Search Results (208)

Web service classification plays an important role in software reuse, service discovery, and automatic metadata organization. Although recent deep learning approaches have improved classification performance by using service names and natural-language descriptions, most existing methods still operate as black-box models and offer limited insight into how different metadata sources influence classification decisions. This lack of transparency reduces their practical usefulness for developers who need to verify predicted categories, analyze incorrect classifications, and improve service metadata quality. A well-trained interpretable model can not only help developers choose more appropriate and reliable categories for each web service, but also help write a more reasonable service name and description. In this paper, we present xServeNet, an explainability-oriented extension of ServeNet for transparent web service classification. xServeNet preserves the BERT-based representation and CNN–BiLSTM feature extractor of ServeNet and introduces (i) an instance-wise dynamic source-fusion mechanism that adaptively combines service-name and service-description features according to their semantic contribution, and (ii) model-internal importance indicators at both the source and word levels that support inspection of classification decisions without introducing additional trainable parameters. We benchmark xServeNet against eleven machine learning baselines on two real-world ProgrammableWeb datasets of 10,943 and 14,086 services covering 50 categories. xServeNet reaches 71.08% Top-1/91.35% Top-5 accuracy on the original dataset and 74.10% Top-1/92.95% Top-5 accuracy on the updated dataset, consistently improving Top-1 accuracy over ServeNet while remaining competitive on Top-5, and achieving the lowest per-category Top-5 standard deviation among all twelve compared methods. In practice, the importance indicators support three concrete activities at the service registry: helping developers verify predicted categories at registration time, iterating on description wording when the predicted category looks wrong, and supporting registry curators in flagging likely mislabelled services for review. Full article

Historic urban districts are increasingly exposed to rapid urban transformation, resulting in the deterioration of heritage fabric, weakening of spatial identity, and disruption of everyday patterns of use. Although participatory approaches are increasingly recognised in heritage-led regeneration, many applications remain limited by the lack of analytical mechanisms capable of connecting community perspectives with spatial and behavioural evidence in a structured and practical manner. This study develops and applies a participatory decision-support approach based on the People–Place–Behaviour (PPB) framework within the historic district of El-Mokhtalat in Mansoura, Egypt. The study combines spatial documentation, behavioural observation, and stakeholder consultation to examine how everyday urban practices, adaptive reuse, informal interventions, and local perceptions collectively influence regeneration priorities within the historic environment. The findings indicate that regeneration priorities emerge through the interaction between spatial conditions, community perceptions, and behavioural patterns rather than through isolated physical conditions alone. Based on stakeholder consultations (n = 30), the analysis identifies a prioritisation gradient in which architectural conservation and environmental enhancement represent the most immediate intervention priorities, while adaptive reuse and public-space improvements remain dependent on contextual compatibility and local acceptance. The study also demonstrates the analytical value of behavioural evidence in revealing recurring spatial pressures, identity-related transformations, and everyday interaction patterns affecting the continuity of the historic urban fabric. By integrating participatory, spatial, and behavioural evidence within a unified evaluation process, the study proposes a context-sensitive analytical approach capable of supporting more informed and locally responsive heritage-led regeneration strategies. Full article

The climate crisis, housing precarity, and the loss of everyday architectural heritage are converging challenges in Mediterranean cities. This article investigates the adaptive reuse of early twentieth-century adobe refugee dwellings in Nea Ionia and Kaisariani, neighborhoods of Attica, Greece, as an integrated social, environmental, and cultural strategy. Historical documentation, urban-morphological analysis, field observations, building survey data, material assessment, and design-based microclimatic analysis were combined to evaluate compatible restoration and bioclimatic upgrades as alternatives to demolition and conventional energy retrofit practices, with the main aim of preserving an important part of Greek history and architecture. The study develops a replicable qualitative assessment framework that identifies how existing adobe envelopes, compact layouts, courtyards, thresholds, vegetated pergolas, and low-water evaporative cooling may support low-carbon housing reuse. The results clarify the current preservation conditions and reuse potential of the selected case-study fragments, showing that adobe dwellings can preserve embodied material value, retain thermal mass and hygroscopic regulation, and support social housing when repaired with compatible, low-impact techniques. The article argues that the reuse of adobe refugee dwellings can function as a distributed urban strategy for housing provision, heritage continuity, and microclimatic adaptation. Its main contribution is a transferable analytical framework for assessing overlooked earthen housing stocks in dense Mediterranean contexts. The study argues that adaptive reuse can serve simultaneously as a means of social housing, a mechanism for optimizing the microclimate, and a means of preserving the tangible and intangible heritage of Greek adobe buildings that have been standing for over 100 years. This position extends circular construction debates by prioritizing non-demolition and direct reuse while preserving an important period of history. Full article

The problem of path following control for underactuated Unmanned Surface Vehicles (USVs) is tackled in this work, and a scheme based on Predicted Adaptive Line-of-Sight (PALOS) is put forward. At the guidance level, prediction techniques and adaptive mechanisms are incorporated to eliminate the inherent assumption of small sideslip angle in the conventional LOS methods, enabling online estimation and dynamic feedforward compensation of time-varying sideslip angles. On the control side, radial basis function neural networks are combined with virtual parameter learning techniques to achieve online approximation of the lumped uncertainties, which include modeling inaccuracies and external disturbances. An adaptive control scheme based on lifelong learning mechanisms is developed, wherein the historical knowledge is constructed and preserved through feedback terms to achieve knowledge retention and on-demand reuse, thereby enhancing control efficiency and mitigating catastrophic forgetting. Additionally, a self-triggered mechanism acts as a knowledge transfer instrument, reducing communication overhead, relaxing transmission conditions, and rigorously precluding Zeno behavior. Through theoretical derivations, one can prove that all closed-loop signals are uniformly ultimately bounded. Comprehensive numerical simulations based on the 1:70 CyberShip II scale-model ship dynamics under complex sea conditions verify the proposed approach to be both effective and practical. Full article

One difficult issue regarding adaptation and adaptive reuse of existing buildings is assessing the heritage significance of functional industrial-oriented heritage buildings, such as railway buildings, that have outlived their original purpose. There is a significant tension in developing strategies for the long-term viability of a sustainable, adaptive reuse of this type of heritage infrastructure. Complicating an assessment is that these buildings may be in constrained locations, or the location has changed beyond all recognition, such that the building inhabits a sterile space. Accepted practice for conserving heritage buildings is to discourage relocating these buildings, with a scholarly concern that presentation of relocated buildings for public engagement will undermine interpretive thinking. In all cases, functional heritage buildings complicate conservation decisions in comparison with mainstream heritage buildings. Existing conservation frameworks remain insufficiently equipped to evaluate industrial and utilitarian heritage buildings whose significance derives as much from operational function, social memory, and technological context as from architectural fabric or fixed location. In response, taxonomy surveying is advanced as a novel stakeholder-centred conservation methodology capable of reconciling tensions between authenticity, adaptive reuse, relocation, and public interpretation. The aim, using case study railway buildings in a museum of industrial heritage, is to test if this methodology is transferable to other functional building types. The findings suggest that taxonomy surveying, as tested on the case study buildings, offers a scalable and internationally transferable framework for evaluating complex industrial heritage assets across differing regulatory, cultural, and spatial contexts. Full article

Adaptive reuse of post-industrial heritage is often studied through technical performance, formal intervention strategies, or decision-support models. While these approaches clarify important aspects of reuse, they give limited attention to how projects evolve through the combined effects of architectural decisions, governance arrangements, financing mechanisms, policy instruments, social programs, and inherited fabric. This paper examines adaptive reuse as a time-structured project trajectory. It applies a hybrid methodology combining within-case reconstruction and comparative cross-case analysis to seven European projects in Brussels, Essen, Rotterdam, San Sebastián, Florence, Vienna, and Barcelona. The cases are analyzed across six dimensions: Asset & Context, Governance & Finance, Circularity, Social & Cultural, Policy & Design, and Outcomes & Transfer. The comparison shows that adaptive capacity depends on the alignment of governance, project time, and intervention strategy. Governance determines who can revise decisions and under what conditions; adaptation time is produced through funding horizons, approval procedures, institutional continuity, and civic or public stewardship; and strategies of retention, replacement, reversible insertion, and incremental occupation distribute future risk differently across project phases. From this synthesis, the paper extracts ten conditional lessons that frame adaptive reuse as configuration knowledge: transferable insights whose relevance depends on the interaction among governance capacity, temporal sequencing, inherited fabric, financing, policy support, and social objectives. The paper argues that knowledge transfer in adaptive reuse should be understood as disciplined translation across comparable constraints, not as the replication of models, rankings, or best-practice templates. Full article

This study implemented an integrated mineralogical and microscopic workflow to identify naturally occurring asbestos (NOA) in former mining areas of H County in the central-western Korean Peninsula and to derive practical implications for long-term site management. Five former mining localities were selected based on regional NOA distribution maps and historical mining records. Representative rock samples were analyzed using polarized light microscopy, X-ray diffraction, scanning electron microscopy–energy-dispersive spectroscopy, and transmission electron microscopy. The findings revealed that chrysotile was the dominant type of asbestos, with localized occurrences of actinolite and anthophyllite also identified. The results indicate that mixed asbestos assemblages can form in structurally controlled and altered lithologic domains, highlighting the need for complementary analytical methods for reliable identification instead of relying on a single technique. Importantly, the study suggests that the response to NOA-bearing environments should focus on long-term management rather than just documenting their presence. Effective management strategies should include revegetation, engineered covering or backfilling, control of dust-generating activities, restrictions on material reuse, provision of information on health risk prevention and exposure reduction, and long-term monitoring for adaptive site control. Full article

Second-life lithium-ion batteries offer strong potential for sustainable stationary energy storage, but their practical reuse is limited by cell-to-cell heterogeneity, non-uniform heat-generation, and the resulting thermal safety risks. Conventional battery thermal management systems (BTMSs), which rely on fixed and uniformly distributed coolant flow, are not well-suited to the asymmetric thermal behaviour of aged battery packs. In this study, an adaptive liquid-cooling framework with locally regulated branch-level flow allocation is proposed for second-life prismatic LiFePO₄ battery modules. A three-dimensional transient conjugate heat transfer model was developed in COMSOL Multiphysics. The analysis was conducted on a 3 × 3 battery module under nine thermal heterogeneity scenarios, followed by a larger 5 × 4 module to evaluate scalability. The results show that thermal severity depends not only on heat-generation magnitude but also on the spatial arrangement of degraded cells. Under the most critical 3 × 3 configuration, the adaptive BTMS reduced the maximum temperature from 37.16 °C to 28.77 °C, corresponding to a reduction of about 8.38 °C, while limiting the cell-to-cell temperature difference to approximately 1.16 °C. A comparison with a conventional constant-flow cooling configuration in the larger 5 × 4 module further showed that adaptive branch-level coolant redistribution improves thermal uniformity under heterogeneous thermal loading by selectively directing cooling capacity toward thermally stressed regions. The results demonstrate the potential of demand-driven flow allocation as a distributed thermal-management strategy for heterogeneous second-life battery systems. Full article

In many rural heritage settings, continuity depends less on static preservation than on the ongoing negotiation of space, governance, and cultural practice. This dynamic is particularly evident in transnational Hakka villages, where lineage networks, migration histories, and everyday adaptation continuously reshape heritage in practice. Existing research, however, often treats material conservation, governance arrangements, and cultural meaning as separate analytical domains, limiting its ability to explain the complexity of lived heritage processes and reducing its relevance for practical heritage management. Drawing on ethnographic fieldwork conducted in Zhongchuan Village, Fujian Province, China, this study employs semi-structured interviews, participant observation, and qualitative thematic analysis to examine how heritage continuity is sustained and transformed through everyday social practice. The findings identify three interrelated dimensions of heritage-making: material–technical adaptation, social–institutional governance, and symbolic–cultural meaning. Based on these interactions, the study develops the Three-Dimensional Cultural Interweaving Model (3D-CCM) as an integrated analytical framework for understanding dynamic heritage processes. By connecting these dimensions, 3D-CCM highlights how rural heritage continuity emerges through the interaction of architectural adaptation, governance negotiation, and cultural interpretation. The study further shows that heritage-making in Zhongchuan Village is shaped not only by local practices and institutional arrangements, but also by ongoing connections within transnational Hakka networks. These findings contribute to current discussions on sustainable rural heritage by emphasizing the importance of community participation, adaptive reuse, and cross-regional cultural relationships. Full article

Agricultural AI agents play a crucial role in the evolution of smart agriculture, from single-point automated applications to intelligent systems driven by tasks, collaborative decision-making, and closed-loop execution. However, their practical implementation still faces key challenges, such as heterogeneous agricultural data processing, insufficient cross-scenario generalization ability, complexity of multi-agent collaboration, difficulties in integrating software and hardware, and insufficient security and trust guarantees in real agricultural environments. This paper presents a systematic review of the architecture design, business processes, key technologies, and future challenges of agricultural AI agents. Agricultural AI agents are classified into two types: virtual agricultural AI agents and embodied agricultural AI agents. The paper summarizes a four-layer system architecture consisting of the infrastructure layer, agent management layer, agent collaboration layer, and application layer. The paper also analyzes the model capabilities required by agricultural AI agents from four typical business dimensions: perception and state understanding, knowledge memory and experience management, reasoning decision-making and task planning, and collaborative execution and resource scheduling. This research shows that technologies such as multimodal perception, knowledge graphs, retrieval-enhanced generation, digital twins, reinforcement learning, and multi-agent collaboration can provide important support for agricultural AI agents to enhance their environmental understanding, knowledge reuse, autonomous decision-making, and physical execution capabilities. Future research should focus on robust perception in open environments, long-term memory and knowledge evolution, reliable multi-agent collaboration, edge-cloud collaborative deployment, and secure and trustworthy human–machine collaboration. Integrating agricultural domain knowledge with intelligent agent technology is an important direction for promoting the large-scale, adaptive, and sustainable application of agricultural AI agents. Full article

Industrial heritage adaptive reuse occupies a structurally privileged position for degrowth: heritage listing already institutionalises material sufficiency as a regulatory obligation, mandating low intervention and resisting the demolish-and-replace logic of resource-intensive development. Yet this regulatory floor imposes no ceiling on how protected structures are programmed or who benefits; the same statutory instrument can produce different schemes depending entirely on governance. This paper demonstrates that gap through two contrasting UK gasholder adaptive reuse projects: King’s Cross Gasholders in London (private-led, luxury residential) and Granton Gasholder in Edinburgh (council-led community park). Applying De Castro Mazarro et al.’s multi-scalar degrowth framework across building, neighbourhood, and city scales through document analysis and site observations, we identify structural mechanisms explaining why building-scale alignment fails to propagate upward. The findings indicate three governance conditions are necessary to convert the structural degrowth potential of industrial heritage into substantive outcomes: public control over development decisions, community participation extended to strategic priorities rather than design preferences, and explicit integration of degrowth values into upstream planning frameworks. Industrial heritage adaptive reuse is not inherently a degrowth practice, but it is one of the few urban development contexts where the regulatory preconditions for degrowth alignment are already in place. Realising that potential requires governance structures that treat sufficiency and collective wellbeing as binding objectives, not rhetorical claims. Full article

The V-Model is widely used in safety-critical engineering; however, its application to rapid prototyping remains challenging due to limited integration between lifecycle governance and executable validation workflows. This paper addresses end-to-end mechatronic ECU development through the general objective of designing an integrated, prototyping-oriented software platform that operationalizes a V-Model-based rapid prototyping lifecycle with explicit, process-level traceability. Four specific objectives structure the contribution. First, bibliometric analyses of the keywords “V-Model” and “Rapid Prototyping Platforms,” conducted using the Web of Science database and VOSviewer, highlight the limited integration of structured lifecycle approaches with practical prototyping workflows. Second, the V-Model is adapted for mechatronic ECU development by introducing domain-specific decomposition and a dependency-driven testing sequence. Third, the BIOComProP (Basic Input Output Communication Protocol Platform)—comprising reusable ECU firmware, PC based test software, and a dedicated request–response communication protocol—is developed, and its testing capabilities are mapped to V-Model phases. Finally, a logic-based workflow is defined to translate patent derived requirements into executable development and validation steps. The results demonstrate staged verification aligned with technical dependencies, structured traceability across development activities, and firmware reuse across multiple prototypes, offering a coherent and reproducible approach for rapid prototyping of mechatronic ECU systems without relying on heavyweight MBSE or ALM toolchains. Full article

Modular construction (MC) is frequently promoted as a path to circular economy (CE) outcomes in built environments, yet circular adoption and performance remain uneven. This study investigates how systemic barriers shape the implementation of circular strategies in MC. A systematic literature review combined with bibliometric mapping and systems-oriented synthesis was conducted using 124 Web of Science records published between 2011 and August 2025. Bibliographic coupling, co-citation, and keyword co-occurrence analyses were used to characterise the field’s intellectual structure, while 30 studies were selected for thematic coding and systems mapping. Ten recurrent barriers were identified and consolidated into six clusters: technical, financial, regulatory, stakeholder and organisational, quality assurance, and institutional and knowledge-based challenges. Their relative severity was assessed across four MC-relevant circular strategies: reuse, repurposing, design for disassembly, and multifunctionality. Systems mapping revealed three reinforcing feedback dynamics involving financial, stakeholder, and supply-chain pressures, knowledge and quality assurance constraints, and regulatory and design lock-in effects that stabilise conventional delivery and constrain circular implementation. Despite being underrepresented in the literature, multifunctionality emerges as a cross-cutting leverage point for enabling adaptable modular systems. The study synthesises five implementation pathways, including adaptable multifunctional design, interoperable interfaces, digital traceability, collaborative life-cycle integration, and policy alignment, and outlines systems-derived leverage points to guide future research and practice in circular modular construction. Full article

The present study aims to explore the relationship between theory and practice by evaluating the feasibility of quantification and evaluation for assessing the spatial performance and circulation logic in historic domestic architecture to inform adaptive reuse strategies. The study examines several courtyard houses in a representative residential area within Erbil Citadel in the Kurdistan Region of Iraq, an area of immense cultural, architectural, and historical value. The selection of the sample is based on the chronological, typological, and spatial diversity of residential architecture in Erbil Citadel. The study uses an integrated methodological approach to investigate the spatial configuration of each sample building. To ensure increased analytical rigor and to compare its findings with similar studies in different contexts, the results are further validated using Euclidean distance and Pearson correlation to assess the compatibility of existing characteristics with proposed adaptive reuse strategies across different contexts. The results show that quantitative spatial analysis can be an effective tool in identifying the potential of existing residential architecture in terms of its spatial configuration while preserving its cultural value. The study concludes that its proposed approach can serve as an effective model for adaptive reuse planning in similar contexts. Full article

Revisit intention is increasingly recognized as a key indicator of sustainable heritage tourism, as it reflects long-term visitor engagement rather than one-time consumption. However, limited attention has been paid to how tourism preferences shape perceived heritage quality and subsequently influence revisit intention, particularly in industrial heritage contexts undergoing urban regeneration. This study develops a structural model linking tourism preferences, perceived quality, and revisit intention, using Shanghai’s waterfront industrial heritage as an empirical case. Based on 335 valid questionnaires, structural equation modeling (SEM) is employed to examine the relationships among environmental preference, cultural and social sustainability preferences, situational perception, and behavioral intention. The results indicate that preference for a sustainable public space environment significantly enhances both physical and atmospheric perception, which in turn positively affects revisit intention. In contrast, social sustainability shows limited influence, suggesting that visitors’ behavioral responses are more strongly driven by environmental quality and experiential engagement in regenerated industrial heritage settings. This study contributes to sustainable heritage tourism research by integrating preference-based perception mechanisms into revisit intention analysis. It also provides practical implications for enhancing long-term attractiveness through experience-oriented adaptive reuse strategies. Full article