Search Results (244)

Background: Pancreatic cancer is the least survivable malignancy, with five-year survival below 10%. Its vague, non-specific symptoms contribute to late diagnosis and poor outcomes. Targeted education for healthcare professionals, students, patients, carers, and the public may improve awareness, confidence, and early help-seeking. This scoping review aimed to map and synthesize peer-reviewed evidence on pancreatic cancer education, identifying intervention types, outcomes, and gaps in knowledge. Methods: A scoping review was undertaken using the Joanna Briggs Institute (JBI) framework and the Arksey and O’Malley framework and reported in accordance with PRISMA-ScR guidelines. The protocol was registered on the Open Science Framework. Four databases (MEDLINE, Embase, CINAHL, PsycINFO) were searched for English-language, peer-reviewed studies evaluating educational interventions on pancreatic cancer for healthcare students, professionals, patients, carers, or the public. Grey literature was excluded to maintain a consistent methodological standard. Data were charted and synthesised narratively. Results: Nine studies (2018–2024) met inclusion criteria, predominantly from high-income countries. Interventions targeted students and professionals (n = 3), patients (n = 2), the public (n = 2), or mixed groups (n = 2), using modalities such as team-based learning, workshops, virtual reality, serious games, and digital animations. Four interrelated themes were identified, encompassing (1) Self-efficacy; (2) Knowledge; (3) Behavior; and (4) Acceptability. Digital and interactive approaches demonstrated particularly strong engagement and learning gains. Conclusions: Pancreatic cancer education shows clear potential to enhance knowledge, confidence, and engagement across diverse audiences. Digital platforms offer scalable opportunities but require quality assurance and long-term evaluation to sustain impact. The evidence base remains limited and fragmented, highlighting the need for validated outcome measures, longitudinal research, and greater international representation to support the integration of education into a global pancreatic cancer control strategy. Future studies should also evaluate how educational interventions influence clinical practice and real-world help-seeking behaviour. Full article

Fog computing has revolutionized the world by providing its services close to the user premises, which results in reducing the communication latency for many real-time applications. This communication latency has been a major constraint in cloud computing and ultimately causes user dissatisfaction due to slow response time. Many real-time applications like smart transportation, smart healthcare systems, smart cities, smart farming, video surveillance, and virtual and augmented reality are delay-sensitive real-time applications and require quick response times. The response delay in certain critical healthcare applications might cause serious loss to health patients. Therefore, by leveraging fog computing, a substantial portion of healthcare-related computational tasks can be offloaded to nearby fog nodes. This localized processing significantly reduces latency and enhances system availability, making it particularly advantageous for time-sensitive and mission-critical healthcare applications. Due to close proximity to end users, fog computing is considered to be the most suitable computing platform for real-time applications. However, fog devices are resource constrained and require proper resource management techniques for efficient resource utilization. This study presents an optimized resource allocation and scheduling framework for delay-sensitive healthcare applications using a Modified Particle Swarm Optimization (MPSO) algorithm. Using the iFogSim toolkit, the proposed technique was evaluated for many extensive simulations to obtain the desired results in terms of system response time, cost of execution and execution time. Experimental results demonstrate that the MPSO-based method reduces makespan by up to 8% and execution cost by up to 3% compared to existing metaheuristic algorithms, highlighting its effectiveness in enhancing overall fog computing performance for healthcare systems. Full article

The rapid proliferation of metaverse platforms with heterogeneous architectures, functionalities, and purposes poses a significant challenge for informed technology selection. Consequently, there is a need for structured evaluation approaches that enable comparison based on functional and non-functional attributes relevant to specific application contexts. The objective of this study was to propose a model for evaluating the quality of metaverse-type platforms based on a hybridization of the aspects defined in the ISO/IEC 25000 family of standards, a maturity model extracted from recent literature, and the Metagon metaverse characterization typology. The proposed model operationalizes 35 evaluation attributes grouped into seven categories, enabling a comprehensive assessment of metaverse platforms. Using this model, 23 metaverse platforms were evaluated through a hierarchical ranking strategy with tolerance. The results show that platforms such as Decentraland and Roblox achieve the highest levels of maturity (ML5), although open-architecture platforms demonstrated superior structural robustness in comparative tie-breakers. The results provide a taxonomy of characteristics refined and validated by experts and used in the evaluation of the analyzed platforms, resulting in a reproducible classification that enables systematic comparison across different application contexts. The discussion presents the basis for future studies focused on the evaluation of specific categories, such as educational, therapeutic, or social interaction platforms. Full article

Digital art repositories strive to disseminate works of art through the World Wide Web and to reach the widest possible global audience. To that end, providing an optimal user experience (UX) is essential. Usability is the cornerstone of UX in all interactions between the visitor and the platform, but at the same time, as virtual places of art and culture, digital art repositories aim to also provide an aesthetically pleasing interface that stimulates the senses. These goals are not always aligned, and how end users perceive the interplay between aesthetics and usability is an important factor in creating a balanced UX. This study presents a streamlined methodology for the collection of visitor insights concerning aesthetics and usability, taking advantage of the attention tracking capabilities of the iMedius platform. The iMedius Form Builder digital research tool allows the collection of both self-reported feedback through survey replies and candid data through gaze and mouse tracking, thus creating a robust dataset that can lead to interesting insights. An interactive questionnaire investigating user reaction to three different digital art repositories is presented, and feedback from higher education students from the fields of digital art and media is presented and analyzed in detail. Through this analysis, interesting insights are derived regarding striking a balance between high usability and memorable aesthetics. Full article

Reliable transfer of control policies from simulation to real-world robotic systems remains a central challenge in robotics, particularly for car-like mobile robots. Digital Twin (DT) technology provides a robust framework for high-fidelity replication of physical platforms and bi-directional synchronization between virtual and real environments. In this study, a DT-based testbed is developed to train and evaluate an imitation learning (IL) control framework in which a neural network policy learns to replicate the behavior of a hybrid Model Predictive Control (MPC)–Backstepping expert controller. The DT framework ensures consistent benchmarking between simulated and physical execution, supporting a structured and safe process for policy validation and deployment. Experimental analysis demonstrates that the learned policy effectively reproduces expert behavior, achieving bounded trajectory-tracking errors and stable performance across simulation and real-world tests. The results confirm that DT-enabled IL provides a viable pathway for Sim2Real transfer, accelerating controller development and deployment in autonomous mobile robotics. Full article

Virtual museums are increasingly adopted to sustain public engagement with cultural heritage, yet the mechanisms through which virtual exhibition experiences motivate on-site visitation remain underexplored. Drawing on the Stimulus–Organism–Response (SOR) framework and extending the Information Systems Success Model (IS Success Model), this study proposes and tests a psychological pathway linking virtual museum experience quality to offline visiting intention. Using the official website of the Sanxingdui Museum as the empirical context, we surveyed 467 users in China who explored the virtual exhibition but had never visited the museum in person. Virtual exhibition experience quality was operationalised through five dimensions: information quality, system quality, perceived interactivity, perceived authenticity and perceived enjoyment. Perceived cultural value and cultural identity were specified as mediators. Structural equation modelling revealed that higher levels of virtual exhibition experience quality significantly enhanced perceived cultural value and cultural identity. Perceived cultural value, in turn, positively predicted cultural identity, and both constructs were positively associated with intention to visit the physical museum, with a significant sequential mediation from experience quality to offline visiting intention via perceived cultural value and cultural identity. These findings clarify how virtual heritage platforms can foster cognitive appreciation and emotional identification that translate into real-world visitation, offering guidance for designing sustainable digital pathways to long-term engagement with cultural institutions. Full article

The metaverse represents a transformative integration of virtual and physical worlds, offering unprecedented opportunities for social interaction, commerce, education, healthcare, and entertainment. Establishing trust in these expansive and decentralized environments remains a critical challenge. Blockchain technology, with its decentralized, secure, and immutable nature, is emerging as an essential pillar of trust and digital asset ownership within the metaverse. This paper provides an extensive review of blockchain-enabled trust and reputation frameworks specifically tailored to metaverse ecosystems. We present an in-depth analysis of existing blockchain solutions across diverse metaverse domains, including gaming, virtual real estate, healthcare, and education. Our core contributions include a comprehensive taxonomy that classifies current trust and reputation schemes by their underlying mechanisms, threat models addressed, and their architectural strategies. We provide a comparative benchmark analysis evaluating key performance metrics such as security robustness, scalability, user privacy, and cross-platform interoperability, revealing critical trade-offs inherent in current designs. Our analysis finds that score-based designs trade scalability for nuanced reputation representation, while SSI- and SBT-based approaches improve Sybil-resistance but introduce significant privacy governance challenges. Finally, we outline unresolved research challenges, including cross-platform reputation portability, privacy-preserving computation, real-time trust management, and standardized governance structures. Full article

In recent years, several countries have introduced strategic plans aimed at promoting metaverse ecosystems. While these initiatives highlight the metaverse as both a technological frontier and a policy priority, the underlying rationales and metaverse approaches remain insufficiently understood. This gap raises the need to critically examine why governments are investing in the metaverse ecosystem and how metaverse is being approached as an innovative platform for digital public services and businesses. An inductive and deductive content analysis was conducted on various regional, national and supranational metaverse strategic plans (n = 7). Virtual worlds can be understood as persistent, immersive, and interactive digital environments that integrate 3D visualisation, simulation, and real-time data to support activities across social and economic domains. The findings indicate that the metaverse is a virtual space shaped by the dual imperative of addressing societal needs—such as public service delivery and stakeholder engagement—and fostering business opportunities within the evolving digital ecosystem. The analysis revealed four main reasons to promote the social and industrial metaverse ecosystem: sustainability; digital sovereignty; competitive advantage and stakeholder building relationship. The results indicate that the metaverse operates mainly through both transactional and connected approaches, where digital twins, artificial intelligence, and extended reality converge to enable user experiences in ways that transcend physical limitations. Full article

The Digital Twin (DT) model within a Digital Twin System (DTS) serves as a real-time digital representation of its corresponding physical entity. It is a dynamic, interconnected model that enables real-time optimization in its application environment, allowing for the simulation, monitoring, evaluation, and control of the physical counterpart’s state and behavior while facilitating data-driven decision-making. In engineering practice, most scholars focus on data visualization and twin system construction. However, a complete digital twin system not only requires numerical representation of the real-time state of the physical entity but also sometimes requires real-time mechanical behavior analysis of the physical entity. Thus, a robust mechanical analysis module becomes essential within the DTS framework. Integrating a general-purpose mechanical analysis platform into the DTS offers an effective solution, thereby necessitating the development of novel fusion techniques for multi-source heterogeneous data. This study takes the integration of the Midas Civil mechanical analysis platform with a digital twin system as an example. By utilizing the API provided by Midas Civil, we develop a synchronization technique for virtual-physical systems, capable of handling and modeling multi-source heterogeneous data. This enables real-time mechanical computation and analysis within the DTS, facilitating the dynamic updating and aggregation of both simulation data from mechanical analysis and monitoring data from the physical entity. Consequently, the digital twin system can predict mechanical behaviors in the virtual domain, providing a more accurate representation of the real-world physical system’s state and dynamics. Full article

With the increasing adoption of virtual reality (VR) in research and training applications, reliable stress detection in naturalistic settings remains challenging, particularly when hardware complexity must be minimized. This study presents an enhanced framework for real-time stress recognition in VR environments that integrates behavioral interactions with selectively derived physiological signals. Building upon previous architectures, the proposed framework incorporates pre-task baseline measurements to account for subject-specific and session-initial variability. While the comprehensive analysis employs a three-class affective framework, the practical implementation focuses on binary stress detection for real-world VR applications. Stress detection is achieved through VR-based behavioral signals, complemented by minimal input from a Galvanic Skin Response (GSR) sensor. The experimental evaluation demonstrates that baseline calibration improves separation across stress conditions. Quantitatively, the proposed Weighted Baseline Detector (WBD) achieved a classification accuracy of 94.17% and an Area Under the Curve (AUC) of 0.9993, outperforming the fixed global baseline approach (85.0% accuracy, AUC 0.9067), which demonstrates the effectiveness of the proposed calibration method. Rigorous cross-validation confirms that the approach achieves stable performance with statistical significance across stress conditions. These findings highlight the potential of combining behavioral analysis with physiological support to develop practical, low-hardware VR platforms for live stress recognition. Full article

In the context of rapidly growing logistics demand, traditional warehouse management methods are inadequate in meeting contemporary efficiency and accuracy requirements. The present study proposes the development of an intelligent warehouse visualization platform, the objective of which is to address issues such as high labor dependency, opaque inventory, and operational inefficiencies. The construction of a virtual warehouse environment was undertaken using Unity3D, with the aim of simulating real-world zones. These comprised storage areas, automatic guided vehicle (AGV) pathways, and operational spaces. The platform incorporates radio frequency identification devices (RFID) for item tracking and a role-based access system, enabling real-time monitoring and management of inbound, inventory, and outbound processes. In order to optimize AGV path planning, the proposed algorithm incorporates a dynamic weighted heuristic, a five-neighborhood search, a bidirectional search, and Bézier curve-based smoothing. The efficacy of these enhancements has been demonstrated through a reduction in searched nodes, computation time, and path length, while simultaneously enhancing smoothness. As demonstrated by simulations conducted in Unity3D, the optimized algorithm exhibits a reduction in search nodes of 59.19%, in time of 45.41%, and in path length of 18%, in comparison with the conventional A-star algorithm. The platform offers a safe, efficient, and scalable solution for enterprise training and operational simulation, contributing valuable insights for intelligent warehouse upgrading. Full article

Background: During postoperative recovery, patients and their caregivers often lack crucial information, leading to numerous repetitive inquiries that burden healthcare providers. Traditional discharge materials, including paper handouts and patient portals, are often static, overwhelming, or underutilized, leading to patient overwhelm and contributing to unnecessary ER visits and overall healthcare overutilization. Conversational chatbots offer a solution, but Natural Language Processing (NLP) systems are often inflexible and limited in understanding, while powerful Large Language Models (LLMs) are prone to generating “hallucinations”. Objective: To combine the deterministic framework of traditional NLP with the probabilistic capabilities of LLMs, we developed the AI Virtual Assistant (AIVA) Platform. This system utilizes a retrieval-augmented generation (RAG) architecture, integrating Gemini 2.0 Flash with a medically verified knowledge base via Google Vertex AI, to safely deliver dynamic, patient-facing postoperative guidance grounded in validated clinical content. Methods: The AIVA Platform was evaluated through 750 simulated patient interactions derived from 250 unique postoperative queries across 20 high-frequency recovery domains. Three blinded physician reviewers assessed formal system performance, evaluating classification metrics (accuracy, precision, recall, F1-score), relevance (SSI Index), completeness, and consistency (5-point Likert scale). Safety guardrails were tested with 120 out-of-scope queries and 30 emergency escalation scenarios. Additionally, groundedness, fluency, and readability were assessed using automated LLM metrics. Results: The system achieved 98.4% classification accuracy (precision 1.0, recall 0.98, F1-score 0.9899). Physician reviews showed high completeness (4.83/5), consistency (4.49/5), and relevance (SSI Index 2.68/3). Safety guardrails successfully identified 100% of out-of-scope and escalation scenarios. Groundedness evaluations demonstrated strong context precision (0.951), recall (0.910), and faithfulness (0.956), with 95.6% verification agreement. While fluency and semantic alignment were high (BERTScore F1 0.9013, ROUGE-1 0.8377), readability was 11th-grade level (Flesch–Kincaid 46.34). Conclusion: The simulated testing demonstrated strong technical accuracy, safety, and clinical relevance in simulated postoperative care. Its architecture effectively balances flexibility and safety, addressing key limitations of standalone NLP and LLMs. While readability remains a challenge, these findings establish a solid foundation, demonstrating readiness for clinical trials and real-world testing within surgical care pathways. Full article

Estimating design hydrographs in small and ungauged basins remains a significant challenge, primarily due to limited hydrometeorological data and the operational complexity of advanced modelling tools. This study presents an interactive digital twin platform to support hydrological modelling in such contexts. The aim of the proposed platform is to integrate three hydrological models—EBA4SUB (event-based rainfall–runoff model), COSMO4SUB (continuous rainfall–runoff model), and Virtual Rain (stochastic rainfall generator)—and automates key pre-processing tasks, including watershed delineation, Curve Number estimation, and rainfall input generation. Built on a three-tier architecture, the system comprises an interactive front end, a back-end database with spatial and meteorological data, and a suite of computational routines developed in Python and C#. The platform was deployed across the Lazio Region (Italy) for basins with contributing areas smaller than 400 km². Users can interactively select watersheds via a map-based interface, obtain preliminary hydrological characterizations, and export model-ready inputs and outputs. The proposed platform offers several advantages: it reduces model preparation time, facilitates access to advanced modelling tools, standardizes input data at the regional level, and ensures reproducible pre-processing workflows. By lowering the technical and time barriers of hydrological modelling, the digital twin provides an effective framework for bringing science-based tools closer to real-world practice. Full article

Omnidirectional vision systems enable panoramic perception for autonomous navigation and large-scale mapping, but physical testbeds are costly, resource-intensive, and carry operational risks. We develop a virtual simulation platform for multi-view omnidirectional vision that supports flexible camera configuration and cross-platform data streaming for efficient processing. Building on this platform, we propose and validate a reconstruction and ranging method that fuses multi-view omnidirectional images with structured-light projection. The method achieves high-precision obstacle contour reconstruction and distance estimation without extensive physical calibration or rigid hardware setups. Experiments in simulation and the real world demonstrate distance errors within 8 mm and robust performance across diverse camera configurations, highlighting the practicality of the platform for omnidirectional vision research. Full article

As immersive technologies reshape how people experience identity, emotion, and loss, virtual memorialization is emerging as an important application of virtual reality. This study examines the psychological mechanisms influencing user intentions to engage in virtual memorialization by extending the Technology Acceptance Model (TAM) to incorporate Avatar Attachment and Social Identity theories. A survey of 437 participants with diverse experiences in virtual worlds and memorial practices was analyzed using structural equation modeling. The results show that Avatar Attachment (AA) and Social Identity (SI) significantly predict perceived usefulness (PU), Perceived Role Importance (PRI), and behavioral intention (BI), with PU and PRI mediating these effects. Perceived ease of use (PEOU) directly influences both PU and BI. Furthermore, perceived human-likeness (PHL) moderates the effect of AA on PU, indicating that anthropomorphic avatars enhance the perceived emotional value of memorialization. However, PHL does not moderate the AA–PRI pathway, suggesting that the salience of avatars in mourning contexts relies more on narrative identity than visual realism. This research advances the application of TAM in immersive environments and contributes to digital thanatology by highlighting the interplay between identity, emotion, and technology. The findings provide design implications for creating user-friendly and emotionally meaningful virtual memorial platforms within emerging VR ecosystems. Full article