Informatics

10 pages, 644 KiB

Open AccessArticle

Enhanced Preoperative Pancreatoduodenectomy Patient Education Using Mixed Reality Technology: A Randomized Controlled Pilot Study

by Jessica Heard, Paul Murdock, Juan Malo, Joseph Lim, Sourodip Mukharjee and Rohan Jeyarajah

Informatics 2025, 12(2), 42; https://doi.org/10.3390/informatics12020042 - 23 Apr 2025

Abstract

(1) Background: Mixed Reality (MR) technology, such as the HoloLens, offers a novel approach to preoperative education. This study evaluates its feasibility and effectiveness in improving patient comprehension and comfort during informed consent for pancreatoduodenectomy. (2) Methods: A single-center, randomized, controlled pilot study [...] Read more.

(1) Background: Mixed Reality (MR) technology, such as the HoloLens, offers a novel approach to preoperative education. This study evaluates its feasibility and effectiveness in improving patient comprehension and comfort during informed consent for pancreatoduodenectomy. (2) Methods: A single-center, randomized, controlled pilot study was conducted between February and May 2023. Patients recommended for pancreatoduodenectomy were randomized into a control group receiving standard education or an intervention group using the HoloLens. Pre- and post-intervention surveys assessed patient understanding and comfort. (3) Results: Nineteen patients participated (8 HoloLens, 11 control). Both groups showed improved comprehension post-intervention, but only the HoloLens group demonstrated a statistically significant increase (Z = −2.524, p = 0.012). MR users had a greater understanding of surgical steps compared to controls, and 75% of participants in both groups reported high comfort levels with the surgery. MR integration was feasible and did not disrupt clinical workflow. (4) Conclusions: These findings suggest that MR can enhance preoperative education for complex procedures. However, limitations include the small sample size and single-center design, necessitating larger studies to confirm its broader applicability. MR-based education represents a promising tool to improve patient engagement and comprehension in surgical decision making. Full article

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22 pages, 2500 KiB

Open AccessArticle

Are We Inclusive? Accessibility Challenges in Philippine E-Government Websites

by Paul Bokingkito, Jr., Jerame Beloy, Jerina Jean Ecleo, Apple Rose Alce, Nenen Borinaga and Adrian Galido

Informatics 2025, 12(2), 41; https://doi.org/10.3390/informatics12020041 - 15 Apr 2025

Viewed by 149

Abstract

Web accessibility is essential for e-government in the Philippines to ensure that all citizens, including those with disabilities, can access important information and services. This study evaluates government web accessibility using the Web Content Accessibility Guidelines 2.0 from the World Wide Web Consortium [...] Read more.

Web accessibility is essential for e-government in the Philippines to ensure that all citizens, including those with disabilities, can access important information and services. This study evaluates government web accessibility using the Web Content Accessibility Guidelines 2.0 from the World Wide Web Consortium and web presence based on the Government Website Template Design guidelines. A combination of automated testing tools and visual inspections was used for the assessment. Results showed significant discrepancies between web presence and web accessibility. Web presence compliance ranged from 28% to 82.67%, averaging 53.43%. Web accessibility scored higher, with compliance rates ranging from 62.32% to 97.1% and an average of 82.5%. This indicates that while many government agencies have focused on accessibility, there is a need to improve their digital services and visibility. A well-structured and user-friendly website is vital. However, without expanded online services, mobile accessibility, and transactional features, the full potential of digital governance remains untapped. Future studies are directed to aid government agencies with adopting accessible design principles, conducting regular audits, collaborating with disability advocacy groups, and integrating assistive technologies to foster a more inclusive and efficient digital government ecosystem. Full article

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14 pages, 268 KiB

Open AccessArticle

Machine Learning Applied to Improve Prevention of, Response to, and Understanding of Violence Against Women

by Mariana Carolyn Cruz-Mendoza, Roberto Angel Melendez-Armenta, Juana Canul-Reich and Julio Muñoz-Benítez

Informatics 2025, 12(2), 40; https://doi.org/10.3390/informatics12020040 - 11 Apr 2025

Viewed by 177

Abstract

Intimate partner violence (IPV) remains a critical issue that requires data-driven solutions to improve victim profiling and intervention strategies. This study introduces Mujer Segura, an innovative web application designed to collect structured data on IPV cases and predict their severity using machine learning [...] Read more.

Intimate partner violence (IPV) remains a critical issue that requires data-driven solutions to improve victim profiling and intervention strategies. This study introduces Mujer Segura, an innovative web application designed to collect structured data on IPV cases and predict their severity using machine learning models. The methodology integrates Random Forest (RF) and Gradient Boosting Classifier (GBC) algorithms to classify IPV cases by leveraging historical data for predictive analysis. The RF model achieved an accuracy of 97%, with a precision of 1.00 for non-severe cases and 0.96 for severe cases, recall values of 0.93 and 1.00 respectively, and an ROC AUC of 0.9534. The GBC model demonstrated an accuracy of 89%, with a precision of 1.00 for non-severe cases and 0.98 for severe cases, recall values of 0.95 and 1.00 respectively, and an ROC AUC of 0.9891. The application also integrates geospatial visualization tools to identify high-risk areas in the State of Mexico, enabling real-time interventions. These findings confirm that machine learning can enhance the timely detection of IPV cases and support evidence-based decision-making for public safety agencies. Full article

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24 pages, 734 KiB

Open AccessArticle

Transparency Unleashed: Privacy Risks in the Age of E-Government

by Cristian Paguay-Chimarro, David Cevallos-Salas, Ana Rodríguez-Hoyos and José Estrada-Jiménez

Informatics 2025, 12(2), 39; https://doi.org/10.3390/informatics12020039 - 11 Apr 2025

Viewed by 281

Abstract

E-government and transparency are significantly improving public service management by encouraging trust, accountability, and the massive participation of citizens. On the one hand, e-government has facilitated online services to address bureaucratic processes more efficiently. On the other hand, transparency has promoted open access [...] Read more.

E-government and transparency are significantly improving public service management by encouraging trust, accountability, and the massive participation of citizens. On the one hand, e-government has facilitated online services to address bureaucratic processes more efficiently. On the other hand, transparency has promoted open access to public information from the State so that citizens can understand and track aspects of government processes more effectively. However, as both require extensive citizen information management, these initiatives may significantly compromise privacy by exposing personal data. To assess these privacy risks in a concrete scenario, we analyzed 21 public institutions in Ecuador through a proposed taxonomy of 6 categories and 17 subcategories of disclosed personal data on their online portals and websites due to LOTAIP transparency initiative. Moreover, 64 open-access systems from these 21 public institutions that accomplish e-government principles were analyzed through a proposed taxonomy of 8 categories and 77 subcategories of disclosed personal data. Our results suggest that personal data are not handled through suitable protection mechanisms, making them extremely vulnerable to manual and automated exfiltration attacks. The lack of awareness campaigns in Ecuador has also led many citizens to handle their personal data carelessly without being aware of the associated risks. Moreover, Ecuadorian citizens’ privacy is significantly compromised, including personal data from children and teenagers being intentionally exposed through e-government and transparency initiatives. Full article

(This article belongs to the Section Social Informatics and Digital Humanities)

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18 pages, 5048 KiB

Open AccessReview

Clustering with Uncertainty: A Literature Review to Address a Cross-Domain Perspective

by Salvatore Flavio Pileggi

Informatics 2025, 12(2), 38; https://doi.org/10.3390/informatics12020038 - 9 Apr 2025

Viewed by 270

Abstract

Clustering is a very popular computational technique that, because of imperfect data, is often applied in the presence of some kind of uncertainty. Taking into account such an uncertainty (and model), the computational output accordingly contributes to increasing the accuracy of the computations [...] Read more.

Clustering is a very popular computational technique that, because of imperfect data, is often applied in the presence of some kind of uncertainty. Taking into account such an uncertainty (and model), the computational output accordingly contributes to increasing the accuracy of the computations and their effectiveness in context. However, there are challenges. This paper presents a literature review on the topic. It aims to identify and discuss the associated body of knowledge according to a cross-domain perspective. A semi-systematic methodology has allowed for the selection of 68 papers, prioritizing the most recent contributions and an intrinsic application-oriented approach. The analysis has underscored the relevance of the topic in the last two decades, in which computation has become somewhat pervasive in the context of inherent data complexity. Furthermore, it has identified a trend of domain-specific solutions over generic-purpose approaches. On one side, this trend enables a more specific set of solutions within specific communities; on the other side, the resulting distributed approach is not always well integrated with the mainstream. The latter aspect may generate a further fragmentation of the body of knowledge, mostly because of some lack of abstraction in the definition of specific problems. While in general terms these gaps are largely understandable within the research community, a lack of implementations to provide ready-to-use resources is critical overall. In more technical terms, solutions in the literature present a certain inclination to mixed methods, in addition to the classic application of Fuzzy Logic and other probabilistic approaches. Last but not least, the propagation of the uncertainty in the current technological context, characterised by data and computational intensive solutions, is not fully analysed and critically discussed in the literature. The conducted analysis intrinsically suggests consolidation and enhanced operationalization though Open Software, which is crucial to establish scientifically sound computational frameworks. Full article

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17 pages, 5441 KiB

Open AccessArticle

Enhancing Cultural Heritage Accessibility Through Three-Dimensional Artifact Visualization on Web-Based Open Frameworks

by Sasithorn Rattanarungrot, Martin White and Supaporn Chairungsee

Informatics 2025, 12(2), 37; https://doi.org/10.3390/informatics12020037 - 9 Apr 2025

Viewed by 243

Abstract

This paper presents an innovative approach to cultural heritage preservation through the development of an open framework that leverages RESTful APIs to make high-fidelity 3D models of cultural artifacts accessible to any application. Focusing on antique kitchenware utensils from the Nakhon Si Thammarat [...] Read more.

This paper presents an innovative approach to cultural heritage preservation through the development of an open framework that leverages RESTful APIs to make high-fidelity 3D models of cultural artifacts accessible to any application. Focusing on antique kitchenware utensils from the Nakhon Si Thammarat National Museum in Thailand, this research utilizes photogrammetry to create detailed 3D models, which are then made available on a web-based platform, accessible globally via standardized HTTP requests. The framework enables real-time access to 3D cultural content, overcoming the geographical and physical barriers that often limit access to cultural heritage. By integrating these 3D models into RESTful APIs, the project not only preserves delicate artifacts but also enhances their educational and cultural value through interactive accessibility. This system demonstrates the practical application of digital preservation technologies and sets a precedent for future initiatives aiming to digitize and disseminate cultural artifacts more broadly. The implications of this study extend beyond preservation to include enhanced global accessibility, enriched educational resources, and a more inclusive approach to cultural engagement. This project illustrates the transformative potential of digital technologies in preserving, accessing, and experiencing cultural heritage worldwide. Full article

(This article belongs to the Section Human-Computer Interaction)

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22 pages, 297 KiB

Open AccessArticle

Exploring the Ethical Implications of Using Generative AI Tools in Higher Education

by Elena Đerić, Domagoj Frank and Dijana Vuković

Informatics 2025, 12(2), 36; https://doi.org/10.3390/informatics12020036 - 7 Apr 2025

Viewed by 602

Abstract

A significant portion of the academic community, including students, teachers, and researchers, has incorporated generative artificial intelligence (GenAI) tools into their everyday tasks. Alongside increased productivity and numerous benefits, specific challenges that are fundamental to maintaining academic integrity and excellence must be addressed. [...] Read more.

A significant portion of the academic community, including students, teachers, and researchers, has incorporated generative artificial intelligence (GenAI) tools into their everyday tasks. Alongside increased productivity and numerous benefits, specific challenges that are fundamental to maintaining academic integrity and excellence must be addressed. This paper examines whether ethical implications related to copyrights and authorship, transparency, responsibility, and academic integrity influence the usage of GenAI tools in higher education, with emphasis on differences across academic segments. The findings, based on a survey of 883 students, teachers, and researchers at University North in Croatia, reveal significant differences in ethical awareness across academic roles, gender, and experience with GenAI tools. Teachers and researchers demonstrated the highest awareness of ethical principles, personal responsibility, and potential negative consequences, while students—particularly undergraduates—showed lower levels, likely due to limited exposure to structured ethical training. Gender differences were also significant, with females consistently demonstrating higher awareness across all ethical dimensions compared to males. Longer experience with GenAI tools was associated with greater ethical awareness, emphasizing the role of familiarity in fostering understanding. Although strong correlations were observed between ethical dimensions, their connection to future adoption was weaker, highlighting the need to integrate ethical education with practical strategies for responsible GenAI tool use. Full article

17 pages, 5507 KiB

Open AccessArticle

Markov-CVAELabeller: A Deep Learning Approach for the Labelling of Fault Data

by Christian Velasco-Gallego and Nieves Cubo-Mateo

Informatics 2025, 12(2), 35; https://doi.org/10.3390/informatics12020035 - 25 Mar 2025

Viewed by 271

Abstract

The lack of fault data is still a major concern in the area of smart maintenance, as these data are required to perform an adequate diagnostics and prognostics of the system. In some instances, fault data are adequately collected, even though the fault [...] Read more.

The lack of fault data is still a major concern in the area of smart maintenance, as these data are required to perform an adequate diagnostics and prognostics of the system. In some instances, fault data are adequately collected, even though the fault labels are missing. Accordingly, the development of methodologies that generate these missing fault labels is required. In this study, Markov-CVAELabeller is introduced in an attempt to address the lack of fault label challenge. Markov-CVAELabeller comprises three main phases: (1) image encoding through the application of the first-order Markov chain, (2) latent space representation through the consideration of a convolutional variational autoencoder (CVAE), and (3) clustering analysis through the implementation of k-means. Additionally, to evaluate the accuracy of the method, a convolutional neural network (CNN) is considered as part of the fault classification task. A case study is also presented to highlight the performance of the method. Specifically, a hydraulic test rig is considered to assess its condition as part of the fault diagnosis framework. Results indicate the promising applications that this type of methods can facilitate, as the average accuracy presented in this study was 97%. Full article

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17 pages, 5550 KiB

Open AccessArticle

Offline System for 2D Indoor Navigation Utilizing Advanced Data Structures

by Jorge Luis Veloz, Leo Sebastián Intriago, Jean Carlos Palma, Andrea Katherine Alcívar-Cedeño, Álvaro Antón-Sacho, Pablo Fernández-Arias, Edwan Anderson Ariza and Diego Vergara

Informatics 2025, 12(2), 34; https://doi.org/10.3390/informatics12020034 - 21 Mar 2025

Viewed by 291

Abstract

This study introduces a robust offline system for 2D indoor navigation, developed to address common challenges such as complex layouts and connectivity constraints in diverse environments. The system leverages advanced spatial modeling techniques to optimize pathfinding and resource efficiency. Utilizing a structured development [...] Read more.

This study introduces a robust offline system for 2D indoor navigation, developed to address common challenges such as complex layouts and connectivity constraints in diverse environments. The system leverages advanced spatial modeling techniques to optimize pathfinding and resource efficiency. Utilizing a structured development process, the proposed solution integrates lightweight data structures and modular components to minimize computational load and enhance scalability. Experimental validation involved a comparative approach: traditional navigation methods were assessed against the proposed system, focusing on usability, search efficiency, and user satisfaction. The results demonstrate that the offline system significantly improves navigation performance and user experience, particularly in environments with limited connectivity. By providing intuitive navigation tools and seamless offline operation, the system enhances accessibility for users in educational and other complex settings. Future work aims to extend this approach to incorporate additional features, such as dynamic adaptability and expanded application in sectors like healthcare and public services. Full article

(This article belongs to the Section Human-Computer Interaction)

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Informatics, Volume 12, Issue 2 (June 2025) – 9 articles

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