Search Results (8,447)

The construction industry is a major contributor to environmental degradation, primarily due to the substantial volumes of construction waste (CW) generated on-site. As sustainability becomes a global imperative aligned with the UN 2030 Agenda, identifying and mitigating the root causes of CW is essential. This study adopts a cross-disciplinary approach to explore the drivers of CW and support more effective, sustainable waste reduction strategies. A systematic literature review was conducted to extract 25 key CW source factors from academic publications. These were analyzed using Social Network Analysis (SNA) to reveal their structural relationships and relative influence. The results indicate that the lack of structured on-site waste management planning, accumulation of residual materials, and insufficient worker training are among the most influential CW drivers. Comparative analysis with industry data highlights theoretical–practical gaps and the need for improved alignment between research insights and site implementation. This paper recommends the adoption of tiered waste management protocols as part of contractual documentation, integrating Building Information Modeling (BIM)-based residual material traceability systems, and increasing attention to workforce training programs focused on material handling efficiency. Future research should extend SNA frameworks to sector-specific waste patterns (e.g., pavement or demolition projects) and explore the intersection between digital technologies and circular economy practices. The study contributes to enhancing waste governance, promoting resource efficiency, and advancing circularity in the built environment by offering data-driven prioritization of CW sources and actionable mitigation strategies. Full article

In the area of structured cabling systems, optimization, i.e., reducing design errors, mini-mizing the need for rework, and increasing overall design productivity, is a critical factor in both design and maintenance. Traditional CAD methods exhibit 12% cable length miscalculations, which our script methodology mitigates. This paper presents a novel approach to the use of scripts in low voltage cabling systems, with a particular focus on the automatic routing of cables based on modeled cable paths. The proposed approach enables the automated construction and calculation of individual cable routes, as well as the comprehensive storage of associated parameter data. The methodology is discussed at conceptual level, with ideas presented at code and user levels. The effectiveness of this methodology is demonstrated through a case study conducted in the context of a real-world project. Full article

China has entered an era of population decline, yet urbanization continues as rural-to-urban migration persists. This demographic transition has prompted a strategic shift in urban development from extensive spatial expansion toward quality-oriented, intensive growth models. However, evolving human–land supply–demand dynamics in cities historically characterized by population inflows remain insufficiently understood. This study focuses on Xiamen, a prototypical coastal migrant-receiving city, to investigate land use simulation under demographic transition. By integrating the cohort-component method with the Patch-generating Land Use Simulation (PLUS) model, we project Xiamen’s population under three scenarios by 2030: Stable Continuation (SCS), Natural Development (NDS), and National 2030 Population Planning (NPP), with projected increases of 5.56%, 6.76%, and 24.69%, respectively. Results show continued but decelerating population growth, with adequate labor supply and persistent demographic dividend. Notably, the NPP scenario reveals a negative correlation between population growth and construction land expansion. In NPP-High, prioritizing compact development and ecological conservation, population grows by 1.27 million while construction land decreases by 2.85% and forest land increases by 4.09%. This framework provides empirical evidence for compact urban development under the dual constraints of land-use efficiency and ecological protection. Full article

With the continuous expansion of power grids and the advancement of ultra-high voltage (UHV) projects, transmission lines are increasingly traversing areas characterized by micro-terrain. These localized topographic features can intensify meteorological effects, thereby increasing the risks of hazards such as conductor icing and galloping, directly threatening operational stability. Enhancing the disaster resilience of transmission lines in such environments requires accurate and efficient terrain identification. However, conventional recognition methods often neglect the spatial alignment of the transmission lines, limiting their effectiveness. This paper proposes a deep learning-based recognition framework that incorporates a dual-branch network architecture and a cross-branch spatial attention mechanism to address this limitation. The model explicitly captures the spatial correlation between transmission lines and surrounding terrain by utilizing line alignment information to guide attention along the line corridor. A semi-synthetic dataset, comprising 6495 simulated samples and 130 real-world samples, was constructed to facilitate model training and evaluation. Experimental results show that the proposed model achieves classification accuracies of 94.6% on the validation set and 92.8% on real-world test cases, significantly outperforming conventional baseline methods. These findings demonstrate that explicitly modeling the spatial relationship between transmission lines and terrain features substantially improves recognition accuracy, offering important support for hazard prevention and resilience enhancement in UHV transmission systems. Full article

Conventional project scheduling techniques often rely on manual trial-and-error methods, which can lead to inaccurate evaluations. This study presents a dynamic scheduling framework to dynamically adjust scheduling decisions based on real-time productivity and budget constraints, resulting in improvement in scheduling accuracy in project management. By integrating advanced computational tools, the proposed approach addresses complex scheduling challenges. The model integrates Building Information Modeling (BIM)-based 3D data, productivity and process simulation, and optimization techniques to provide a unified scheduling tool that supports informed decision-making while considering real-time constraints, including productivity performance and budget limitations. The results demonstrated notable improvements over conventional methods, including a 13% increase in scheduling accuracy relative to the actual total project cost and a 34.4% improvement in scheduling accuracy based on the actual project duration, compared to the contractor’s baseline. The framework dynamically adjusts schedules and budgets according to current project conditions. These findings demonstrate its reliability as a decision-making tool for construction project management. The study introduces an integrative scheduling framework that adapts to real-time project conditions and is validated against actual project data. The integration of BIM, system dynamics, process simulation, and ACOR optimization provides a novel approach to construction scheduling. This methodology improves project management efficiency by automating scheduling adjustments based on ongoing progress. Full article

After decades of decline, Detroit has begun advocating for immigrant inclusion as a regional revitalization strategy. Yet, some migrants do not share the city’s enthusiasm. Chaldean Iraqis, for instance, tend to underscore their distinctiveness from the city and its residents. Nevertheless, their insistence on difference seems spatially specific. Drawing on ethnographic observations in and around Chaldean community organizations in metro Detroit, as well as a sociological discourse analysis of urban policy documents, this paper traces newcomers and the city’s mutually constitutive nature of identity formation. Moreover, I show how community members strategically link their collective memories from Iraq to those of Southeast Michigan, resulting in highly complex place-identity projects. The carefully curated public narrative, in turn, has real consequences for Detroit’s social fabric, reproducing, and challenging Detroit’s own regional identity. Theoretically, the findings point to the limitations of a one-dimensional, spatially bounded, and temporally delimited notion of identity formation. Empirically, Chaldeans’ identity formation highlights the heterogeneity in newcomers’ identity construction, one that differs from that of other co-nationals. Full article

The construction of prefabricated concrete houses in Ecuador poses significant challenges in terms of environmental and social sustainability, amid growing housing demand and the urgent need to mitigate adverse impacts associated with the construction processes and materials. In particular, the lack of a comprehensive assessment of these impacts limits the development of effective strategies to improve the sustainability of the sector. In addition, in rural areas, the design of flexible and adapted solutions is required, as evidenced by recent studies in the Andean area. This study conducts a comprehensive assessment of the impacts and sustainability indicators for prefabricated concrete houses, employing international certification systems such as LEED, BREEAM, and VERDE, to validate various relevant environmental and social indicators. The methodology used is the Hierarchical Analytical Process (AHP), which facilitates the prioritization of impacts through paired comparisons, establishing priorities for decision-making. Hydrological, soil, faunal, floral, and socioeconomic aspects are evaluated in a regional context. The results reveal that the most critical environmental impacts in Ecuador are climate change (28.77%), water depletion (13.73%) and loss of human health (19.17%), generation of non-hazardous waste 8.40%, changes in biodiversity 5%, extraction of mineral resources 12.07%, financial risks 5.33%, loss of aquatic life 4.67%, and loss of fertility 3%, as derived from hierarchical and standardization matrices. Despite being grounded in a literature review and being constrained due to the scarcity of previous projects in the country, this research provides a useful framework for the environmental evaluation and planning of prefabricated housing. To conclude, this study enhances existing methodologies of environmental assessment techniques and practices in the construction of precast concrete and promotes the development of sustainable and socially responsible housing in Ecuador. Full article

With the ongoing transformation of the energy structure and the advancement of smart grid development, green and sustainable development of substations has become an inevitable trend. As the core driving force of substation transformation, novel technologies remain at the pilot application stage, and their performance evaluations are yet to be clarified. In view of this, this paper proposes a comprehensive evaluation framework for the application effectiveness of novel technologies in green construction for substations. Firstly, based on the feature for the whole life cycle of the technologies, an evaluation index system is established covering multiple dimensions and stages, including resource conservation, technical performance enhancement, and economic benefits. Secondly, on the basis of AHP group decision and EWM combination weights, a variable-weight model is constructed by combining projection gray target evaluation to enable significant differentiation in cross-technology comparative analysis. Finally, a case study is conducted on pilot applications of multiple novel technologies in substations within a specific region, and the results indicate that novel technologies which demonstrate better sustainable development effects throughout the entire life cycle have a broader prospect for promotion. Full article

Karst regions, characterized by thin soil layers, severe rocky desertification, and fragile vegetation, hold significant scientific value for achieving China’s “dual-carbon” goals. This study focuses on Zhijin County in Guizhou Province, integrating provincial carbon density data with forest resource inventory data. By constructing a model to adjust aboveground forest carbon density (AGC) estimation parameters and utilizing the InVEST model alongside hotspot analysis, the research systematically examines the spatiotemporal heterogeneity of carbon storage from 2000 to 2020. These findings provide actionable strategies for enhancing carbon sequestration efficiency in ecologically fragile regions, supporting China’s “dual-carbon” policy goals. Key findings include: (1) Carbon storage exhibits a “growth-turning point” two-phase pattern, increasing by 0.46% from 2000 to 2015 but decreasing by 3.31% in 2020 due to construction land expansion. (2) There are significant differences in carbon storage among ecological engineering projects, with the highest carbon storage found in the “Grain-for-Green Program” project area and the lowest in the “National Rocky Desertification Control Program” area. (3) Elevation is the primary controlling factor for carbon storage, with rocky desertification showing notable spatial differentiation. This study provides theoretical support for the precise regulation of ecological programs and the development of high-precision carbon storage models in karst regions. Full article

In the cybersecurity attack and defense space, the “attacker” and the “defender” form a dynamic and symmetrical adversarial pair. Their strategy iterations and capability evolutions have long been in a symmetrical game of mutual restraint. We will introduce modern Intrusion Detection Systems (IDSs) from the defender’s side to counter the techniques designed by the attacker (APT attack). One major challenge faced by IDS is to identify complex attack paths from a vast provenance graph. By constructing an attack behavior tracking graph, the interactions between system entities can be recorded, but the malicious activities of attackers are often hidden among a large number of normal system operations. Although traditional methods can identify attack behaviors, they only focus on the surface association relationships between entities and ignore the deep causal relationships, which limits the accuracy and interpretability of detection. Existing graph anomaly detection methods usually assign the same weight to all interactions, while we propose a Causal Autoencoder for Graph Explanation (CAGE) based on reinforcement learning. This method extracts feature representations from the traceability graph through a graph attention network(GAT), uses Q-learning to dynamically evaluate the causal importance of edges, and highlights key causal paths through a weight layering strategy. In the DARPA TC project, the experimental results conducted on the selected three datasets indicate that the precision of this method in the anomaly detection task remains above 97% on average, demonstrating excellent accuracy. Moreover, the recall values all exceed 99.5%, which fully proves its extremely low rate of missed detections. Full article

This paper presents a comprehensive economic and environmental analysis of the utilization of recycled ceramic demolition materials in the construction sector, considering three distinct applications: erecting vertical partitions, constructing road bases, and producing decorative finishes. The findings demonstrate significant economic advantages when using recycled ceramic materials in structural applications, specifically vertical partitions and road base layers, with cost reductions of approximately 14.1% and 23.9%, respectively, compared to new materials. Conversely, the economic viability of using recycled materials for decorative finishes (“old brick”) proved limited due to high labor intensity and significant waste generation during processing, resulting in higher costs than using new materials. From an environmental perspective, the recycling of construction ceramics provides substantial benefits, notably in reducing carbon footprints. The greatest environmental benefit observed was a reduction in carbon footprint by about 90% in vertical partition applications, and about 70% for decorative finishes. Despite these benefits, practical implementation faces substantial technological and regulatory barriers, including labor-intensive recovery processes and the absence of unified quality standards. Overcoming these challenges requires further development of advanced sorting and processing technologies, clear regulations, unified quality standards, and educational efforts targeted at the construction industry and investors. Full article

This study aims to develop a performance evaluation system specifically for the design phase of high-rise building projects within the architecture, engineering, and construction industry, where performance is often only measured during construction. The research process included three stages: identification of 21 key performance indicators through a literature review and expert validation; development of standardized indicator sheets detailing calculation protocols and data collection procedures; and creation of a functional dashboard-based evaluation system using Excel. The system was validated through expert review and tested with a simulated project generated using an AI-based language model. The evaluation system proved functional, accessible, and effective in detecting performance issues across five core categories: planning, cost, time, quality, and people. The results from the simulated application highlighted strengths in quality and stakeholder collaboration but also revealed significant gaps in cost and time performance. This study addresses a gap in the existing literature by focusing on performance evaluation during the design phase of construction projects, a stage often underrepresented in performance studies. The resulting system offers a structured, practical tool adaptable to real-world projects. The validation relied on a limited number of expert participants and a simulated project. Future research should recommend broader international validation and real-world application. Full article

With the advancement of refined urban governance and the construction of high-quality public spaces, street furniture design and usage face multiple challenges, including insufficient public participation and a neglect of actual user experience. These issues highlight the urgent need to establish a scientifically grounded user evaluation framework to inform design practices. This study focuses on Yangzhou Ecological Science and Technology New Town and, drawing on field investigation, grounded theory, and the Delphi method, develops a street furniture design evaluation framework encompassing three core dimensions: planning and configuration, environmental coordination, and operational management. Building on this framework, the Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation method are employed to conduct a holistic assessment of the street furniture and to identify critical design deficiencies. The results demonstrate that the proposed framework effectively identifies the strengths and weaknesses of street furniture and provides robust support for formulating targeted optimization strategies. The results reveal significant variations in the perceived importance of design factors among different user groups. Residents primarily emphasize practicality and convenience in daily use. Tourists value aesthetic expression and cultural resonance, whereas government officials focus on construction standardization and maintenance efficiency. In terms of satisfaction, all three groups reported relatively low scores, with the ranking as follows: “planning and configuration” > “management and operations” > “environmental coordination.” Based on these findings, the study proposes targeted design guidelines for future practice. The evaluation framework has been adopted by local authorities, incorporated into official street furniture design guidelines, and implemented in pilot projects—demonstrating its practical applicability and value. This research contributes to the theoretical advancement of street furniture design and provides empirical and methodological support for applications in other emerging urban areas and new town developments. Full article

This research focuses on developing neural network-based models for predicting time and cost overruns in construction projects during the construction phase, incorporating sustainability considerations. Previous studies have identified seven key performance areas that affect the final outcome: productivity, quality, time, cost, safety, team satisfaction, and client satisfaction. Although the interconnections among these performance areas are recognized, their exact relationships and impacts are not fully understood. Hence, the utilization of a neural networks proves to be highly beneficial in predicting the outcome of future construction projects, as it can learn from data and identify patterns, without requiring a complete understanding of these mutual influences. The neural network was trained and tested on the data collected on five completed construction projects, each analyzed at three distinct stages of execution. A total of 182 experiments were conducted to explore different neural network architectures. The most effective configurations for predicting time and cost overruns were identified and evaluated, demonstrating the potential of neural network-based approaches to support more sustainable and proactive project management. The time overrun prediction model demonstrated high accuracy, achieving a MAPE of 10.93%, RMSE of 0.128, and correlation of 0.979. While the cost overrun model showed a lower predictive accuracy, its MAPE (166.76%), RMSE (0.4179), and correlation (0.936) values indicate potential for further refinement. These findings highlight the applicability of neural network-based approaches in construction project management and their potential to support more proactive and informed decision-making. Full article

Biodiversity in arid river basins is highly climate-sensitive, yet the multi-pathway relations among the environment, landscape structure, connectivity, and plant diversity remain unclear. Framed by a scale–place–space sustainability perspective, we evaluated, in the Hotan River Basin (NW China), how the environmental factors affect plant diversity directly and indirectly via the landscape configuration and functional connectivity. We integrated Landsat images (2000, 2012, and 2023), 57 vegetation plots, topographic and meteorological data; computed the landscape indices and Conefor connectivity metrics (PC, IIC); and fitted a partial least squares structural equation model (PLS-SEM). From 2000 to 2023, the bare land declined, converted mainly into shrubland and cropland; the construction land is projected to expand under SSP1-2.6/SSP2-4.5/SSP5-8.5 by 2035 and 2050. The landscape metrics showed a rising PD, DIVISION, and SHDI/SHEI, and a declining AI and CONTAG, indicating finer, more heterogeneous mosaics. Plant diversity peaked on low–moderate slopes and with ~32–36 mm annual precipitation. The PLS-SEM revealed significant direct effects on diversity from environmental factors (positive), landscape structure (negative), and connectivity (positive). The dominant chained mediation (environment → structure → connectivity → diversity) indicated that environmental constraints first reconfigure the spatial structure and then propagate to community responses via connectivity, highlighting connectivity’s role in buffering climatic stress and stabilizing communities. The findings provide a quantitative framework to inform biodiversity conservation and sustainable landscape planning in arid basins. Full article