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Found 6374 publications
Impact of Gamification on Student Engagement and Behavior Moderated by Public Policy in Higher Education Institutions
Publication Name: Human Behavior and Emerging Technologies
Publication Date: 2025-01-01
Volume: 2025
Issue: 1
Page Range: Unknown
Description:
This study investigates the impact of gamification on student engagement moderated by public policy in higher education. The psychological perspective of student engagement refers to the deep involvement of students in learning and acquiring knowledge. There are three dimensions of student engagement: cognitive, emotional, and behavioral. This study selects computer science students who were already enrolled in gamification classes. The selected sample of the study is based on multiple cities of Pakistan, including Lahore, Islamabad, and Karachi. The selection of institutes from three cities is made based on a convenience sampling technique. A 5-point Likert scale questionnaire is used to assess the role of gamification and its impact on gaming platforms and student engagement with dummy variables as public policy management that controls and devises rules and regulations for gamification in higher education departments. We examine the impact of gamification content, challenges, rewards, and the Kahoot platform on student engagement. There are positive and weak results regarding the impact of gamification, as the Kahoot platform itself has no attraction for students, but it provides a user-friendly medium to play games. There are a few topics for future research, such as the role of gamification platforms and their significant impact on students’ motivation and the role of public policy regarding gamification platforms and engagement. Gamification challenges and rewards have been discussed in the study to observe the mediating impact. The analysis of the study is carried out in SmartPLS Version 4.0.
Open Access: Yes
DOI: 10.1155/hbe2/9026903
Taxonomic contribution to knowledge of the oribatid mite genus Rugoppia (Acari, Oribatida, Oppiidae)
Publication Name: International Journal of Acarology
Publication Date: 2025-01-01
Volume: 51
Issue: 3
Page Range: 172-176
Description:
A new species of the genus Rugoppia (Oribatida, Oppiidae)–R. amharaensissp. nov.—is described, based on material collected from terrestrial moss and litter under Erica arborea L. in Central Ethiopia. Generic diagnosis is revised. An identification key, distribution, and habitats of the known representatives of Rugoppia are presented. http://www.zoobank.org/urn:LSIDurn:lsid:zoobank.org:pub:44F8EEDE-379C-4513-885C-65E94603D662.
Open Access: Yes
THE IMPACT OF AN ARTIFICIAL INTELLIGENCE-BASED FORECASTING MODEL ON THE DEVELOPMENT OF SUSTAINABLE TOURISM
Publication Name: Geojournal of Tourism and Geosites
Publication Date: 2025-01-01
Volume: 61
Issue: 3
Page Range: 1758-1766
Description:
This research investigates the application of artificial intelligence (AI) and Web 3.0 technologies in promoting sustainable urban tourism, with a particular focus on demand forecasting and environmental impact assessment. The study presents a two-layered AI-based model aimed at supporting data-driven decision-making in destination management, addressing the need for forward-looking strategies that align with both operational and sustainability goals. The research applies the Facebook Prophet algorithm to forecast monthly tourism demand in two Hungarian cities—Budapest and Győr—selected for their contrasting tourism profiles. Forecast outputs were then integrated into a sustainability impact module estimating carbon dioxide emissions, water consumption, and waste generation, based on empirically defined conversion factors. Results indicated strong seasonal peaks in Budapest, with over 1.3 million overnight stays projected for August 2026, and corresponding environmental impacts surpassing 62,000 tons of CO₂. In contrast, Győr exhibited more moderate fluctuations and lower error margins, reflecting a more stable tourism pattern. Forecast accuracy was assessed using MAE, RMSE, and MAPE metrics, showing acceptable performance for strategic use, although with reduced reliability in low-demand periods. The sustainability module effectively highlighted peak periods of ecological burden, enabling targeted interventions such as infrastructure scaling, service optimization, and seasonal policy adjustments. In addition to its forecasting functionality, the model offers practical guidance for municipalities by identifying where and when ecological pressure is likely to arise. The dual-model framework offers a scalable and replicable approach for cities seeking to balance tourism growth with environmental and community well-being. By integrating predictive analytics with sustainability assessment, the model provides valuable insights into the timing and magnitude of tourism’s impact. This supports smarter capacity planning, emission reduction strategies, and the alignment of visitor flows with local resilience thresholds. The findings contribute to the evolving discourse on smart and sustainable tourism in the Web 3.0 era, positioning AI as a critical enabler of holistic and proactive destination manageme nt.
Open Access: Yes
Digital Transformation in Taiwan’s Insurance Industries for MABAC Technology Based on Circular Modified Fuzzy Choquet Frank Network Data Envelopment Analysis
Publication Name: International Journal of Analysis and Applications
Publication Date: 2025-01-01
Volume: 23
Issue: Unknown
Page Range: Unknown
Description:
Fuzzy set theory has significant and dominant applications in Taiwan’s insurance industry, especially in fields involving decision-making, uncertainty, and risk assessment. Providing the complexity and problems in assessing factors, for instance, natural disaster risks, customer creditworthiness, or health conditions, traditional binary logic often falls short. Taiwanese insurers have adopted fuzzy logic systems to enhance fraud detection, premium pricing, and privilege evaluations by catching the indistinctness characteristic in human ruling and imperfect data. The Taiwan insurance industry is a dynamic and spirited module of the commercial sector, contributing meaningfully to risk management and economic stability. For this, we study to propose an assessment of the proficiency of insurance enterprises using Network Data Envelopment Analysis. Toward this end, the frank operational laws for circular Pythagorean fuzzy (CPF) uncertainty are applied. Moreover, the CPF Choquet Frank averaging (CPFCFA) operator and CPF Choquet Frank geometric (CPFCFG) operator with three dominant properties for each operator have been studied. The study deliberates the multi-attributive border approximation area comparison (MABAC) model and verifies it with the help of numerical examples. This study enhances the industry’s efficiency to offer adapted insurance products and handle risks precisely, aligning with Taiwan’s push toward intelligent financial services and digital transformation. In the following, we establish the decision-making performance for assessing the proficiency of insurance enterprises using the network data envelopment analysis (NDEA) technique. Finally, we examine the ranking values of offered representations to compare them with the ranking values of prevailing models to show the capability and efficacy of the originated approaches.
Open Access: Yes
Sentiment and Deep Learning Analysis of Childbirth Experiences: Insights for Improving Maternity Care and Hospital Policies
Publication Name: Applied Computational Intelligence and Soft Computing
Publication Date: 2025-01-01
Volume: 2025
Issue: 1
Page Range: Unknown
Description:
Maternal childbirth experiences are crucial indicators of health care quality, patient satisfaction, and emotional health. The increasing use of social media platforms, such as Facebook, provides a unique opportunity to examine public sentiment and narratives around maternity care. However, limited studies have employed deep learning (DL)–based sentiment analysis (SA) to comprehensively analyze childbirth experiences in low-resource environments. This study utilizes a hybrid technique that integrates unsupervised topic modeling with supervised DL sentiment classification to capture both thematic breadth and emotional tone of birthing experiences. A dataset of Facebook comments was preprocessed and analyzed using word frequency analysis, latent Dirichlet allocation (LDA) for thematic extraction, sentiment classification using convolutional neural networks (CNNs), and robustly optimized BERT pretraining approach (RoBERTa). Statistical correlations between sentiment polarity and hospital service variables were examined using the chi-square test. The word frequency analysis revealed significant themes such as maternal care, labor and childbirth experiences, informal childbirth discussions, spiritual beliefs, and personal childbirth stories. SA found a majority positive sentiment (5106 instances) with widespread sentiments of trust and joy, although considerable occurrences of fear (1,851), sadness (1,564), and anger (1,114) indicated traumatic delivery experiences. The CNN model outperformed RoBERTa, which had an AUC of 0.9988 and an accuracy of 87%. Statistical study (chi-square test, p < 0.0001) showed a significant correlation between sentiment polarity and hospital service variables, indicating the influence of treatment quality on patient views. This study emphasizes the significance of SA in assessing maternal health care experiences and improving hospital practices. The findings highlight the need of increased communication, empathetic midwifery care, and patient-centered approaches in addressing unfavorable childbirth experiences. This study provides policymakers with data-driven insights to improve maternal health care policies, increase patient experiences, and ensure valuable maternity services.
Open Access: Yes
DOI: 10.1155/acis/8915424
The Impact Beyond Academia: Patent Citations of the Advanced Pharmaceutical Bulletin
Publication Name: Advanced Pharmaceutical Bulletin
Publication Date: 2025-01-01
Volume: 15
Issue: 2
Page Range: 223-227
Description:
Purpose: This study aims to analyze the technological impact of papers that Advanced Pharmaceutical Bulletin (APB) has published through patent-to-paper citations analysis. Methods: Current research uses a Scientometric approach to analyze patent citations to published papers by the APB. The Lens has been used for collecting patents that cited related papers. Some of the data analysis was conducted using the Lens analytical tool. Results: Results show that APB’s patent-to-paper citation rate is 32.39%, above the toxicology field average (6.15%) but below pharmacology (46.33%), indicating significant technological influence. APB contributes to both science and technology, attracting global inventors. Conclusion: The patent citations metric can be used to understand how a journal contributes to technological progress. However, these methods need to be standardized and promoted to understand a journal’s real value in technology contribution.
Open Access: Yes
The revenue diversification of top-tier higher education institutions
Publication Name: Journal of International Studies
Publication Date: 2025-01-01
Volume: 18
Issue: 4
Page Range: 86-106
Description:
This study examines the revenue diversification of the Top 30 higher education institutions (HEIs) as identified in the 2025 Times Higher Education and QS World University Rankings. Faced with declining government appropriations, HEIs are strategically diversifying revenue streams. Our analysis of financial reports reveals substantial variability in revenue sources, with some institutions primarily relying on research grants, tuition, and government funding. In contrast, others prioritize income from endowments, services, or medical activities. While funding optimization strategies may prioritize single revenue sources for short-term convenience, our findings suggest they risk institutional fragility, highlighting the need for sustainable financial models that balance research productivity, teaching quality, and public service over the long term. This article emphasizes the vital importance of financial autonomy, which enables institutions to invest strategically in recruiting top academic and research staff, upgrading research infrastructure, and enhancing an institution’s overall performance. While strategic autonomy empowers institutions to achieve excellence and adapt flexibly to evolving societal needs, they must remain true to their core mission of public service as they diversify and optimize revenue sources.
Open Access: Yes
A Novel Motor Modelling Method for Reluctance Motor Electric Vehicle Drive Systems
Publication Name: Proceedings 2025 IEEE 7th Global Power Energy and Communication Conference Gpecom 2025
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: 216-221
Description:
The field of electric vehicles is one of the most popular research topics today. These vehicles require highly efficient and cost-competitive drive system solutions due to the increasing competition. The reluctance motor drive systems are excellent candidates for fulfilling these requirements However, the controlling of these drive systems is difficult as they represent a heavily nonlinear behavior due to the varying stator inductances. The stator inductances are changing both in the function of the stator currents- and that of the rotor position. This phenomenon makes it necessary to apply advanced modelling solutions that provide a more precise motor model for the torque control algorithm. This paper presents a novel motor modeling method for the reluctance motor drive systems. A new type of inductance matrix is derived, which is a critical part of the motor model. This inductance matrix is used to define new relationships for the electromagnetic torque and the phase voltages of the machine for a given stator current, leading to a novel motor model. This new motor model can serve as an input for the torque control algorithm research and development activities.
Open Access: Yes
Green and Sustainable Chemistry in the Work of the United Nations Environment Programme: Results and Options for Future Regulation
Publication Name: Chemical Engineering Transactions
Publication Date: 2025-01-01
Volume: 121
Issue: Unknown
Page Range: 103-108
Description:
The expression of green and sustainable chemistry has gained significant attention around the world in recent years. Nowadays, it is evident that green and sustainable chemistry is necessary for Sustainable Development Goals (SDGs); however, the concept and its realisation seem quite vague. Until 2021, green and sustainable chemistry had been defined in different documents, which led to divergent practices. However, in 2021, the United Nations Environment Programme (UNEP) created a Framework Manual on Green and Sustainable Chemistry, which now serves as a uniform guidance for various stakeholders to realise innovation actions and assess management practices for green and sustainable chemistry. Despite its significance, the Framework Manual is not widely known, as it has hardly been analysed, and more seriously, its legal classification has not been examined so far. The aim of this paper is to fill this gap and analyse the Framework Manual from a regulatory viewpoint. In line with this, the study presents the main characteristics of the document, determines the correct legal classification of the document, and makes recommendations regarding the possible improvements of the document and the future regulating options for green and sustainable chemistry. By analysing these questions, the study arrives at significant results: Firstly, it declares that the Framework Manual is a legally non-binding, soft law document. Secondly, it identifies the advantages and disadvantages of soft law regulation. Thirdly, it concludes that the Framework Manual cannot be regarded as a final result. The topic of green and sustainable chemistry should be regulated in a legally binding form in the future. With these results, the study fills the huge gap in legal analysis of the Framework Manual and contributes to the satisfactory future regulation of green and sustainable chemistry.
Open Access: Yes
DOI: 10.3303/CET25121018
