A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks

Ropero, Rosa F.; Maldonado, Ana D.; Uusitalo, Laura; Salmerón, Antonio; Rumí, Rafael; Aguilera, Pedro A.

doi:10.3390/agronomy11040740

Cited by 3 publications

(1 citation statement)

References 58 publications

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“…In terms of interdisciplinarity, we have combined disciplines in creative industries, design, and management for the one-health food security fields [58][59][60]. Lessons learned from previous projects were included in the conception of a new course (CoP in new agro-ecology standards), and were used for the technology and knowledge transfer centre [61,62].…”

Section: Swot Analysismentioning

confidence: 99%

Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia

Bucea-Manea-Ţoniş

Kuleto²,

Gudei

et al. 2022

Sustainability

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In their struggle to offer a sustainable educational system and transversal competencies for market requests, significant transformations characterise the higher education system in Serbia and Romania. According to EU policy, these transformations are related to educational reforms and the introduction of new technology and methodologies in teaching and learning. They are expected to answer to the PISA requirements and to increase the DESI (Digital Economy and Society Index). They are also likely to mitigate the inequity of HEIs (higher education institutions), empowered by a structured, goal-oriented strategy towards agile management in HEIs that is also appropriate for new market demands. Our study is based on an exploratory survey applied to 139 Romanian and Serbian teachers from the Information Technology School—ITS, Belgrade, and Spiru Haret University, Romania. The survey let them provide their knowledge of AI or their perceptions of the difficulties and opportunities of these technologies in HEIs. Our study discovered how difficulties and opportunities associated with AI impact HEIs. This study aims to see how AI might assist higher education in Romania and Serbia. We also considered how they might be integrated with the educational system, and if instructors would utilise them. Developing creative and transversal skills is required to anticipate future breakthroughs and technological possibilitiesThe new methods of education focuses on ethics, values, problem-solving, and daily activities. Students’ learning material, how they might achieve critical abilities, and their educational changes must be addressed in the future. In this environment, colleges must create new digital skills in IA, machine learning, IoT, 5G, the cloud, big data, blockchain, data analysis, using MS Office and other applications, MOOCs, simulation applications, VR/AR, and gamification. They must also develop cross-disciplinary skills and a long-term mindset.

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Section: Swot Analysismentioning

confidence: 99%

Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia

Bucea-Manea-Ţoniş

Kuleto²,

Gudei

et al. 2022

Sustainability

View full text Add to dashboard Cite

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Assessing the risks of northeastern African archaeological heritage and their relationship to human–environmental processes: a Bayesian network approach

Laguna-Palma,

Palacios,

Mokránová

2023

World Archaeology

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Generic Method for Social–Environmental System Boundary Delineation—An Amalgamation of Spatial Data Integration, Optimization, and User Control for Resource Management

Parvez,

Feng

2024

IJGI

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The Social–Environmental System (SES) framework is crucial in understanding the intricate interplay between human societies and their environmental contexts. Despite its significance, existing SES delineation methods often rely on subjective judgment and struggle with the non-linear, multi-scale nature of SES data, leading to challenges in effective resource management and policymaking. This research addresses these gaps by proposing a novel, reproducible framework for SES boundary delineation that integrates both vector and raster data, utilizing advanced spatial optimization techniques and dimension reduction algorithms like UMAP to manage the non-linear characteristics of SES. The framework also leverages the SKATER algorithm for precise regionalization, ensuring spatial continuity and compactness while allowing user control over region selection and data dimensions. Applied to the Rio Grande/Bravo Basin, this approach demonstrates the practical utility and computational efficiency of the proposed method, offering a scalable solution adaptable to various regions. While focusing on this transboundary area, the study underscores how its framework can be generalized globally for addressing socio-environmental challenges while maintaining flexibility to accommodate local and regional specificities. The framework’s reliance on open-source tools further enhances its accessibility and reproducibility, making it a valuable contribution to SES research and practical environmental management.

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A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks

Cited by 3 publications

References 58 publications

Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia

Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia

Assessing the risks of northeastern African archaeological heritage and their relationship to human–environmental processes: a Bayesian network approach

Generic Method for Social–Environmental System Boundary Delineation—An Amalgamation of Spatial Data Integration, Optimization, and User Control for Resource Management

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