Search results

Fall accidents can cause casualties and economic losses in the construction industry. Fall portents, such as loss of balance (LOB) and sudden sways, can result in fatal, nonfatal or attempted fall accidents. All of them are worthy of studying to take measures to prevent future accidents. Detecting fall portents can proactively and comprehensively help managers assess the risk to workers as well as in the construction environment and further prevent fall accidents.

This study focused on the postures of workers and aimed to directly detect fall portents using a computer vision (CV)-based noncontact approach. Firstly, a joint coordinate matrix generated from a three-dimensional pose estimation model is employed, and then the matrix is preprocessed by principal component analysis, K-means and pre-experiments. Finally, a modified fusion K-nearest neighbor-based machine learning model is built to fuse information from the x, y and z axes and output the worker's pose status into three stages.

The proposed model can output the worker's pose status into three stages (steady–unsteady–fallen) and provide corresponding confidence probabilities for each category. Experiments conducted to evaluate the approach show that the model accuracy reaches 85.02% with threshold-based postprocessing. The proposed fall-portent detection approach can extract the fall risk of workers in the both pre- and post-event phases based on noncontact approach.

First, three-dimensional (3D) pose estimation needs sufficient information, which means it may not perform well when applied in complicated environments or when the shooting distance is extremely large. Second, solely focusing on fall-related factors may not be comprehensive enough. Future studies can incorporate the results of this research as an indicator into the risk assessment system to achieve a more comprehensive and accurate evaluation of worker and site risk.

The proposed machine learning model determines whether the worker is in a status of steady, unsteady or fallen using a CV-based approach. From the perspective of construction management, when detecting fall-related actions on construction sites, the noncontact approach based on CV has irreplaceable advantages of no interruption to workers and low cost. It can make use of the surveillance cameras on construction sites to recognize both preceding events and happened accidents. The detection of fall portents can help worker risk assessment and safety management.

Existing studies using sensor-based approaches are high-cost and invasive for construction workers, and others using CV-based approaches either oversimplify by binary classification of the non-entire fall process or indirectly achieve fall-portent detection. Instead, this study aims to detect fall portents directly by worker's posture and divide the entire fall process into three stages using a CV-based noncontact approach. It can help managers carry out more comprehensive risk assessment and develop preventive measures.

The purpose of this paper is to study the pressure response characteristics of the cartridge electromagnetic relief valve, which offers the problems caused by low pressure response and low efficiency in hydraulic plate shearing machines.

First of all the mathematical model of the cartridge electromagnetic relief valve is deduced to analyze the influence of the relevant parameters on the system pressure response. Then experiments are conducted to research the dynamic characteristics on building and relieving pressure. Through comparison of theoretical and experimental research, the results are found.

The results show that the input flow, working pressure, diameter of adjacent damping hole, and spring stiffness of the main valve have great influence on building pressure of the system, and have no influence on relieving pressure, while diameter of damping hole of control cover plate has influence on the building and relieving pressure of the system.

The research results provide powerful theoretical support for the parametric design of the cartridge electromagnetic relief valve in the hydraulic system of plate shearing machine.

The purpose of this paper is to weigh up the effect of index-based livestock insurance (IBLI) on loan take up behavior of the pastoral households in the Borena zone of Southern Ethiopia. Although the insurance was introduced over the last decade and it appears to have promising welfare benefit, there is a lack of pragmatic evidence on its effect in leveraging the household’s future wealth for the hope of better productivity in the present.

The authors analyze household-level unique panel data collected in three rounds using descriptive statistics and the fixed effect model estimated by least squares dummy variable analysis.

The authors found that the IBLI appears to have a positive and significant effect on the loan uptake behavior of the herding households.

This increased likelihood of loan uptake suggests that the insurance can reduce the cognitive cost of loan default that would occur due to weather shocks and build-up of the household’s confidence to uptake loan. Consequently, this likelihood can promote the creditworthiness of the insured and reduce his/her fear and worry regarding the possibility of loan delinquency.

The paper is, except where otherwise stated, entirely new work.

This paper aims to study whether the upstream foundry in the original design manufacturer (ODM) supply chain will violate the commission contract and engage in the production of pirated products. Based on the conclusion, this study hopes to explain the phenomenon of pirated products in reality and provide management enlightenment for related companies.

To understand when will foundry violates the processing contract, this paper constructs a five-stage decision-making model, this study derives a model to get three situations and draw data images to describe the characteristics of decision-making by the foundry. Finally, this paper also considers some external supervision.

The results show that processing fee and other parameters (special cost, common cost, weakening factor and product difference) jointly determine the possibility of piracy by the foundry. Moreover, the external supervision mechanism has a significant effect on the piracy behavior of the foundry.

The research provides some support for real business activities, which actually involve many participants and mechanisms. Thus, it could be interesting to explore more multi-stage and complex business methods in reality.

The analysis highlights less-concerned moral hazard behaviors in the ODM supply chain. By recreating the complex interactions of participants, the conclusion shed light on how should different roles deal with their risks and take actions in a real business environment.

The biggest contribution of this study is to discuss the issue of moral hazard in the ODM supply chain. Piracy initiated by foundries may be a new type of supply chain risk and should be paid attention to.

Studies on titanium implants have shown that the mechanical properties of the parts are affected by the microstructure characteristic derived from the manufacturing process. The properties of different orientations of specimens under the same process parameters will be different, which should be considered in the application of bone implants. This paper aims to understand the influence of microstructure on micro-hardness, wear and corrosion resistance in different orientations.

The authors manufactured titanium parts and carried out micro-hardness, wear tests and electrochemical corrosion of different orientations under the same process conditions. Then, finally studied the evolution mechanism of the microstructure in different orientations and its influence mechanism on wear and corrosion mechanism.

The melting method makes the grains on the surface in XY orientation finer. The wear mechanism of XY orientation is abrasive wear, that of XZ and YZ orientations are adhesive wear. During corrosion, XY orientation forms a stable passivation film earlier. Compared with XZ and YZ orientations, XY orientation has higher micro-hardness, better wear and corrosion resistance.

In this paper, the microstructure, wear and corrosion resistance of selective laser melted parts were discussed and the differences in different orientations under the same experimental conditions were discussed. The evolution mechanism of the microstructure in different orientations and its influence mechanism on wear mechanism and corrosion mechanism was studied. The mechanical anisotropy of selective laser melted components was discussed.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.