—in providing contraceptive counseling. Methods: A cross-sectional analysis was conducted using standardized contraception questions, established readability indices, and a panel of blinded OB/GYN physician reviewers comparing model responses to an AAFP benchmark. Results: The models varied in readability and evidence adherence; notably, ChatGPT 3.5 provided more evidence-based responses than GPT-4.0, although all outputs exceeded the recommended 6th-grade reading level. Conclusions: Our findings underscore the need for the further refinement of LLMs to balance clinical accuracy with patient-friendly language, supporting their role as a supplement to clinician counseling. Full article

Mobile Health (mHealth) technologies are transforming healthcare by making it more accessible, efficient, and patient-centric. This study investigates the factors influencing Millennial’s mobile health adoption intention (mHAI). We propose a research model based on the integrated model of the Unified Theory of Acceptance and Use of Technology—UTAUT and the health belief model—HBM. A cross-sectional study was carried out employing purposive sampling to enlist Generation Y (born between 1981 and 1996) and 220 valid questionnaires were collected. We employed structure equation modeling partial least square (SEM-PLS) along with artificial neural network (ANN) and importance–performance map analysis (IPMA) to analyze our model. The research findings revealed that performance expectancy is the most influential factor, while effort expectancy showed no significant association with mHAI. Theoretical and managerial implications are offered to expand the literature on digital healthcare studies, indicating how healthcare providers in developing countries can attract their potential users. Full article

Workplace safety training is the cornerstone of workplace safety and accident prevention. In the case of frequently rotating employees, such as in the laboratories of higher education institutions, where students are required to perform tasks as part of their education, a considerable amount of effort for workplace safety training is demanded from the supervising instructors. Accordingly, the use of self-guided workplace safety training may lead to significant savings in the workload for instructors. In this evaluation study, we investigated to what extent an augmented reality (AR) app is deemed suitable for workplace safety training. The prototypical augmented reality (AR) app is based on an AR platform that performs tracking based on visual Simultaneous Localization and Mapping (vSLAM, Google Tango). The workplace safety training was carried out for two common stations and two devices in a workshop of an environmental engineering laboratory at a higher education institution. A total of 12 participants took part in the mixed-method study. Standardized questionnaires were used to assess usability, cognitive load and the learner prerequisites of motivation and emotion. Qualitative results were collected through subsequent semi-structured interviews. The app was able to achieve good usability, and the values for cognitive load can be classified as conducive to learning, as can the values for the learning prerequisites of motivation and emotion. The interviews provided insights into strengths, but also into potential improvements to the app. The study proved that using vSLAM-based AR apps for workplace safety training is a viable approach. However, for further efforts to establish AR-app-based workplace safety training, these insights need to be ported to a new AR platform, as the platform used has since been discontinued. Full article

The success of digital transformation initiatives relies heavily on effective digital leadership, which requires a blend of human-centric traits and technical expertise. While digital technologies enable transformation, organizations must develop leaders with the skills to navigate the complexities of change, foster innovation, and align strategies with organizational goals. Despite the growing importance of digital leadership, there is a lack of standardized, validated tools to measure and assess digital leadership competencies systematically. This study introduces the Digital Leadership Scale (DLS), a validated self-assessment tool designed to measure a leader’s ability across seven human-centric dimensions essential for digital transformation: Positive Attitude, Ethical AI Use, Growth Mindset, Track Record, Transparent Agenda, Skills Acquisition, and Participative Style. The DLS serves as a practical tool for leaders to engage in self-reflection, identify strengths and development areas, and adopt personalized learning strategies. Organizations can leverage this scale to cultivate a digitally proficient workforce and foster leadership capabilities aligned with digital transformation success. Full article

This paper presents an application of the Ant Colony Optimization (ACO) algorithm combined with the Logistic Regression (LR) method in the lead acid battery charging process. The ACO algorithm is used to obtain the best current pattern in the battery charging system to produce a smart charging system with a fast and safe charging current for the battery. The best current pattern is conducted gradually and repeatedly to obtain termination in the form of the best current pattern according to the ACO algorithm. The results of the algorithm design produce a current pattern consisting of 10 A, 5 A, 3 A, 2 A, and 0 A. The charging system with this algorithm can charge all types of lead acid batteries. In this research, the capacity of battery 1’s State of Charge (SOC) is 56%, battery 2’s SOC is 62%, and battery 3’s SOC is 80%. When recharging the battery’s full condition to a SOC of 100%, the length of time for charging battery 1 for 12.73 min, battery 2 takes 15.73 min, and battery 3 takes 29.11 min. Smart charging with the ACO can charge the battery safely without current fluctuations compared to charging without an algorithm such that the amount of charging current used is not dangerous for the battery. In addition, data analysis is carried out to determine the value of accuracy in estimating SOC charging using supervised learning linear regression. The results of the data analysis with linear regression show that the battery’s SOC estimation has good accuracy, with an RMSE value of 0.32 and an MAE of 0.27. Full article

In South Korea, Generation Z’s influence on the growth of sports over-the-top (OTT) services is significant. For sustainable growth, OTT service providers need to focus on converting existing users into loyal customers. In this context, understanding Generation Z’s subjective perceptions of the constraints on the continued use of sports OTT services would be meaningful. Therefore, this study aims to identify and categorize the factors constraining Generation’s Z’s continued use of sports OTT services using the Q methodology. A total of 25 Q samples and 18 P samples were selected. The QUANL program was used to calculate the correlation coefficients for each respondent, and Q factor analysis was performed through principal component analysis and varimax rotation. As a result, three types were identified: ‘Demand for improvements in pricing plans and system quality’, ‘Dissatisfaction with subscription fees and demand for diverse content’, and ‘Demand for differentiated services’. The findings of this study suggest that, for Generation Z’s continued use of OTT services, it is essential to provide personalized experiences and benefits or satisfaction relative to subscription fees. On top of that, offering various pricing plans can provide flexibility in service choices and encourage continued use among Generation Z. As such, this study can provide insights into appreciating the consumption trends and factors influencing the continued use of OTT services by Generation Z and interpreting related research results in the future. Full article

This study investigates the integration, usability, and learning patterns associated with voice assistant technology among older adults, focusing on the “Amazon Echo Show 10, 3rd generation” as a case study. Conducted with 32 participants aged 55 and above in senior and complementary households, this research employs a mixed-method approach, incorporating qualitative interviews and quantitative voice command logging over a twelve-week period. Our findings reveal a high level of learnability and usability of the voice assistant, with 90% of participants finding the device easy to learn and use. The study further explores the patterns of voice assistant use, highlighting a preference for listening to music and seeking information, predominantly on weekends. Despite initial reservations, participants reported a high satisfaction level, with most not feeling monitored by the device. Key recommendations for manufacturers include prioritizing the design and user experience to cater to older adults’ needs, aiming to enhance their digital inclusion and participation. This study contributes to the human–computer interaction (HCI) field by providing insights into older adults’ interactions with voice assistant technology, emphasizing the importance of designing accessible and user-friendly digital solutions for the aging population. Full article

Cybercrime prevention is critical for the effective functioning of e-government services. Despite its importance, internal cybercrime mitigation processes within these services are underrepresented in the existing literature. This study addresses this gap by conducting a systematic review and bibliometric analysis of e-government research from January 2015 to January 2025. Using the Web of Science and Scopus databases, 3790 studies were identified; after removing duplicates, bibliometric analysis was performed using R Studio (Build 467). The analysis revealed that Government Information Quarterly was the leading journal, with China, the USA, and the UK contributing the most publications. Nineteen major themes emerged, with “adoption” identified as the dominant theme, followed by “governance” and “development”. Among 88 security-related studies, 19 specifically addressed cybersecurity in e-government services. Findings indicate a predominant focus on user-centric perspectives, such as service adoption and system vulnerabilities, while internal cybersecurity issues, including managerial practices and mitigation strategies, remain largely unexplored. Limited data availability may contribute to this gap. This study highlights the need for future research to adopt an integrated approach, emphasising management-level practices for cybercrime mitigation within e-government institutions from both developing and developed nations. Full article

Crowd panic emergencies can pose serious risks to public safety, and effective detection and mapping of such events are crucial for rapid response and mitigation. In this paper, we propose a real-time system for detecting and mapping crowd panic emergencies based on machine learning and georeferenced biometric data from wearable devices and smartphones. The system uses a Gaussian SVM machine learning classifier to predict whether a person is stressed or not and then performs real-time spatial analysis to monitor the movement of stressed individuals. To further enhance emergency detection and response, we introduce the concept of CLOT (Classifier Confidence Level Over Time) as a parameter that influences the system’s noise filtering and detection speed. Concurrently, we introduce a newly developed metric called DEI (Domino Effect Index). The DEI is designed to assess the severity of panic-induced crowd behavior by considering factors such as the rate of panic transmission, density of panicked people, and alignment with the road network. This metric offers immeasurable benefits by assessing the magnitude of the cascading impact, enabling emergency responders to quickly determine the severity of the event and take necessary actions to prevent its escalation. Based on individuals’ trajectories and adjacency, the system produces dynamic areas that represent the development of the phenomenon’s spatial extent in real time. The results show that the proposed system is effective in detecting and mapping crowd panic emergencies in real time. The system generates three types of dynamic areas: a dynamic Crowd Panic Area based on the initial stressed locations of the persons, a dynamic Crowd Panic Area based on the current stressed locations of the persons, and the dynamic geometric difference between these two. These areas provide emergency responders with a real-time understanding of the extent and development of the crowd panic emergency, allowing for a more targeted and effective response. By incorporating the CLOT and the DEI, emergency responders can better understand crowd behavior and develop more effective response strategies to mitigate the risks associated with panic-induced crowd movements. In conclusion, our proposed system, enhanced by the incorporation of these two new metrics, proves to be a dependable and efficient tool for detecting, mapping, and assessing the severity of crowd panic emergencies, leading to a more efficient response and ultimately safeguarding public safety. Full article

This study highlights the Digital Transformation issues in recent scientific topics, as well as the trends in the European Union’s Digital Economy dynamics. The aim is to identify key and promising research topics in the digital field and define priorities for adopting digital innovations in the EU in terms of bibliographical and statistical aspects. The study includes a bibliographic analysis using publication metrics statistics, word cloud diagrams, and network clustering. There is also a quantitative analysis of the leading Digital Economy trends in the EU using correlation and cluster analyses and visualizations of the selected economic and Digital Transformation metrics. The results identify critical keywords in digitalization publications related to other key research and multidisciplinary areas. A grouping is proposed of research paper topics and research issues related to Digital Transformation in the EU and worldwide based on the identified trends in recent research proposals. The study examines the correlation of some digital indices and trends in EU countries’ GDP dynamics, R&D investment, and digital inclusion. From the clustering based on the data of a single digital market that promotes e-commerce for individuals and businesses, groups of EU countries have been identified as having the potential to increase digital inclusion and convergence growth rate. The results provide a basis for future research on Digital Transformation and determine the need for further intensification of EU digitalization. Full article

Despite the demonstrable benefits of data monetization initiatives for achieving competitive advantages, many of these efforts struggle to realize their potential. Companies often find it challenging to sustain even initially successful data monetization initiatives due to formidable data quality issues. This reflects a disconnect between advancements in data monetization research—which range from digitization to digitalization and digital transformation—and their practical implementation within companies. Consequently, misguided approaches to data monetization are relatively common. A critical prerequisite for successful data monetization is the establishment and maintenance of clean, high-quality data. This study underscores the importance of data quality by conducting an in-depth analysis of Medical Inc., a company that prepares pristine customer master data for advanced customer analytics. The investigation aims to elucidate Medical Inc.’s approach for addressing data cleanliness challenges and developing a general framework for the process of cleansing customer master data. This framework illuminates a relatively unexplored aspect of data monetization, thereby supplementing existing research on digitization, digitalization, and digital transformation. Full article

Hospitals use their websites to reinforce their relationships with stakeholders and build the brand collectively; however, they face challenges such as patients’ new needs or strict legal frameworks. This paper analyzes how Australia’s best hospitals manage their websites to implement content strategies that help them build their brands collectively with stakeholders. We conducted a literature review about smart hospitals, their corporate communication initiatives, and their online content strategies. Then, we identified 40 brand indicators to analyze how Australia’s best hospitals used their websites to interact with healthcare professionals, patients, media companies, and shareholders. We proved that most hospitals had sections for these targets (healthcare professionals -72.06%-, patients -85.51%-, media companies -98.53%, shareholders 100%-); however, they only respected, on average, 14.06 brand indicators. We concluded that Australian hospitals should follow a more emotional communication approach, make their brands more present on their website, and increase their collaborations with media companies. Full article

Traditional tools, such as 3D Slicer, Fiji, and MATLAB^®, often encounter limitations in rendering performance and data management as the dataset sizes increase. This work presents a GPU-enabled volume renderer with a MATLAB^® interface that addresses these issues. The proposed renderer uses flexible memory management and leverages the GPU texture-mapping features of NVIDIA devices. It transfers data between the CPU and the GPU only in the case of a data change between renderings, and uses texture memory to make use of specific hardware benefits of the GPU and improve the quality. A case study using the ViBE-Z zebrafish larval dataset demonstrated the renderer’s ability to produce visualizations while managing extensive data effectively within the MATLAB^® environment. The renderer is available as open-source software. Full article

The interdisciplinary teaching of contemporary physics has become increasingly common in physics education, especially for high school students and teachers. This approach, which integrates content and methodologies from various disciplines, fosters scientific reasoning, enhances creativity, and increases student motivation and interest in physics. The use of digital technologies, such as social media platforms, supports these educational goals by facilitating the inclusive and cost-effective dissemination of scientific knowledge and the development of soft skills. This paper introduces the “Gravitas” project, an initiative that employs an interdisciplinary approach to present contemporary physics topics to high school students through social media. Coordinated by the Cagliari Division of the National Institute of Nuclear Physics (INFN) in Italy, the “Gravitas” project offers a non-traditional learning environment where students explore modern physics and philosophy and the history of science. Through the creation of educational materials, such as social media posts, students actively engage in their learning. In 2022, around 250 students from 16 high schools across Sardinia, Italy, participated in this project. This paper discusses the learning outcomes, highlighting the potential of integrating formal high school curricula with innovative educational and digital tools. Full article

As the digital environment evolves, the need to integrate artificial intelligence (AI) technology into corporate IT network operations increases. In this study, the aim was to define the factors that influence AI adoption in the network operations and analyze their impact on productivity and service stability. The technology–organization–environment (TOE) framework was employed for this investigation, focusing on technological, organizational, and environmental factors. In addition, in this study, structural equation modeling was employed to analyze the relationships between these influencing factors and the intention to adopt AI. The mediation effect was examined through the network operation productivity and network service stability. A survey was conducted targeting network operations and AI professionals to collect data. The analysis results revealed that technological and environmental factors positively influenced the network operation productivity, while only environmental factors positively influenced the network service stability. Furthermore, the findings of this study highlight that environmental factors are the most significant factors that influence network operation productivity and network service stability. Moreover, the direct positive impact of network operation productivity and IT network service stability on the intention to adopt AI underscores their crucial role. In conclusion, when evaluating AI adoption in terms of network operation productivity and network service stability, prioritizing technological and environmental factors over organizational factors is necessary. Full article

Three-dimensional information visualizations are widely used in various fields for their aesthetic appeal. However, using them can sometimes lead to occlusion and distortion, which raises questions about when and why to use them. In this study, we aimed to investigate the effects of three-dimensional visualizations on human gaze and user understanding and analyze the perception process in detail. Our empirical research consisted of a two-part experimental study that involved both subjective and objective evaluation. We specifically focused on bar charts as they are among the most frequently used types of information visualizations. The results suggest that, for bar chart visualizations with varying gap dimensions, there is no statistically significant difference in user understanding between the two-dimensional and three-dimensional versions. Our findings indicate that, in general, three-dimensional bar chart visualizations are as comprehensible as their two-dimensional counterparts for the gap dimensions examined in this research. This study provides empirical insights demonstrating that both 3D and 2D bar charts are equally understandable, particularly when a specific gap depth is used in 3D visualizations. These findings contribute to the ongoing discussion about the effective use of three-dimensional visualizations and highlight areas for further research. Full article