Search Results (264)

In evaluating the construction safety of the building in the subway tunnel using the cover-and-cut method, the main objective is to analyze the diaphragm wall, the central pillar, and the roof. This article conducted a blasting vibration test based on the background of the Guiyang Metro Line 3 project and used the FLAC3D software to establish a three-dimensional numerical model. The results showed that the peak particle velocity (PPV) decreased with increasing distance from the blasting center. The PPV measured at the underground diaphragm wall was 1.424 cm/s, while at the bottom of the central pillar it was 1.482 cm/s. The predicted PPV on the roof was up to 1.537 cm/s, which met the safety standards. According to the cloud map of particle vibration velocity and the comprehensive analysis of particle vibration velocity, the degree of impact of artificial structures in the subway tunnel was the central pillar, the underground diaphragm wall, and the roof in order from high to low. After eight blasting operations per day, the vibration velocity trend at the vulnerable point of the central column increases, but it will not exceed the safety standard. Full article

The accuracy and stability of Very Long Baseline Interferometry (VLBI) systems are essential for maintaining global geodetic reference frames such as the International Terrestrial Reference Frame (ITRF). This study focuses on the precise determination of the VLBI Invariant Point (IVP) and the detection of antenna axis offset. Ground-based surveys were conducted at the Sejong Space Geodetic Observatory using high-precision instruments, including total station, to measure slant distances, as well as horizontal and vertical angles from fixed pillars to reflectors attached to the VLBI instrument. The reflectors comprised both prisms and reflective sheets to enhance redundancy and data reliability. A detailed stochastic model incorporating variance component estimation was employed to manage the varying precision of the observations. The analysis revealed significant measurement variability, particularly in slant distance measurements involving prisms. Iterative refinement of the variance components improved the reliability of the IVP and antenna axis offset estimates. The study identified an antenna axis offset of 5.6 mm, which was statistically validated through hypothesis testing, confirming its significance at a 0.01 significance level. This is a significance level corresponding to approximately a 2.576 sigma threshold, which represents a 99% confidence level. This study highlights the importance of accurate stochastic modeling in ensuring the precision and reliability of the estimated VLBI IVP and antenna axis offset. Additionally, the results can serve as a priori information for VLBI data analysis. Full article

Several approaches have been developed to generate synthetic object points using real LiDAR point cloud data for advanced driver-assistance system (ADAS) applications. The synthetic object points generated from a scene (both the near and distant objects) are essential for several ADAS tasks. However, generating points from distant objects using sparse LiDAR data with precision is still a challenging task. Although there are a few state-of-the-art techniques to generate points from synthetic objects using LiDAR point clouds, limitations such as the need for intense compute power still persist in most cases. This paper suggests a new framework to address these limitations in the existing literature. The proposed framework contains three major modules, namely position determination, object generation, and synthetic annotation. The proposed framework uses a spherical point-tracing method that augments 3D LiDAR distant objects using point cloud object projection with point-wall generation. Also, the pose determination module facilitates scenarios such as platooning carried out by the synthetic object points. Furthermore, the proposed framework improves the ability to describe distant points from synthetic object points using multiple LiDAR systems. The performance of the proposed framework is evaluated on various 3D detection models such as PointPillars, PV-RCNN, and Voxel R-CNN for the KITTI dataset. The results indicate an increase in mAP (mean average precision) by $1.97\%$, $1.3\%$, and $0.46\%$ from the original dataset values of $82.23\%$, $86.72\%$, and $87.05\%$, respectively. Full article

Multimodal fusion-based object detection is the foundational sensing task in scene understanding. It capitalizes on LiDAR and camera data to boost the robust results. However, there are still great challenges in establishing an effective fusion mechanism and performing accurate and diverse feature interaction fusion. In particular, the relationship construction between the two modalities has not been comprehensively exploited, leading to sensor data utilization deficiencies and redundancies. In this paper, a novel 3D object-detection framework, namely a symmetry-aware sparse sensor fusion detection network (2SFNet), is proposed. This framework was designed to leverage point clouds and RGB images. The 2SFNet consists of three submodules, filtered colored point cloud generation, pseudo-image generation, and a dilated feature fusion network, to solve these problems. Firstly, filtered colored point cloud generation constructs non-ground colored point cloud (NCPC) data by employing an early fusion strategy and a ground-height-filtering module, selectively retaining only object-related information. Subsequently, 2D grid encoding is used on the reduced colored data. Finally, the processed colored data are fed into the improved PillarsNet architecture, which now has expanded receptive fields to enhance the fusion effect. This design optimizes the fusion process by ensuring a more balanced and effective data representation, aligning with the symmetry concept that underlies the model’s functionality. Experiments and evaluations were conducted on the KITTI dataset to present the effectuality, particularly for categories characterized by sparse point clouds. The results indicate that the symmetry-aware design of the 2SFNet leads to an improved performance when compared to other multimodal fusion networks, and alleviates the phenomenon caused by highly obscured and crowded scenes. Full article

Laboratory-based high-sensitivity cardiac troponin testing has been the pillar for emergency stratification of suspected acute coronary syndrome for well over a decade. Point-of-care troponin assays achieving the requisite analytical sensitivity have recently been developed and could accelerate such assessment. This review summarises the latest assays and describes their potential diverse clinical utility in the emergency department, community healthcare, pre-hospital, and other hospital settings. It outlines the current clinical data but also highlights the evidence gap, particularly the need for clinical trials using whole blood, that must be addressed for safe and successful implementation of point-of-care troponin analysis into daily practice. Additionally, how point-of-care troponin testing can be coupled with advances in biosensor technology, cardiovascular screening, and triage algorithms is discussed. Full article

The work developed aims to present an innovative methodology to execute the heritage conservation processes in a collaborative and interdisciplinary Building Information Modeling (BIM) project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with an architectural survey using terrestrial laser scanning (TLS) and terrestrial photogrammetry software, Structure from Motion (SfM), studying study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the Cyclone 3DR post-processing software, which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it was possible to develop an efficient Scan-to-HBIM workflow, where the Heritage BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, and quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural heritage, focusing on the deformations and deterioration of the masonry in columns and pilasters. To make multidisciplinary conservation work more flexible, specific properties have been created for the identification and analysis of the degradation detected in the structures, with the HBIM project constituting a manager of the control and inspection activities. The restoration technician interacts with the determined 3D element to mark the “type decay”, managing the properties in the element’s own definition window. Interactive schemes have been defined that incorporate the items for the mapping of the elements, as well as particular properties of a conservation process (intervention, control, and maintenance). All listed parametric elements have links to be viewed in 2D and 3D views. Therefore, the procedure has facilitated the auscultation of the scanned element as it is semantically delimited, the parametric modeling of it, the analytical study of its materials and deterioration, and the association of intrinsic parameters so that they can be evaluated by all the intervening agents. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment. Full article

New Zealand’s goal of achieving net-zero greenhouse gas emissions (GHG) by 2050 highlights the urgent need for integrating sustainable practices into the construction industry. Since the construction industry makes a major contribution to GHG emissions, this study aims to address this need by identifying and prioritizing the critical criteria relevant to the effective selection of sustainable construction materials for New Zealand’s construction industry. The research employs a multi-stage approach, including a comprehensive literature review, expert interviews, and industry surveys. Initially, 80 criteria were identified through the literature review. Subsequently, expert interviews and industry surveys led to the identification of 30 critical criteria, which were categorized into environmental, technical, economic, and social impacts, and were ranked based on their importance. This study utilizes a 5-point importance index and Analytic Hierarchy Process (AHP) to rank these criteria. This study notably integrates technical impacts with the three traditional sustainability pillars—environmental, economic, and social—providing a nuanced evaluation of construction material selection. The results indicate that environmental and technical criteria received the highest priority weights (32% each), followed by economic (19%) and social impacts (17%). The findings offer valuable insights for industry stakeholders, assisting them in applying these critical criteria to improve material selection practices in alignment with New Zealand’s sustainability objectives. Full article

Human activity recognition (HAR) technology is related to human safety and convenience, making it crucial for it to infer human activity accurately. Furthermore, it must consume low power at all times when detecting human activity and be inexpensive to operate. For this purpose, a low-power and lightweight design of the HAR system is essential. In this paper, we propose a low-power and lightweight HAR system using point-cloud data collected by radar. The proposed HAR system uses a pillar feature encoder that converts 3D point-cloud data into a 2D image and a classification network based on depth-wise separable convolution for lightweighting. The proposed classification network achieved an accuracy of 95.54%, with 25.77 M multiply–accumulate operations and 22.28 K network parameters implemented in a 32 bit floating-point format. This network achieved 94.79% accuracy with 4 bit quantization, which reduced memory usage to 12.5% compared to existing 32 bit format networks. In addition, we implemented a lightweight HAR system optimized for low-power design on a heterogeneous computing platform, a Zynq UltraScale+ ZCU104 device, through hardware–software implementation. It took 2.43 ms of execution time to perform one frame of HAR on the device and the system consumed 3.479 W of power when running. Full article

With advancements in autonomous driving, LiDAR has become central to 3D object detection due to its precision and interference resistance. However, challenges such as point cloud sparsity and unstructured data persist. This study introduces MS3D (Multi-Scale Feature Fusion 3D Object Detection Method), a novel approach to 3D object detection that leverages the architecture of a 2D Convolutional Neural Network (CNN) as its core framework. It integrates a Second Feature Pyramid Network to enhance multi-scale feature representation and contextual integration. The Adam optimizer is employed for efficient adaptive parameter tuning, significantly improving detection performance. On the KITTI dataset, MS3D achieves average precisions of 93.58%, 90.91%, and 88.46% in easy, moderate, and hard scenarios, respectively, surpassing state-of-the-art models like VoxelNet, SECOND, and PointPillars. Full article

To address the challenges of limited detection precision and insufficient segmentation of small to medium-sized objects in dynamic and complex scenarios, such as the dense intermingling of pedestrians, vehicles, and various obstacles in urban environments, we propose an enhanced methodology. Firstly, we integrated a point cloud processing module utilizing the DBSCAN clustering algorithm to effectively segment and extract critical features from the point cloud data. Secondly, we introduced a fusion attention mechanism that significantly improves the network’s capability to capture both global and local features, thereby enhancing object detection performance in complex environments. Finally, we incorporated a CSPNet downsampling module, which substantially boosts the network’s overall performance and processing speed while reducing computational costs through advanced feature map segmentation and fusion techniques. The proposed method was evaluated using the KITTI dataset. Under moderate difficulty, the BEV mAP for detecting cars, pedestrians, and cyclists achieved 87.74%, 55.07%, and 67.78%, reflecting improvements of 1.64%, 5.84%, and 5.53% over PointPillars. For 3D mAP, the detection accuracy for cars, pedestrians, and cyclists reached 77.90%, 49.22%, and 62.10%, with improvements of 2.91%, 5.69%, and 3.03% compared to PointPillars. Full article

The present article is devoted to the issue of studying the patterns of displacement of superincumbent rock over panels of a mine obtained using advanced seismic technologies, allowing for the study of the boundaries of caving zones in the depths of rock mass. A seismic exploration has been performed in local areas of Zhomart mine responsible for the development of Zhaman-Aybat cuprous sandstone deposits in Central Kazakhstan at the stage of repeated mining with pulling of previously non-mined ore pillars and superincumbent rock caving. A 2D field seismic exploration has been accomplished, totaling to 8000-line m of seismic lines using seismic shot point. The survey depth varied from 455 m to 625 m. The state-of-the-art technologies of kinematic and dynamic analysis of wavefield have been widely used during data processing and interpretation targeted at identifying anomalies associated with the structural heterogeneity of the pays and rock mass, engaging modern algorithms and mathematical apparatuses of specialized geodata processing systems. The above effort resulted in new data regarding the location and morphology of the reflectors, characterizing geological heterogeneity of the section, zones of smooth rock displacement, and displacement of strata with significant disturbance of the rocks overlying mined-out productive pay. The potential of the application of modern 2D seismic exploration to studying an underworked zone with altered physical and mechanical properties located over an ore deposit has been assessed. The novelty and practical significance of the research lies in the determination of the boundaries of zones of displacement and superincumbent rock caving over the panels obtained using state-of-the-art technologies of seismic exploration. The deliverables may be used to improve the process of recognizing specific types of technogenic heterogeneities in the rock mass, impacting the efficiency and safety of subsurface ore mining, both for localization and mining monitoring. Full article

To investigate the reasonable width of a coal pillar in the downward mining section of close-distance coal seams, the stress state of any point below the residual coal pillar in the overlying goaf and the width of a small coal pillar were studied by theoretical calculation, numerical simulation, similar simulation and field monitoring. The findings indicate that the width range of the small coal pillar is 7.92~11.42 m. The 4-1 coal seam is in the stress reduction zone when it is more than 16.6 m horizontally from the border of the residual coal pillar above it. In addition, the peak stress is situated inside the elastic zone of the coal pillar and is lower than the coal pillar’s bearing limit when a small coal pillar of 8 m is maintained. With the help of distributed optical fiber monitoring to model the coal pillars’ stress distribution, it is found that 8 m simulated coal pillars have a certain bearing capacity. The practical findings demonstrate that the 8 m small coal pillar that was left on the site satisfies the demand, and the convergence of the roadway’s floor and roof, and its two sides fall within the controllable range. The findings of the study offer a reference for the location of a return air roadway and the width of section coal pillars in the downward mining of close-distance coal seams. Full article

Hanging tunnels are a unique type of highway constructed on hard cliffs and towering mountains, renowned for their steep and distinctive characteristics. Compared to traditional full tunnels or open excavations, hanging tunnels offer significant advantages in terms of cost and construction time. However, the engineering design and construction cases of such tunnels are rarely reported, and concerns about construction safety and surrounding rock stability have become focal points. Taking the Shibanhe hanging tunnel as a case study, this paper focuses on the stability of the surrounding rock during the excavation of limestone hanging tunnels using physical analog model (PAM) experiments and numerical calculation. Firstly, based on the similarity principle and orthogonal experiments, river sand, bentonite, gypsum and P.O42.5 ordinary Portland cement were selected as the raw materials to configure similar materials from limestone. Secondly, according to the characteristics of hanging tunnels, geological models were designed, and excavation experiments with three different sidewall excavation widths and rock wall slopes were carried out. The effects of these variables on the stress and displacement behavior of the surrounding rock were analyzed, and the laws of their influence on the stability of the surrounding rock were explored. Finally, numerical simulations were employed to simulate the tunnel excavation, and the results of the numerical simulations and PAM experiments were compared and analyzed to verify the reliability of the PAM experiment. The results showed that the vertical stress on the rock pillars was significantly affected by the sidewall excavation widths, with a maximum increase rate of 53.8%. The displacement of the sidewall opening top was greatly influenced by the sidewall excavation widths, while the displacement of the sidewalls was more influenced by the rock wall slope. The experimental results of the PAM are consistent with the displacement and stress trends observed in the numerical simulation results, verifying their reliability. These findings can provide valuable guidance and reference for the design and construction of hanging tunnels. Full article

This paper presents our study of the deformation and failure characteristics surrounding rock in roadways with super-large sections during the integrated coal pillar excavation, filling and retention process between coalfaces. Based on the theory of complex variable function, the mapping accuracy of conformal transformation is improved, and an analytical solution for surrounding rock stress in super-large sections of roadway is derived. The stress distribution law of the surrounding rock of rectangular roadways is analyzed, and numerical simulation software is used for supplementary analysis and verification. According to the research findings, the compressive stresses on two sides and the tensile stress on the roof of a rectangular roadway with super-large sections decreased with the increase in the side-pressure coefficient; however, when the side-pressure coefficient increased to a certain point, those two sides changed from a pressure-bearing status to a tensile force-bearing status, while the roof changed from a tensile force-bearing status to a pressure-bearing status. In these stress changes, all the stresses upon the surrounding rock of roadways were compressive stresses and the two critical side-pressure coefficient values were λ_up and λ_down. As the aspect ratio of the roadway increased from 1 to 9, its λup increased from 1.823 to 5.865 and its λdown increased from 0.549 to 0.888. When those side-pressure coefficients in the environment where a roadway is located exceed their critical values, tensile stress will take place on the roadway boundary and result in tensile failure, thus leading to instability in the roadway super-large section. The impact of the side-pressure coefficient upon the plastic zone range of roadway surrounding rock is greater than the impact of the roadway width. In order to secure stability in the surrounding rock of roadways with super-large sections during the excavation process, the side-pressure coefficient should remain around 1; in this situation, the plastic zone covers the smallest range and the relevant support work is the easiest. These research findings provide theoretical references for the excavation and support of roadways with super-large sections. Full article

This paper addresses the critical and urgent need to reduce food losses and waste (FLW) resulting from stringent marketing standards. It proposes a comprehensive and actionable framework grounded in the three pillars of sustainability—environmental, economic, and social—to effectively evaluate FLW across the entire food supply chain. The paper involves a thorough review of existing marketing standards, including research on FLW due to marketing standards, and proposes the implementation of targeted key actions within four key food sectors: fruits, vegetables, dairy, and cereals. The study provides a detailed analysis of the significant impact marketing standards have on FLW at various stages of the supply chain, including primary production, processing, retail, and consumption. By focusing on these critical points, the research underscores the necessity of addressing marketing standards to achieve meaningful reductions in FLW. The proposed framework aims to foster improved business practices and drive the development of innovative, sector-specific solutions that balance sustainability goals with economic viability. The holistic approach followed for this research lays the foundation for ensuring that the proposed framework is adaptable and practical, leading to measurable improvements in reducing FLW and promoting sustainability across the food industry. Full article