Construction Method Research Articles

Effective Project Delivery Method for Public Construction: Case in the Oromia Region, West Wallaga Zone

This thesis is to identify and evaluate effective delivery methods and assess their applicability to the local situations in the Oromia region of the West Wallaga Zone. The significance of the research is that the broadening of the service packages is believed to enable the optimization of the process and the product as a whole in the construction industry, as well as facilitate the development of the infrastructure sectors. The objective of this research is to identify effective project delivery methods for public works construction in the Oromia Region West Wallaga Zone. The data collection process used in the research had the option of two basic methods: primary data collection and secondary data collection. Accordingly, four project delivery methods based on their relevance to the local situation have been evaluated; their merits, demerits, and requirements have been identified. These methods are: the design-bid-build, construction managers (at resk and at fee), the design-build, and the design-build-operate-transfer methods. Based on these findings of the study, the design-bid-Build method has been the most widely used effective project delivery method in the Oromia Region West Wallaga Zone. Performance-based project delivery methods are thought to offer a way to develop the sector and to benefit all stakeholders. In order to benefit all parties involved in the building sector, this will serve as a beneficial addition to the current techniques.

Continuous Slag Discharge Construction Technology for Shield Tunneling in Narrow Space Environment

The shield tunneling method is the main construction method in subway tunnel construction, which has the characteristics of safety, efficiency, mechanization, and high degree of automation. However, the shield tunneling equipment is huge, the supporting facilities are numerous, and the site requirements are high. In response to the problems of slow slag removal speed and low construction efficiency in shield tunneling under the construction conditions of small wellhead shield tunneling sections in urban subways, taking the shield tunneling section of Guangzhou Metro Line 13 Phase II as the background,This article introduces the main components, working principles, installation and transportation processes, fault handling, and benefit analysis of the continuous belt conveyor slag removal system,This article elaborates on the method of using a continuous belt conveyor in the tunnel combined with a vertical lifting system at the wellhead to achieve continuous slag removal during underground shield tunneling construction in a narrow wellhead construction site. This not only improves excavation efficiency but also reduces construction costs, solves construction problems, and provides reference for similar projects in the future.

MDD brain network analysis based on EEG functional connectivity and graph theory

BackgroundExisting studies have shown that the brain network of major depression disorder (MDD) has abnormal topologies. However, constructing reliable MDD brain networks is still an open problem. New methodThis paper proposed a reliable MDD brain network construction method. First, seven connectivity methods are used to calculate the correlation between channels and obtain the functional connectivity matrix. Then, the matrix is binarized using four binarization methods to obtain the EEG brain network. Besides, we proposed an improved binarization method based on the criterion of maximizing differences between groups: the adaptive threshold (AT) method. The AT can automatically set the optimal binarization threshold and overcome the artificial influence of traditional methods. After that, several network metrics are extracted from the brain network to analyze inter-group differences. Finally, we used statistical analysis and Fscore values to compare the performance of different methods and establish the most reliable method for brain network construction. ResultsIn theta, alpha, and total frequency bands, the clustering coefficient, global efficiency, local efficiency, and degree of the MDD brain network decrease, and the path length of the MDD brain network increases. Comparison with existing methodsThe results show that AT outperforms the existing binarization methods. Compared with other methods, the brain network construction method based on phase-locked value (PLV) and AT has better reliability. ConclusionsMDD has brain dysfunction, particularly in the frontal and temporal lobes.

Application and investigation of knowledge graph in biomedical field

A large amount of drug and disease research knowledge is scattered in unstructured literature data, presenting significant challenges in text mining within the field of biomedicine. These challenges include handling professional knowledge, integrating related knowledge, and disambiguating different meanings of the same words. Therefore, constructing a biomedical knowledge graph can significantly save expert human resources and make efficient use of medical literature resources. This review paper aims to summarize the construction methods used during the development of Biomedical Knowledge Graphs. It also outlines the latest models and frameworks, such as BioBERT and LSTM+CRF, highlighting their contributions and applications. In addition, this paper points out the limitations of current biomedical knowledge graphs, such as scalability issues and the need for large annotated datasets. To address these limitations, it proposes the use of Apache Spark for improved processing capabilities and transfer learning to enhance model performance and adaptability in diverse biomedical contexts.

基于扫描上下文和 NDT-ICP 融合方案的果园同步定位与绘图方法研究

Simultaneous localization and mapping (SLAM) is one of the key technologies for agricultural robots to build maps and localize in complex orchard environments and realize unmanned autonomous operations. Due to the complexity of the orchard environment, the single canopy feature and the diffuse reflection of light caused by the leaves, etc., the map construction process of the orchard environment leads to mismatch and increases the cumulative error of the map construction. Aiming at the above problems, this paper propose a navigation map construction method for orchard environment based on the fusion of Scan Context and NDT-ICP. The method firstly searches the Ring key quickly to get the candidate frames, and scores the similarity between the candidate frames and the current frame, and effectively detects the loopbacks by two-stage searching algorithm to reduce the false matches in the map of orchard environment. Meanwhile, a point cloud alignment method based on the fusion of normal distribution transform coarse alignment and iterative nearest point exact alignment is used to reduce the cumulative error of the orchard environment map. The results show that the improved algorithm compensates the drift of the point cloud map with higher mapping accuracy, better real-time performance, lower resource utilization, higher overlap between the trajectory estimation and the real trajectory, smoother loops, and a 4% reduction in CPU occupancy. In the complex orchard environment, the root mean square error and standard deviation of the trajectories of this paper's algorithm are 0.57 m and 0.19 m, which are 68% and 83% higher than those of the loop detection algorithms in the Lightweight Ground Optimized Lidar Trajectory Measurement and Multivariate Terrain Mapping (LeGO-LOAM), respectively. Accurate map construction and low drift pose estimation can be performed.The research algorithm effectively reduces the influence of mis-matching and large cumulative error in the process of map construction in the orchard environment, meets the demand for high-precision environmental mapping in the orchard environment, and provides technical support for promoting unmanned operation in the orchard environment.

Overview of knowledge graph construction in the field of fully electronic computer interlocking systems

As a core technology in railway signal control, the fully electronic computer interlocking system achieves the control of railway signals and switches through computerization, ensuring the safety and efficiency of train operations. With the increasing complexity of railway systems, traditional management and maintenance face significant challenges. Knowledge graphs, as an advanced data management and representation method, can effectively organize and utilize large-scale domain knowledge, enhancing the system's intelligence. This paper introduces the construction methods, core concepts, and applications of knowledge graphs in the field of fully electronic computer interlocking systems, providing references for research and practice in this area.

Cognitive Bias in Perceptions of Industrialized Housing

Industrialized housing offers potential benefits in efficiency and sustainability compared to traditional construction methods, but public perception often remains negative due to a lack of familiarity. This study explores how prior information and knowledge influence perceptions of industrialized versus traditional housing. An online survey with 267 participants evaluated stimuli composed of an image of a house and a label (industrialized or non-industrialized). Results indicated no significant differences in perception based on visual appearance alone; however, the “industrialized” label was rated less favorably. This effect was more pronounced among those without expertise in industrialized construction. The study also revealed that providing objective prior information improved perceptions of personal and emotional attributes (e.g., cozy, family-friendliness, comfortable, well-being), but did not affect views on construction-specific attributes (e.g., quick-to-build, automated, or modular). These findings underscore the need for neutral and informative communication to counteract negative biases and enhance acceptance of industrialized housing. For the construction industry and policymakers, it is crucial to promote unbiased information and education to overcome resistance due to misconceptions and foster a more positive perception of the product’s features. Addressing concerns and clarifying benefits, these initiatives aim to shift public opinion toward recognizing the value of industrialized housing.

The Current Status of the Application of Surgical Specialty Nursing Quality Evaluation Indicators

This paper reviews the current status of the application of surgical specialty nursing quality evaluation indicators both domestically and internationally. It covers the related concepts, theoretical foundations, construction methods, construction fields, application research, and existing shortcomings of these indicators. It suggests that scholars and researchers in the nursing field in China should base their work on mature theories, use scientific research methods, and construct a quality indicator system that aligns with China’s surgical development, is practical, unified, suitable for the local context, and beneficial for the development of the surgical nursing discipline.

Construction of Spirocyclic Compounds via Electrochemical Intramolecular Dearomatization of Benzene Derivatives

The spirocyclic framework is found in many natural products, some of which are biologically active. However, It remains a challenge to develop environmentally friendly and atom‐economic synthetic methods. Herein, we report an intramolecular dearomatization reaction of benzene derivatives enabled by electrochemistry‐mediated two successive single‐electron‐transfer (SET) processes, providing an alternative method for the rapid construction of spirocyclic skeletons without using sacrificial reagents. A series of cyclohexadiene products were obtained in 25‐81% yields. Furthermore, a proposed mechanism involving a sequential electron transfer event was supported by cyclic voltammetry experiments. This strategy features transition‐metal‐free conditions and easy handling, which will greatly enhance its practical utility.

Research on Construction Method of Water Body Database in Wuhan City

Water is the source of life, the factor of production and the basis of ecology. When controlling flood disasters and planning water use, it is necessary to use the local water body information, so how to grasp the local water body information accurately and real-time becomes crucial. With the development of modern science and technology, image information can be quickly obtained by remote sensing satellites, and corresponding water system information can be obtained by processing satellite image data, and water body database can be established. This paper takes Wuhan city as the research object, uses Landsat-8 satellite images in 2020 as the data source, adopts the normalized differential water index method (NDWI) to extract water system information, and then constructs the database of the obtained water system information of Wuhan City through ArcGIS software, which can provide basic information for water data management of Wuhan City.

Optimization Method of Mine Ventilation Network Regulation Based on Mixed-Integer Nonlinear Programming

Mine ventilation is crucial for ensuring safe production in mines, as it is integral to the entire underground mining process. This study addresses the issues of high energy consumption, regulation difficulties, and unreasonable regulation schemes in mine ventilation systems. To this end, we construct an optimization model for mine ventilation network regulation using mixed-integer nonlinear programming (MINLP), focusing on objectives such as minimizing energy consumption, optimal regulation locations and modes, and minimizing the number of regulators. We analyze the construction methods of the mathematical optimization model for both selected and unselected fans. To handle high-order terms in the MINLP model, we propose a variable discretization strategy that introduces 0-1 binary variables to discretize fan branches’ air quantity and frequency regulation ratios. This transformation converts high-order terms in the constraints of fan frequency regulation into quadratic terms, making the model suitable for solvers based on globally accurate algorithms. Example analysis demonstrate that the proposed method can find the optimal solution in all cases, confirming its effectiveness. Finally, we apply the optimization method of ventilation network regulation based on MINLP to a coal mine ventilation network. The results indicate that the power of the main fan after frequency regulation is 71.84 kW, achieving a significant energy savings rate of 65.60% compared to before optimization power levels. Notably, ventilation network can be regulated without adding new regulators, thereby reducing management and maintenance costs. This optimization method provides a solid foundation for the implementation of intelligent ventilation systems.

Construction of dielectric and magnetic coupling cobalt salt/chitosan derived Co/C hybrid aerogels for high-performance infrared/radar compatible applications

In virtue of mutually exclusive stealth mechanisms, effectively protecting from infrared detection and attenuating microwaves through composition and structure design remains a formidable challenge. To achieve high-efficiency infrared/radar compatible stealth, in this work, 0D magnetic Co nanoparticles were successfully in situ grown onto the renewable biomass chitosan-based 3D porous carbon skeletons via facile liquid reaction, freeze-drying, and calcination method. Herein, the as-prepared Co/C hybrid aerogels exhibit dielectric and magnetic coupling network, and the relevant infrared/radar compatible stealth property can be regulated by adjusting the addition amount of Co salt. The minimum thermal conductivity value reached 0.095 W m−1 K−1 at 60 °C, and the lowest infrared emissivity of 0.717 in the 8–14 μm band was also achieved. Furthermore, the minimum reflection loss (RLmin) value of −44.70 dB at a relatively thin thickness of 1.35 mm and the maximum effective absorption bandwidth (EAB) of 5.45 GHz at only 1.5 mm appeared in the optimal Co/C hybrid aerogel with the most appropriate Co content. Compared with perfect conductive layer (PEC), the simulated radar cross section (RCS) signals of Co/C composites covered PEC have been significantly reduced by 18.44 dB m2 at the scanning angle of 80°. This study inspires the exploration of the elaborate design strategy and facile construction method for environment-friendly infrared/radar compatible hybrid aerogels in the future.

Exploring Sustainable Approaches for Electronic Textile Products and Prototypes.

This research investigated the sustainability of textile garments with integrated electronics and their potential impact on the environment. The electronic textiles (E-textiles) sector is booming, with many advancements in E-textile product designs and construction methods having been made in recent years. Although there is a rapidly increasing interest in the reusability and sustainability of textiles, work towards E-textile sustainability requires further attention. Vastly different components are combined when constructing an electronic textile product, which makes it challenging at the end of the life of these products to dispose of them in a responsible way. In this study, a teardown analysis was conducted using a structured method, which first mapped out the interactions between each component of the product with the environment, followed by using Kuusk's sustainable framework to analyze sustainable strategies. The research provides a unique contribution to transitioning sustainability theories into practical applications in the area of E-textiles, and the method proposed in this work can be employed in modifying electronics-embedded textiles to improve longevity and reduce the negative environmental impact. The work has highlighted key points of improvement that could be applied to a series of commercial E-textile garments, as well as a prototype E-textile device. Beyond this, the work provides a systematic approach for implementing new E-textile product designs that can evaluate overall product sustainability from the design stage to material selection, construction, and the planning of the commercial approaches of a product.

Examining the role of concrete 3D printing for housing construction on Indigenous Reserves in Canada

PurposeThis research explores the role of concrete 3D printing (C3DP) in the development of culturally appropriate housing in Indigenous Reserves in Canada through the design, building and evaluation of the Star Lodge project located in the Siksika Nation of Alberta, Canada. The project aims to assess the potential of C3DP in addressing the escalating housing demands in Indigenous communities in Canada.Design/methodology/approachThe research involved a collaborative and multidisciplinary approach, engaging Blackfoot Elders, Knowledge Keepers from the Siksika Nation, Siksika Housing and Nidus3D. Central to this was the design, build and documentation of the Star Lodge project to analyse the advantages and challenges, guided by weekly meetings and site visits.FindingsThe project harnessed C3DP to streamline construction, enhance durability, reduce maintenance costs and enhance the energy performance of the homes. Notable time savings were achieved compared to conventional construction methods. Challenges included developing strategies to overcome extreme cold weather conditions, achieving a consistent concrete mix and integrating conventional construction elements such as drywall construction in interiors. The project served as a platform for collaboration and community participation, shaping the design and construction process while raising awareness of innovative construction techniques in the community.Originality/valueThis study provides an evidence-based framework for the evaluation of C3DP technology by analysing the Star Lodge Project, the first C3DP project in Alberta and the largest of its kind in Canada. By addressing housing challenges in Indigenous communities, the research holds broader implications for sustainable development and Indigenous empowerment across Canada.

FDIA localization and classification detection in smart grids using multi-modal data and deep learning technique

False data injection attacks (FDIA) exploit the vulnerabilities of bad data detection in energy management systems to maliciously tamper with state estimation results, seriously jeopardizing the safe and reliable operation of power systems. In order to promptly detect FDIA, recent studies have used machine learning techniques to extract attack characteristics and detect FDIA based on changes in these characteristics. Current research predominantly focuses on detecting a single type of FDIA attack model and topology. However, the increasing diversification of FDIA construction methods and the variability of topological structures in power systems can reduce or even invalidate detection effectiveness. To cope with the abovementioned difficulties, this study introduces a multimodal deep learning detection model based on variational graph auto-encoders (VGAE), temporal convolutional networks (TCN), and gated recurrent units (GRU). The topological features of power systems are obtained through VGAE to adapt to the detection needs of various topological structures and performance enhancement. These features are then integrated with preprocessed measurement data via BDD to form multimodal data. Furthermore, this multimodal data is used to locate and classify FDIA with complete information, FDIA with incomplete information, and topology attack after applying a multi-label classification algorithm based on TCN-GRU for temporal feature extraction. Experiments carried out on the IEEE 14 and IEEE 118 bus systems show that the proposed method is robust and has high detection performance. The results indicate that the proposed detection method achieves AUC values that are, on average, 0.085, 0.145, and 0.04 higher than those of CNN, LSTM, and CNN-LSTM, respectively. Moreover, under various noise and attack intensities, recall, precision, F1 score, and RACC remain above 0.859, 0.877, 0.867, and 0.818, respectively, with a classification accuracy greater than 0.912. This study provides a unique perspective on detecting FDIA across various attack models and power system topologies.

Advancing Circular Buildings: A Review of Building Strategies for AEC Stakeholders

The uptake of a circular economy (CE) in the building sector is challenging, primarily due to the complexity associated with the design process and the dynamic interaction among architects, engineers, and construction (AEC) stakeholders. The standard and typical design process and construction methods raise concerns about building life cycles. Buildings should not only fulfill current needs, but one also needs to consider how they will function in the future and throughout their lifetime. To address these complexities, early planning is required to guide designers in holistically applying systems thinking to deliver CE outcomes. This paper outlines a critical review of CE implementation in buildings, with a proposed trifecta of approaches that significantly contribute to the development of circular buildings (CBs). The findings outline a proposed visualized framework with a conceptual formula that integrates CE design strategies to simplify and enhance AEC stakeholders’ perception of the circularity sequence in buildings. By strategically integrating loop-based strategies with the value retention process (VRP) and design for X (DFX) strategies, along with efficient assessment tools and technologies, it becomes feasible to embrace a CE during the design phase. The outcome of this review informs AEC stakeholders to systematically and strategically integrate the critical dimensions of a CE throughout the building life cycle, striking a balance between environmental concern, economic value, and future needs.

Effects of impact and microphone positions on heavy-weight floor impact sound pressure levels in concrete buildings

This study aims to analyze the spatial distribution of heavy-weight impact sound transmitted to a receiving room in 59 households within a concrete residential building. The performance of buildings is generally regulated by single number quantities such as L′iA,Fmax. To enhance performance, it is important to understand the effect of the impact sound pressure level at designated impact positions and microphones. Therefore, this study proposes a method to quantify the impac sound pressure level for determining L′iA,Fmax according to the impact and microphone positions. Analysis of the data revealed that significant similarities in frequency spectra were observed when generating impacts at two positions near the window, in addition to two at the area near the corridor, both of which have similar boundary conditions. The central impact position exhibited the highest contribution at 24.6%, while other positions had contributions of 18.2–19.5%. For the microphone positions, those located at the corners on either side of the window showed contributions of 22.8–23.7%, whereas the remaining positions demonstrated lower contributions of 17.3–18.5%. These results can serve as basic data for developing construction methods to reduce floor impact sound.

Opportunities and Challenges in the Implementation of Modular Construction Methods for Urban Revitalization

The urban landscape is undergoing significant transformations due to economic shifts, urban planning initiatives, technological advancements, and sociopolitical changes. Almost 89% of the U.S. population is projected to reside in urban areas by 2050, which increases a pressing need for innovative and efficient urban revitalization strategies. Modular construction is an extensively researched topic with potential promise for addressing these challenges; however, there is a lack of comprehensive understanding of its specific opportunities and challenges within the context of urban revitalization. This paper explores the potential of modular construction methods as a viable solution in densely populated areas with limited space and competing land uses. This study employs a systematic literature review using PRISMA and mixed methods analysis with NVivo to identify the opportunities and challenges associated with implementing modular construction in urban settings. The findings highlight the advantages of modular construction, including reduced construction time, enhanced quality control, and improved sustainability. However, challenges such as land scarcity, restrictive zoning laws, and the need for innovative planning and collaboration among stakeholders are also emphasized. This paper provides valuable insights for policymakers, urban planners, and developers to effectively leverage modular construction methods for sustainable and efficient urban renewal efforts.

An Effective LiDAR-Inertial SLAM-Based Map Construction Method for Outdoor Environments

An Effective LiDAR-Inertial SLAM-Based Map Construction Method for Outdoor Environments

Research on the "2+1" Talent Training Model in Higher Vocational Railway Colleges under the "Four Platforms and One Meeting" Linkage Mechanism

This study aims to explore the construction and implementation of the "2+1" talent training model in higher vocational railway colleges under the "Four Platforms and One Meeting" linkage mechanism. Through theories of school-enterprise cooperation, Internet+ education, and talent training models, the study analyzes the construction methods of school-enterprise teaching platforms, online resource platforms, enterprise practice platforms, and school-enterprise joint "2+1" teaching feedback platforms. The research finds that the "Four Platforms and One Meeting" linkage mechanism can effectively integrate school and enterprise resources, leverage the advantages of Internet+, improve the quality of talent training, and provide innovative pathways for the reform of higher vocational education.