Search Results (196)

Against the backdrop of global energy crises and accelerated urbanization, urban wind energy has garnered increasing attention through its integration with building environments. This study investigates the synergistic optimization of architectural parameters (including floor layouts, three-dimensional forms, and roof configurations) with wind capture efficiency. By employing parameterized design and multi-scale flow field analysis, we systematically examine how architectural morphology modulates wind fields and enhances energy performance. Our key findings reveal the following: spatially arranged floor plans significantly influence wind speed distribution; three-dimensional form openings effectively enhance wind velocity while reducing wind-induced vibration responses; and roof configurations and floor layouts demonstrate the highest contribution to wind energy efficiency, with curved roofs showing particularly notable power generation improvements in low-wind environments. The building “density + layout angle + roof form” collaborative strategy has been validated for practical implementation. Current limitations include simulation errors in complex geometries, efficiency bottlenecks in vertical axis turbines, and inadequate lifecycle assessments. Future efforts should focus on multi-field coupled simulations, integrated turbine–architecture design, and enhanced low-carbon evaluation systems to facilitate the transformation of buildings into distributed energy production entities. Full article

The transboundary partnership encourages multi-stakeholder efforts to mobilize adaptation funding and services for adaptation governance. However, challenges exist in scope, equality, and transparency when engaging these stakeholders. Few studies have examined the detailed coordination among multi-stakeholders and the performance of their partnerships, creating an opportunity to understand how multi-stakeholders contribute to and manage efforts for future adaptation projects. This study focused on a transboundary action research project on climate adaptation, analyzing the partnership structure, stakeholder arrangements, coordination scenarios, and the role of the partnership within it. It included interviews with project personnel and focus group discussions with community members at the project sites. The results showed that the project emphasized collaboration while maintaining both vertical and horizontal coordination. The donor maintained vertical coordination for monitoring but collaborated on budget adjustments, funding, identifying challenges, and developing strategies to improve the partnership. Partners continued horizontal coordination by sharing responsibilities and taking leadership roles in synthesizing research reports. Additionally, this project facilitated community participation in piloting the adaptation intervention. Although this partnership aimed to establish collaboration, it remains far from effectively liaising with national-level governments to maximize the benefits of adaptation technology. Future research should expand this scope to promote sustainable development. Full article

The proliferation of diverse multi-stakeholder partnering arrangements that seek to achieve the 2030 Agenda for Sustainable Development has prompted calls for overarching standards to enhance their governance, legitimacy and effectiveness. This conceptual article critically examines the limitations of applying universal partnership standards across complex and context-sensitive collaborative arrangements. Drawing on a purposive sampling of approximately 115 academic, policy-oriented and practitioner sources, identified through targeted database searches, we explore the historical development of sustainability-related partnership norms and identify some of the tensions in their alignment with socio-historic, institutional and relational dynamics. We examine the concept of partnership meta-governance as a way of both ensuring and enabling effective collaborative initiatives working to meet the targets of the 2030 Agenda’s 17 Sustainable Development Goals. Using a methodology that combines conceptual analysis with practitioner-tested support mechanisms, we propose a principles-based approach to enrich the enabling dimension of partnership meta-governance by privileging contextual responsiveness, co-creation and relational values over prescriptive compliance. This approach seeks to reinforce the transformational intent of the 2030 Agenda by offering a foundation for more inclusive and adaptive collaboration that supports the long-term aspirations of the United Nations’ Pact for the Future. Full article

The main objective of this study is to offer fresh empirical insight into the evolving relationship between digitalisation and agroecology by examining Mulini Di Segalari, a biodynamic vineyard in Italy. While much of the existing literature positions digital agriculture as potentially misaligned with agroecological principles, this case study unveils how digital tools can actively reinforce agroecological practices when embedded within supportive socio-technical networks. Novel findings of this study highlight how the use of digital technologies supported agroecological practices and led to the reconfiguration of social relations, knowledge systems, and governance structures within the farm. Employing a technographic approach revealed that the farm’s transformation was driven not just by technology but through collaborative arrangements involving different stakeholders. These interactions created new routines, roles, and information flows, supporting a more distributed and participatory model of innovation. By demonstrating how digital tools can catalyse agroecological transitions in a context-sensitive and socially embedded manner, this study challenges the binary framings of technology versus ecology and calls for a more nuanced understanding of digitalisation as a socio-technical process. Full article

Background/Objectives: Despite its significant impact on learning, classroom acoustics and students’ hearing difficulties are often overlooked compared with more visible issues like lighting. Hearing loss—frequently underestimated and invisible—affects both students and teachers, potentially leading to fatigue, reduced participation, and academic challenges. The A.BA.CO. project in Italy was developed to address these issues by promoting improved classroom design, technological solutions, and better auditory communication accessibility in schools. Objective: This article presents the A.BA.CO. project, offering context and an overview of the preliminary analyses conducted by its multidisciplinary team. The goal is to share insights and propose organizational frameworks, technical solutions, and best practices concerning the hearing, communication, and auditory learning challenges experienced by students with hearing impairments. Results: The A.BA.CO. team’s analyses identified key barriers to inclusion for students with (or without) hearing impairments, such as poor classroom acoustics, excessive noise, and suboptimal seating arrangements. The project underscores the importance of improved acoustic environments and the integration of assistive technologies, including speech-to-text systems. The findings highlight the need for interdisciplinary collaboration to design accessible and inclusive educational settings for all learners. Conclusions: Embedding educational audiology within school systems—alongside enhancements in classroom acoustics and the use of assistive technologies and other technological solutions—is essential to ensure that all students, regardless of hearing ability, have equitable access to learning and full participation in educational life. Full article

Collaborative digital games and interfaces are increasingly used in both research and commercial contexts, yet little is known about how the spatial arrangement and interface sharing affect the user experience in dyadic settings. Using a two-player iPad pong game, this study compared user experiences across three collaborative gaming scenarios: face-to-face single-screen (F2F-OneS), face-to-face dual-screen (F2F-DualS), and remote dual-screen (Rmt-DualS) scenarios. Eleven dyads participated in all conditions using a within-subject design. After each session, the participants completed a 21-item user experience questionnaire and took part in brief interviews. The results from a repeated-measure ANOVA and post hoc paired t-tests showed significant scenario effects for several experience items, with F2F-OneS yielding higher engagement, novelty, and accomplishment than remote play, and qualitative interviews supported the quantitative findings, revealing themes of social presence and interaction. These results highlight the importance of spatial and interface design in collaborative settings, suggesting that both technical and social factors should be considered in multi-user interface development. Full article

The UI GreenMetric World University Ranking has become a widely adopted instrument for benchmarking institutional sustainability performance; nevertheless, empirically grounded evidence from universities in diverse regional contexts remains scarce. This study undertakes a rigorous appraisal of the extent to which Mahasarakham University (MSU) has institutionalized the United Nations Sustainable Development Goals (SDGs) within its pedagogical offerings, research portfolio, community outreach, and governance arrangements during the 2021–2024 strategic cycle. Employing a mixed-methods design and guided by the 2024 UI GreenMetric Education and Research indicators, this investigation analyzed institutional datasets pertaining to curriculum provision, ring-fenced research funding, 574 peer-reviewed sustainability publications, student-led community initiatives, and supporting governance mechanisms; the analysis was interpreted through a Plan–Do–Check–Act management lens. The number of sustainability-oriented academic programs expanded from 49 to 58. Student participation in community service activities strongly recovered following the COVID-19 pandemic, and MSU’s GreenMetric score increased from 7575 to 8475, thereby elevating the institution to the 100th position globally. These gains were facilitated by strategic SDG-aligned investment, cross-sector collaboration, and the consolidation of international partnerships anchored in Thailand’s Isaan region. The MSU case provides a transferable model for universities—particularly those operating in resource-constrained contexts—endeavoring to align institutional development with the SDGs and internationally recognized quality benchmarks. The findings substantiate the capacity of transformative education and applied research to engender enduring societal and environmental benefits. Full article

To address the challenges in ship plate detection under complex maritime scenarios—such as small target size, extreme aspect ratios, dense arrangements, and multi-angle rotations—this paper proposes a multi-module collaborative detection algorithm, RT-DETR-HPA, based on an enhanced RT-DETR framework. The proposed model integrates three core components: an improved High-Frequency Enhanced Residual Block (HFERB) embedded in the backbone to strengthen multi-scale high-frequency feature fusion, with deformable convolution added to handle occlusion and deformation; a Pinwheel-shaped Convolution (PConv) module employing multi-directional convolution kernels to achieve rotation-adaptive local detail extraction and accurately capture plate edges and character features; and an Adaptive Sparse Self-Attention (ASSA) mechanism incorporated into the encoder to automatically focus on key regions while suppressing complex background interference, thereby enhancing feature discriminability. Comparative experiments conducted on a self-constructed dataset of 20,000 ship plate images show that, compared to the original RT-DETR, RT-DETR-HPA achieves a 3.36% improvement in mAP@50 (up to 97.12%), a 3.23% increase in recall (reaching 94.88%), and maintains real-time detection speed at 40.1 FPS. Compared with mainstream object detection models such as the YOLO series and Faster R-CNN, RT-DETR-HPA demonstrates significant advantages in high-precision localization, adaptability to complex scenarios, and real-time performance. It effectively reduces missed and false detections caused by low resolution, poor lighting, and dense occlusion, providing a robust and high-accuracy solution for intelligent ship supervision. Future work will focus on lightweight model design and dynamic resolution adaptation to enhance its applicability on mobile maritime surveillance platforms. Full article

Complex problems are rarely solved on their own. One such problem facing Aotearoa New Zealand is the provision of affordable housing that enhances the wellbeing of tenants and local communities. Using qualitative methodology, this study examines the various ways in which public and community housing providers work together with external organisations to improve wellbeing. This research is the first of its kind in New Zealand to examine the different ways that housing providers collaborate with external organisations. It is also the first of its kind to explore the extent to which the Treaty of Waitangi (the founding document of New Zealand between Māori and the Crown) influences collaboration. To assist our understanding of collaboration typology, a focused literature review was undertaken, where a collaboration continuum was developed. The literature findings were utilised to strengthen our interrogation of the data by observing activities, rather than relying on commonly used terms. All housing providers were identified as investing heavily in collaboration. Those engaged in large complex projects exhibited higher levels of inter-organisational intensity. The Treaty of Waitangi was identified as influencing collaboration between housing providers and Māori, including non-Crown agencies. As the affordable housing sector undergoes changes, further research is recommended. Full article

Acoustic metasurfaces play a key role in building acoustics, noise control, and acoustic cloaking by regulating the acoustic wave scattering characteristics through subwavelength structures. The design of diffusely reflecting metasurfaces aims to achieve a uniform distribution of a scattered field, which is essentially a high-dimensional nonconvex optimization problem that needs to balance the computational efficiency in the synergistic optimization of the spatial arrangement of cells and the angular response. In traditional methods, a heuristic algorithm is prone to local optimization, and it is difficult to balance the global search and local adjustment. And full-wave simulation is time consuming and seriously restricts the design efficiency. Therefore, the hybrid tornado-gradient descent optimization algorithm (VDGD) is proposed in this paper. It uses a two-stage collaborative optimization approach to refine the reflection angle distribution of acoustic metasurfaces, thereby enhancing the uniformity of the diffuse acoustic field. The Tornado Optimization Algorithm (TOA) was initially employed to introduce global perturbations to the randomly initialized design. Local optimization can be avoided by gradually decreasing the perturbation magnitude, which reduces the standard deviation of the sound field from about 5.81 dB to about 4.07 dB. Then, the gradient descent is used for local fine adjustment to further reduce the standard deviation to about 1.91 dB. Experimental results show that the VDGD algorithm outperforms the seven classical and up-to-date optimization algorithms in improving scattering uniformity. This method achieves an effective balance between global search and local fine tuning, providing an efficient and flexible optimization strategy for metasurface design, which can bring application support for intelligent acoustic devices and sound field regulation. Full article

An intrusion detection system (IDS) is a crucial element in cyber security concerns. IDS is a safeguarding module that is designed to identify unauthorized activities in network environments. The importance of constructing IDSs has never been this significant with the growing number of attacks on network layers. This research work was intended to draw the attention of the authors to a different aspect of intrusion detection, considering privacy and the contribution of the features on attack classes. At present, the majority of the existing IDSs are designed based on centralized infrastructure, which raises serious concerns about security as the network data from one system are exposed to another system. This act of sharing the original network data with another server can worsen the current arrangement of protecting privacy within the network. In addition, the existing IDS models are merely a tool for identifying the attack categories without analyzing a further emphasis of the network feature on the attacks. In this article, we propose a novel framework, FEDXAIIDS, converging federated learning and explainable AI. The proposed approach enables IDS models to be collaboratively trained across multiple decentralized devices while ensuring that local data remain securely on edge nodes, thus mitigating privacy risks. The primary objectives of the proposed study are to reveal the privacy concerns of centralized systems and identify the most significant features to comprehend the contribution of the features to the final output. Our proposed model was designed, fusing federated learning (FL) with Shapley additive explanations (SHAPs), using an artificial neural network (ANN) as a local model. The framework has a server device and four client devices that have their own data set on their end. The server distributes the primary model constructed using an ANN among the local clients. Next, the local clients train their individual part of the data set, deploying the distributed model from the server, and they share their feedback with the central end. The central end then incorporates an aggregator model named FedAvg to assemble the separate results from the clients into one output. At last, the contribution of the ten most significant features is evaluated by incorporating SHAP. The entire research work was executed on CICIoT2023. The data set was partitioned into four parts and distributed among the four local ends. The proposed method demonstrated efficacy in intrusion detection, achieving 88.4% training and 88.2% testing accuracy. Furthermore, UDP has been found to be the most significant feature of the network layer from the SHAP analysis. Simultaneously, the incorporation of federated learning has ensured the safeguarding of the confidentiality of the network information of the individual ends. This enhances transparency and ensures that the model is both reliable and interpretable. Federated XAI IDS effectively addresses privacy concerns and feature interpretability issues in modern IDS frameworks, contributing to the advancement of secure, interpretable, and decentralized intrusion detection systems. Our findings accelerate the development of cyber security solutions that leverage federated learning and explainable AI (XAI), paving the way for future research and practical implementations in real-world network security environments. Full article

Camellia oleifera harvester is a compact agricultural vehicle utilized in plantations located in China’s red soil hilly regions. To enhance its functionality and off-road performance, additional electronic devices and a more powerful powertrain system have been integrated within the engine compartment. However, the increased component density has resulted in constrained heat dissipation space, leading to critical issues including insufficient engine power, delayed control response, and reduced vibration frequency of the harvesting device. These thermal problems significantly compromise operational efficiency and pose safety hazards to operators. To address these heat dissipation challenges, this study proposes a collaborative optimization approach integrating computational fluid dynamics (CFD) simulation with an Adaptive Particle Swarm Optimization (APSO) algorithm. Initially, preliminary experiments, coupled with CFD simulations, were conducted to analyze the airflow distribution and temperature field within the engine compartment. Based on these findings, the component arrangement was reconfigured to improve thermal performance. Subsequently, an “engine compartment cover parameters–temperature” correlation model was established, and the dimensional parameters of the engine compartment cover were optimized using the APSO algorithm. Experimental results demonstrate that the optimized configuration achieves an average surface temperature reduction of approximately 17.82% for critical components, enabling prolonged stable operation and significantly enhanced operational reliability of the harvester. Full article

Establishing good contact arrangements between children in public care and their parents is of great significance for those involved. To ensure the child’s protection and safety, supervised contact may be necessary. This can be a complex situation that necessitates high-quality social work and thorough reflection. Empirical data were derived from a vignette study and eight focus groups conducted by the Norwegian Child Welfare Services. Our research considers the following questions: How does supervised contact become a theme when assessing contact arrangements for children and parents after the child has been taken into care, and how is the concept of supervised contact understood by social workers? The findings show that supervised contact may be recommended for various reasons, such as control, support, and safety, to observe and gather more information. This study reveals a need for social workers to develop greater awareness in their assessments and decisions regarding the implementation of supervised contact. It is important to explore the various ways supervised contact is conceived and practiced. We also need to critically discuss the opportunities and challenges it represents, as well as the need to provide support and guidance to the child and parents and facilitate positive collaboration with child welfare services. Full article

Facility layout design (FLD) is critical for optimizing manufacturing efficiency, yet traditional approaches struggle with complexity, dynamic constraints, and fragmented data integration. This study proposes a generative-AI-enabled facility layout design, a novel paradigm aligning with Industry 4.0, to address these challenges by integrating generative artificial intelligence (AI), semantic models, and data-driven optimization. The proposed method evolves from three historical paradigms: experience-based methods, operations research, and simulation-based engineering. The metamodels supporting the generative-AI-enabled facility layout design is the Asset Administration Shell (AAS), which digitizes physical assets and their relationships, enabling interoperability across systems. Domain-specific knowledge graphs, constructed by parsing AAS metadata and enriched by large language models (LLMs), capture multifaceted relationships (e.g., spatial adjacency, process dependencies, safety constraints) to guide layout generation. The convolutional knowledge graph embedding (ConvE) method is employed for link prediction, converting entities and relationships into low-dimensional vectors to infer optimal spatial arrangements while addressing data sparsity through negative sampling. The proposed reference architecture for generative-AI-enabled facility layout design supports end-to-end layout design, featuring a 3D visualization engine, AI-driven optimization, and real-time digital twins. Prototype testing demonstrates the system’s end-to-end generation ability from requirement-driven contextual prompts and extensively reduced complexity of modeling, integration, and optimization. Key innovations include the fusion of AAS with LLM-derived contextual knowledge, dynamic adaptation via big data streams, and a hybrid optimization approach balancing competing objectives. The 3D layout generation results demonstrate a scalable, adaptive solution for storage workshops, bridging gaps between isolated data models and human–AI collaboration. This research establishes a foundational framework for AI-driven facility planning, offering actionable insights for AI-enabled facility layout design adoption and highlighting future directions in the generative design of complex engineering. Full article

In this study, the temperature change and its control measures caused by hydration heat in the construction process of bridge mass concrete cap in severe cold area are discussed. The finite element analysis method was used to simulate the temperature field of the mass pile cap concrete of the No. 13 pier of the swivel bridge in Dehui City under different construction conditions. The effects of different pouring methods, cooling water pipe layout, and its parameters on temperature control were investigated. The research shows that layered pouring combined with multi-layer cooling water pipe arrangement can effectively reduce the core temperature of concrete, thereby reducing the temperature gradient and stress concentration. Among them, the four-layer metal cooling water pipe scheme can significantly reduce the temperature peak, improve the temperature field distribution, and reduce the risk of cracks. In this study, a ‘layered pouring and four-layer metal cooling water pipe collaborative temperature control system’ was proposed for the first time. Combined with the environmental characteristics of severe cold regions, the core temperature of concrete was reduced from 63.55 °C without control to 40.70 °C, and the temperature decreased by 22.85 °C (about 36%). At the same time, the temperature gradient and temperature stress are significantly reduced, which inhibits the stress concentration caused by the temperature gradient and effectively controls the risk of crack formation. In addition, this study explores the influence of cooling water pipe diameter, material and water flow rate on the internal temperature of concrete, and proposes an optimized construction strategy that provides a scientific basis and engineering reference for the construction of mass concrete caps under cold climate conditions. Full article