Search Results (223)

Our article AI, cultural heritage, and bias examines the challenges and potential solutions for using machine learning to interpret and classify human memory and cultural heritage artifacts. We argue that bias is inherent in cultural heritage collections (CHCs) and their digital versions and that AI pipelines may amplify this bias. We hypothesise that effective AI methods require vast, well-annotated datasets with structured metadata, which CHCs often lack due to diverse digitisation practices and limited interconnectivity. This paper discusses the definition of bias in CHCs and other datasets, exploring how it stems from training data and insufficient humanities expertise in generative platforms. We conclude that scholarship, guidelines, and policies on AI and CHCs should address bias as both inherent and augmented by AI technologies. We recommend implementing bias mitigation techniques throughout the process, from collection to curation, to support meaningful curation, embrace diversity, and cater to future heritage audiences. Full article

Studying historical rural landscapes beyond their archaeological and cultural significance, as has typically been addressed in previous research, is important in the context of current environmental challenges. Some historical rural landscapes, such as Roman land divisions, have persisted for more than 2000 years and may still contribute to sustainability goals. To assess this topic, the hydraulic and vegetation network of the centuriation northeast of Padua were studied, emphasising their multiple benefits. Their length, distribution, and evolution over time (2008–2022) were vectorised and measured using available digital terrain models and orthophotographs in a geographic information system (GIS). The results revealed a significant decline in the length of water ditches and hedgerows across almost all examined areas, despite their preservation being highlighted in regional and local spatial planning documents. These findings indicate the need for a better understanding of the local dynamics driving such trends and highlight the importance of adopting a more tailored approach to their planning. This study discusses the GIS metrics utilised and, in this way, contributes to landscape monitoring and restoration actions. Finally, a multifunctional approach to the sustainable planning of this area is proposed here—one that integrates the cultural archaeological heritage in question with environmental preservation and contemporary climate adaptation and mitigation strategies. Full article

Background: Health disparities related to socio-economic factors impact access to preventive health interventions. The PRECEDE–PROCEED model, a multidimensional approach to health promotion, has been adapted to optimise cancer screening programs in Lombardy, Italy, addressing these disparities. Methods: This study evaluated the application of systemic audits based on the PRECEDE–PROCEED model across Lombardy cancer screening programs. A systematic region-wide audit was performed in 2019, and follow-up audits were performed in 2022–2023. Data were collected using structured analysis methodologies, including epidemiological, behavioural, and organisational assessments. Results: The 2019 audit showed strengths in participation and quality standards but identified challenges in cervical cancer screening coverage and waiting times for assessments. Improvements plans included the digitisation of processes and stakeholder engagement. The 2022–2023 audits reported increased coverage for breast and colorectal screenings, but a slight decline in participation rates and examination coverage. Organisational improvements were noted, yet gaps in training and equity-targeted actions remained. Conclusion: The PRECEDE–PROCEED model audits led to notable improvements in the quality and equity of cancer screening programs in Lombardy. Sustained focus on digital integration, continuous re-training, and targeted equity interventions is essential for further progress. Full article

Collaborative Opportunities for Professional Inquiry Leading to Organisational Transformation (COPILOT) represents an Erasmus+ initiative involving four transnational partners from three EU countries including IES Cristobal de Monroy secondary school [Spain], Laois Offaly Education Training Board (LOETB) [Ireland], University College Dublin (UCD) School of Education [Ireland], and Akadimos, a teacher continuing professional development provider [Greece]. The project encompassed three primary objectives, aligned with the Erasmus+ programmes’s emphasis on supporting teachers and school leaders to address digital transformation. These included the following: the identification of participatory approaches and digital methodologies employed by schools to facilitate digital transformation among educators; exploring and establishing dynamic professional environments in schools by identifying synergies with organisations operating in diverse fields or socio-economic contexts and enhancing the capacity and professionalism of partners to engage in EU/international collaboration. To investigate the outcomes of the project objectives, a small-scale qualitative study was conducted, which involved analysing participants’ reports on the project’s collaborative activities. Additionally, a focus group was held at the conclusion of the project to gain insights into the digital readiness, capacity, and resilience of teachers and school leaders within their respective organisations. Thematic analysis was employed to analyse the collected data. The findings of the study offer encouraging indications regarding the crucial symbiotic role played by school leaders and “early adopter” teachers in promoting digital transformation. Moreover, participating teachers displayed a general willingness to adapt their teaching methods to incorporate more technology, provided they receive both formal and informal support. Furthermore, there exists a willingness among transnational partners to digitise and share resources both at present and in the future. Full article

To improve the problem-solving capabilities of students, this study explored using interactive digital teaching materials based on animation and manga. A classroom teaching system was developed based on teaching material using a manga format. Students from a national university and a science and technology university in southern Taiwan were recruited. A questionnaire survey was administered for data collection. A total of 104 valid samples were collected; the data were analysed using SPSS 17.0. Two statistically significant models could be used to predict learning outcomes, and the highest R2 value was 52.5%. The utilisation of interactive multimedia teaching materials based on animation and manga helped students apply knowledge to solve practical problems, cultivating their problem-solving capabilities. The findings differed from previous studies; models developed in this study could be used to determine the effects and relationships of multiple factors. Full article

The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and job creation. Data science can support SMEs to optimise production processes, anticipate customers’ needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of artificial intelligence (AI) and big data, and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to their limited resources and restricted access to financing. This paper presents trends and challenges towards effective data-driven decision making for organisations based on a 3-year long study which covered more than 85 UK SMEs, mostly from the West Midlands region of England. In particular, this study attempts to find answers to several key research questions around data science and AI adoption among UK SMEs, and the advantages of digitalisation and data-driven decision making, as well as the challenges hindering their effective utilisation of these technologies. We also present two case studies that demonstrate the potential of digitisation and data science, and use these as examples to unveil challenges and showcase the wealth of currently available opportunities for SMEs. Full article

Virtual Reality (VR) is and will be a key driver in the evolution of e-commerce, providing an immersive and gamified shopping experience. However, for VR shopping spaces to become a reality, retailers’ product catalogues must first be digitised into 3D models. While this may be a simple task for retail giants, it can be a major obstacle for small retailers, whose human and financial resources are often more limited, making them less competitive. Therefore, this paper presents an analysis of low-cost scanning technologies for small business owners to digitise their products and make them available on VR shopping platforms, with the aim of helping improve the competitiveness of small businesses through VR and Artificial Intelligence (AI). The technologies to be considered are photogrammetry, LiDAR sensors and NeRF.In addition to investigating which technology provides the best visual quality of 3D models based on metrics and quantitative results, these models must also offer good performance in commercial VR headsets. In this way, we also analyse the performance of such models when running on Meta Quest 2, Quest Pro and Quest 3 headsets (Reality Labs, Reality Labs, CA, USA) to determine their feasibility and provide use cases for each type of model from a scalability point of view. Finally, our work describes a model optimisation process that reduce the polygon count and texture size of high-poly models, converting them into more performance-friendly versions without significantly compromising visual quality. Full article

Piped drinking water supplies are exposed to a range of threats. Changing hazard situations arise from climate change, digitisation, and changing conditions in the power supply, among other things. Risk and crisis management adapted to the hazard situation can increase the resilience of the piped drinking water supply. Analogous to the risk management system, this article describes a methodology that ranges from hazard analysis with the prioritisation of 57 individual hazards to vulnerability assessment with the help of balance sheet structure models (BSM) and the planning and implementation of measures to increase the resilience of the piped drinking water supply in a targeted manner. The work steps mentioned build on each other and were tested using the case study of a water supply company in Saxony (Germany). As a result, priority hazards are identified, the remaining supply periods and replacement and emergency water requirements are determined as part of the vulnerability assessment, and finally, planning principles for increasing resilience are documented. The methodology focuses primarily on practicable application by water supply companies. Full article

This article analyses the ongoing processes in the organisational field of Italian schools in light of the innovations induced by digital education policies. Specifically, it focuses on the relationship between actors and digital policies concerning the experience of distance learning (DL) that characterised the period of the COVID-19 pandemic. The paper reflects on DL outcomes regarding the three expectations that have often characterised the rhetoric associated with the promotion of digital educational policies, namely: the raising of learning levels, the development of digital competences and the increase in school inclusion. Through an analysis of a series of empirical studies exploring the point of view of the paper, this paper highlights what progress has been made in the digital schooling in Italy and what are still its main limitations. The results of the study show both the limits of the effectiveness of educational policies constructed with a top-down approach and highlight the potential for policy recalibration offered by a reorganisation of the decision-making process through the active involvement of all the actors in the educational system. Full article

In the era of the climate emergency and different pandemics, systems that can provide an immediate response to housing needs are required. This paper aims to evaluate the use of fibre-reinforced plastic polymers (FRPs) to satisfy this need. In particular, a modular emergency housing system that utilises FRPs for structures and cladding is proposed, which proves adaptable to both different uses and different kinds of temporary or permanent buildings. By adapting modular emergency housing to different contexts, developing an integrated design process (IDP) and building information modelling (BIM) methodology, this research aims to provide innovations for the the architecture, engineering, and construction (AEC) sector, including FRPs, through a digitised approach, applied also to an experimental case study. A pilot unit of the modular emergency housing system, a nearly zero-energy building (nZEB), is described in detail, while laboratory tests are reported. Construction considerations confirm the sustainability and highlight the adaptability of the modular system to different housing needs conditions, justifying the possible future development of supply chain industrialisation supported by the presented methodology. Full article

This study examines the global literature that looks at spatial–visual abilities (SVA) while considering the numerous differential studies, methods of evaluation designed over a century, and multiple external influences on its development. The dataset was retrieved from Google Scholar and publisher databases such as Elsevier, Taylor & Francis, Springer, etc. Only factual reports and bibliographic reviews were included in an analysis of a total of 87 documents. Each study of SVA is classified based on information, country, year, and age groupings. SVA has been extensively studied in the areas of “STEM (Science, Technology, Engineering and Mathematics) fields”, “demographic factors” and “other activities”. “Spatial visualisation” or “visual ability” is the term employed to refer to the cognitive ability that allows one to comprehend, mentally process, and manipulate three-dimensional visuospatial shapes. One of the most crucial distinct abilities involved is spatial aptitude, which aids in understanding numerous aspects of everyday and academic life. It is especially vital for comprehending scientific concepts, and it has been extensively studied. Nearly all multiple-aptitude assessments include spatial ability. It is determined that over the past two decades, the study of SVA has gained momentum, most likely because of information being digitised. Within the vast reservoir of spatial-cognition research, the majority of the studies examined here originate from the United States of America, with less than a quarter of the studies based in the Asia–Pacific region and the Middle East. This paper presents a comprehensive review of the literature on the assessment of SVA with respect to sector, year, country, age and socio-economic factors. It also offers a detailed examination of the use of spatial interventions in educational environments to integrate spatial abilities with training in architecture and interior design. Full article

Android phones are widely recognised as the most popular mobile phone operating system. Additionally, tasks like browsing the internet, taking pictures, making calls, and sending messages may be completed with ease in daily life because of the functionality that Android phones offer. The number of situations in which users are harmed by unauthorised access to data emerging from these processes is growing daily. Because the Android operating system is open source and generated applications are not thoroughly reviewed before being released onto the market, this scenario has been the primary focus of hackers. Therefore, technologies to distinguish between malware and benign Android applications are required. CNN-based techniques are proven to produce important and successful outcomes when applied to Android malware detection on images. The CICMalDroid 2020 dataset, which is currently utilised in the literature, was used for this purpose. The features of the apps in the dataset were obtained using the AndroPyTool tool, and faster analysis files of 17,089 Android applications were obtained using the parallel execution technique. Permissions, intents, receivers, and services were used as static analysis features in this article. After these features were obtained, as data preprocessing, the ones with a grand total equal to 1 for each feature in the whole dataset were excluded in order to exclude the features that were specially created by the applications themselves. For each of the features specified for each application, a comma-separated text was obtained according to the usage status of the application. The BERT method was used to digitise the pertinent texts in order to create a unique embedding vector for every feature. Following the digitisation of the vectors, picture files were produced based on the length of each feature. To create a single image file, these image files were combined side by side. Finally, these image files were classified with CNNs. Experimental results were obtained by applying CNNs to the dataset used in the study. As a result of the experiments, a CNN with two outputs provided the highest performance with an accuracy of 91%, an F1-score of 89%, a Recall of 90%, and a Precision of 91%. Full article

This paper describes the requirements analysis phase towards the establishment and implementation of a municipal data utility (KDW = Kommunales Datenwerk, German) to facilitate data sharing between intra- and intermunicipal stakeholders. Against the backdrop of increasing digitisation and the growing importance of data-driven decision making in municipal governance, this paper aims to address the pressing need for efficient data management solutions within and across municipalities. Based on a structured self-developed methodology, the authors use a qualitative research approach: the paper examines the experiences and challenges encountered during the requirements phase, the design phase, and the development phase of the KDW. The findings indicate that the establishment of a robust KDW requires (1) extensive stakeholder engagement, (2) clear governance structures, and (3) a robust technical infrastructure. In addition, the study highlights the critical importance of establishing a sound legal framework that addresses data ownership, privacy, security and regulatory compliance. Addressing legal and regulatory barriers to data sharing is paramount to the successful implementation and operation of the KDW. The paper concludes by highlighting the potential benefits of KDWs and outlining future work. The overall methodology, approach, and outcome are validated within the city of Mainz, and the lessons learned are accommodated in the insights presented in the rest of the paper. Full article

Over the past two decades, environmental sustainability has become a key corporate and organisational issue. Today, firms are increasingly turning to existing and emerging digital technologies to help ensure that they meet the medium and long-term needs and expectations of customers and other stakeholders with respect to sustainability performance. This raises the important question of which digitisation factors most significantly impact environmental sustainability performance, as well as the mediating factor of sustainability innovation balance (the ability of a firm to balance the exploration of new innovations with the exploitation of existing innovations). A comprehensive survey instrument was developed and refined through expert feedback and a pilot study, leading to data collection from 374 professionals in the Freight and Logistics industry in Saudi Arabia, all of whom held senior positions in areas such as business development, IT, and Environmental, Social, and Governance (ESG) departments. This data was then analysed using structural equation modelling (SEM). The results of this analysis showed that the key factors impacting sustainability performance were digital competence, strategy alignment, digital adaptability, innovation exploitation and innovation exploration. These findings contribute to the current literature by expanding our understanding of the real-world drivers of sustainability performance. In practical terms, the study will help managers improve sustainability performance by enhancing resource efficiency, streamlining, and supply chain management, as well as improving employee engagement and training, fostering a culture of sustainability within the organisation. Full article

Arguments inspired by algorithmic information theory predict an inverse relation between the probability and complexity of output patterns in a wide range of input–output maps. This phenomenon is known as simplicity bias. By viewing the parameters of dynamical systems as inputs, and the resulting (digitised) trajectories as outputs, we study simplicity bias in the logistic map, Gauss map, sine map, Bernoulli map, and tent map. We find that the logistic map, Gauss map, and sine map all exhibit simplicity bias upon sampling of map initial values and parameter values, but the Bernoulli map and tent map do not. The simplicity bias upper bound on the output pattern probability is used to make a priori predictions regarding the probability of output patterns. In some cases, the predictions are surprisingly accurate, given that almost no details of the underlying dynamical systems are assumed. More generally, we argue that studying probability–complexity relationships may be a useful tool when studying patterns in dynamical systems. Full article