In construction, about 80%–90% of accidents are associated with workers' unsafe acts. Nevertheless, the measurement of workers' behavior has not been actively applied in practice, due to the ...difficulties in observing workers on jobsites. In an effort to provide a robust and automated means for worker observation, this paper proposes a framework of vision-based unsafe action detection for behavior monitoring. The framework consists of (1) the identification of critical unsafe behavior, (2) the collection of relevant motion templates and site videos, (3) the 3D skeleton extraction from the videos, and (4) the detection of unsafe actions using the motion templates and skeleton models. For a proof of concept, experimental studies areundertaken to detect unsafe actions during ladder climbing (i.e., reaching far to a side) in motion datasets extracted from videos. The result indicates that the proposed framework can potentially perform well at detecting predefined unsafe actions in videos.
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•The framework allows for the automatic detection of unsafe actions in site videos.•Computer vision techniques enable estimation of body joint positions on 2D images.•Using stereo cameras, a 2D human skeleton can be reconstructed in a 3D coordinate.•Dimension reduction can improve the accuracy and efficiency of motion analysis.•With motion templates, similar actions can be detected through pattern recognition.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Over the past decades, the construction industry has been attracted to modular construction because of its benefits for reduced project scheduling and costs. However, schedule deviation risks in the ...logistics process of modular construction can derail its benefits and thus interfere with its widespread application. To address this issue, we aim to develop a digital twin framework for real-time logistics simulation, which can predict potential logistics risks and accurate module arrival time. The digital twin, a virtual replica of the physical module, updates its virtual asset based on building information modeling (BIM) in near real-time using internet of thing (IoT) sensors. Then, the virtual asset is transferred and exploited for logistics simulation in a geographic information system (GIS)-based routing application. We tested this framework in a case project where modules are manufactured at a factory, delivered to the site via a truck, and assembled onsite. The results show that potential logistical risks and accurate module arrival time can be detected via the suggested digital twin framework. This paper’s primary contribution is the development of a framework that mediates IoT, BIM, and GIS for reliable simulation which predicts potential logistics risks and accurate module delivery time. Such reliable risk prediction enables effective supply chain coordination, which can improve project performance and the widespread application of modular construction.
The use of wearable sensing devices (e.g., GPS and physiological sensors) can open a new door toward occupational safety and health management in physically demanding and hazardous construction ...(e.g., tracking worker's locations in dangerous working area and monitoring of worker's physiological status). These potential benefits cannot be achieved, however, if construction workers do not recognize the value of wearable devices as well as the details of their usage. This study thus investigates determinants for workers' adoption of wearable technology in the occupational work context. Specifically, the scope of this study is to test hypotheses regarding workers' intention to adopt two representative wearable devices for occupational safety and health, a smart vest with an embedded indoor GPS for location tracking, and a wristband-type wearable activity tracker (i.e., wristband) with physiological sensors. The research results indicate that perceived usefulness (PU), social influence (SI), and perceived privacy risk (PR) are associated with workers' intention to adopt (IA) both smart vest and wristband. Also, workers' experiences using wearable devices positively moderates the association between PU and IA of smart vest and negatively moderates the association between SI and IA of smart vest. In the work context, foremen are more likely to be influenced by PU than workers with regard to using a wristband. By considering the different functions, benefits, and challenges of each device, and by taking into account individual and job characteristics, the results of this study provide crucial insight into the process of motivating workers to adopt each device in their work, which can promote the continued and appropriate use of wearable technology in occupational safety and health management.
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•The research model on construction workers' wearable device adoption is developed.•A smart vest and wristband are selected as the representative wearable devices.•The model extends the TAM by adding four independent and two moderating variables.•The research hypotheses are tested with data collected from 120 construction workers.•This study broadens understandings of construction workers' wearable device adoption.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•Oxygen-incorporated MoS2 nanoflowers with the 1T/2H hybrid phase were synthesized.•It is the first report on 1T/2H-O-MoS2 nanoflowers by using Mo-blue solution.•The 1T/2H hybrid phase and ...incorporated oxygens enable fast electrochemical kinetics.•The 1T/2H-O-MoS2 nanoflowers show a high specific capacitance and rate capability.•The 1T/2H-O-MoS2@GF//MnO2@GF ASC exhibits excellent power and energy densities.
Molybdenum disulfide (MoS2) has shown potential as a supercapacitor electrode material, owing to its high theoretical specific capacitance and wide negative potential window, especially in neutral electrolytes. However, its practical application is hindered by low inherent electrical conductivity and narrow interlayer spacing. In this study, oxygen-incorporated MoS2 nanoflowers with 1T/2H hybrid phase were fabricated on a graphite foil substrate (1T/2H-O-MoS2@GF) from molybdenum blue solution via a facile hydrothermal process. Dispersible Mo-blue clusters, composed of polymerized structures containing numerous MoOx-type building units combined with NH4+ cations, were formed by introducing ammonium persulfate before hydrothermal synthesis; they were subsequently used as precursors of MoS2. Mo-blue clusters lead to the formation of metallic 1T-phase dominant heterostructure and incorporation of oxygens in MoS2 during the hydrothermal reaction. The 1T/2H hybrid phase formed by using Mo-blue clusters provided MoS2 with excellent stability in the 2H-phase and high electrical conductivity in the 1T-phase, simultaneously. The incorporated oxygens induced a wide interlayer spacing (9.8 Å) and improved the surface hydrophilicity of MoS2, thereby facilitating the fast diffusion of electrolyte ions. As a result, the 1T/2H-O-MoS2@GF electrode exhibited a high specific capacitance of 280 F g−1 at 1.0 A g−1 and 88% capacitance retention after 10,000 cycles at 10 A g−1. The asymmetric supercapacitor device, assembled using a 1T/2H-O-MoS2@GF negative electrode and MnO2@GF positive electrode, demonstrated superior power and energy densities of 450–18000 W kg−1 and 39.7–5.46 Wh kg−1 in a working window of 1.8 V.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
AbstractAutomated worker action recognition helps to understand the state of workers’ actions, enabling effective management of work performance in terms of productivity, safety, and health issues. A ...wristband equipped with an accelerometer (e.g., activity tracker) allows to collect the data related to workers’ hand activities without interfering with their ongoing work. Considering that many construction activities involve unique hand movements, the use of acceleration data from a wristband has great potential for action recognition of construction activities. In this context, the authors examine the feasibility of the wrist-worn accelerometer-embedded activity tracker for automated action recognition. Specifically, masonry work was conducted to collect acceleration data in a laboratory. The classification accuracy of four classifiers—the k-nearest neighbor, multilayer perceptron, decision tree, and multiclass support vector machine—was analyzed with different window sizes to investigate classification performance. It was found that the multiclass support vector machine with a 4-s window size showed the best accuracy (88.1%) to classify four different subtasks of masonry work. The present study makes noteworthy contributions to the current body of knowledge. First, the study allows for automatic construction action recognition using a single wrist-worn sensor without interfering with workers’ ongoing work, which can be widely deployed to construction sites. The use of a single sensor also greatly reduces the burden to carry multiple sensors while also reducing computational cost and memory. Second, influences associated with the variability of movement between subject and experience group were examined; thus, a consideration of data acquisition that reflects the characteristics of workers’ actions is suggested.
•The feasibility of wearable sensors to assess workers’ perceived risk is tested.•Electrodermal Activity is collected from workers in the field using wristbands.•Electrodermal Response (EDR) shows a ...potential to assess workers’ perceived risk.•Field EDR monitoring can be useful for workers’ perceived risk analysis.
Risk perception is known as a critical step in workers’ safety decision-making process. However, current approaches to assess workers’ perceived risk include surveys and interviews which are post hoc, subjective, and cumbersome to implement at construction sites. To address the issues associated with these methods, the authors propose a novel approach for the continuous and quantitative assessment of workers’ perceived risk using physiological responses acquired from wearable sensors. With this background, this study aims to investigate the potential of using physiological sensory data (e.g., electrodermal activity (EDA)) collected from off-the-shelf wristband typed sensors to understand construction workers’ perceived risk during their ongoing work. To achieve this objective, 30 h of physiological sensory data were collected from eight construction workers during their ongoing work. The results indicate that: (1) electrodermal response (EDR), which refers to short-term changes in EDA, shows significant differences between low and high-risk activities; (2) high-risk activities significantly affect workers’ EDR during their ongoing work. The main contribution of this study is to show the feasibility of using wearable sensors to understand workers’ perceived risk in construction sites continuously. Considering the complexity and dynamicity of workers’ tasks on construction sites, the development of an objective, continuous, and non-intrusive method for monitoring workers’ physiological responses is expected to contribute to a more in-depth understanding of construction workers’ perceived risk.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Recent advancements in wearable health devices equipped with biosensor systems (e.g., heart rate (HR) sensor) have provided an ample opportunity to continuously measure and understand workers' ...physical demands from construction work. Specifically, a relative measurement of physical demands, which is a percentage of HR reserve (%HRR), is convenient and useful by normalizing individual differences of HR. Since affordable HR monitoring using wearable devices (particularly, a comfortable wristband-type device: wristband hereafter) becomes available, %HRR-based physical demand measurement, which can be continuously calculated without interfering with workers' ongoing work, provides an enormous potential to protect workers' safety and health and to sustain expected productivity. This research investigates the usefulness of affordable %HRR-based physical demand measurement using a wristband from a case study of 19 workers in construction sites. The aim of the analysis is to examine the potential of this continuous measurement in capturing any significant physical demand variations, by investigating in-depth information on factors affecting physical demands (e.g., work tasks, individual and environmental factors). The results show that workers' physical demands are highly variable according to their working patterns (i.e., direct work, and indirect work including tool/equipment/material handling, traveling, and preparatory work), combined influences of work tasks, as well as individual and environmental factors (e.g., age and heat stress). These results demonstrate the need for continuous physical measurement during workers' ongoing work so that any significant high physical demands, which need to be avoided if possible, can be captured. The findings of this paper show that the continuous measurement of physical demands using a wristband provides rich information to understand, manage, and design physically demanding construction work (e.g., flexible work-rest cycle and managing demanding indirect work) by balancing workloads throughout a day and/or reducing unnecessary physical demands beyond direct work. By anticipating potential health and safety problems from excessive physical demands, as well as productivity loss before they occur, this research will have an ameliorative impact across the construction industry.
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•Worker's physical demand measurement using a wearable wristband is tested.•Usefulness of affordable %HRR-based physical demand measurement is investigated.•The need for continuous physical demand measurement of workers is demonstrated.•Workers' physical demand variations can be captured to avoid excessive demands.•Automated and continuous physical demand measurement can be enabled at the field.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In this work, we present numerical studies of fixed-stress iterative coupling for solving flow and geomechanics with propagating fractures in a porous medium. Specifically, fracture propagations are ...described by employing a phase-field approach. The extension to fixed-stress splitting to propagating phase-field fractures and systematic investigation of its properties are important enhancements to existing studies. Moreover, we provide an accurate computation of the fracture opening using level-set approaches and a subsequent finite element interpolation of the width. The latter enters as fracture permeability into the pressure diffraction problem which is crucial for fluid filled fractures. Our developments are substantiated with several numerical tests that include comparisons of computational cost for iterative coupling and nonlinear and linear iterations as well as convergence studies in space and time.
•Fixed-stress formulations for fluid-filled phase-field fractures.•Accurate fracture-width finite element computations using level-sets.•Numerical examples in 2D and 3D with spatial and temporal convergence studies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Disruptions of the cortico-striato-thalamo-cortical circuit has been implicated in both attention-deficit/hyperactivity disorder and substance use disorder. Given the high prevalence of cannabis use ...among patients with attention-deficit/hyperactivity disorder, we set out to investigate the relationship between the two in the thalamus. We analyzed resting-state functional magnetic resonance imaging data obtained from the Addiction Connectome Preprocessed Initiative Multimodal Treatment Study of Attention-Deficit/Hyperactivity Disorder database. Functional connectivity maps were extracted to compare thalamic connectivity among adults who had been diagnosed with attention-deficit/hyperactivity disorder during childhood according to whether or not they used cannabis. The study participants included 18 cannabis users and 15 cannabis non-users with childhood attention-deficit/hyperactivity disorder. Our results revealed that adults with attention-deficit/hyperactivity disorder who used cannabis (n = 18) had significantly decreased functional connectivity between the thalamus and parietal regions, which was particularly prominent in the inferior parietal areas, in comparison with those who did not use cannabis (n = 15). Left thalamic functional connectivity with the inferior parietal and middle frontal areas and right thalamic functional connectivity with the inferior parietal and superior frontal areas were increased in non-users of cannabis with attention-deficit/hyperactivity disorder compared with a local normative comparison group (n = 7). In conclusion, adults with a childhood history of attention-deficit/hyperactivity disorder who do not use cannabis often have relatively stronger thalamoparietal and thalamofrontal connectivity, which may help reduce the risk of cannabis use.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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