Physiological condition monitoring of construction workers

Monitoring of workers' physiological conditions can potentially enhance construction workforce productivity, safety, and well-being. Recently, Physiological Status Monitors (PSMs) were validated as an accurate technology to assess physiological conditions during typical sport science and medicine testing procedures (e.g., treadmill and cycle ergometer protocols). However, sport science and medicine testing procedures cannot simulate routine construction worker movements in a comprehensive manner. Thus, this paper investigated the validity of two PSMs by comparing their measurements with gold standard laboratory instruments' measurements at rest and during dynamic activities resembling construction workforce's routine activities. Two physiological parameters such as heart rate and breathing rate were considered. Ten apparently healthy subjects participated in the study. One of the PSMs proved to be a viable technology in assessing construction workers' heart rate (correlation coefficient ≥ 0.74; percentage of differences within ± 11 bpm ≥ 84.8%).     

Feature extraction and soft computing methods for aerospace structure defect classification

This study concerns the effectiveness of several techniques and methods of signals processing and data interpretation for the diagnosis of aerospace structure defects. This is done by applying different known feature extraction methods, in addition to a new CBIR-based one; and some soft computing techniques including a recent HPC parallel implementation of the U-BRAIN learning algorithm on Non Destructive Testing data. The performance of the resulting detection systems are measured in terms of Accuracy, Sensitivity, Specificity, and Precision. Their effectiveness is evaluated by the Matthews correlation, the Area Under Curve (AUC), and the F-Measure. Several experiments are performed on a standard dataset of eddy current signal samples for aircraft structures. Our experimental results evidence that the key to a successful defect classifier is the feature extraction method – namely the novel CBIR-based one outperforms all the competitors – and they illustrate the greater effectiveness of the U-BRAIN algorithm and the MLP neural network among the soft computing methods in this kind of application.     

Imparting strength into nanofiberous yarn by adhesive bonding

Low strength is one of the main disadvantages of nanofibrous structures in some applications such as suture yarns. To overcome this matter, in the present research, a novel method was applied to improve the tensile properties of nanofiber yarns. For this purpose, nanofibers and particles of polyvinyl acetate (PVAc) were added as a hot melt adhesive to nanofiber yarns in order to initiate adhesive bonding between nanofibers by two approaches. In the first one, Nylon 66/ PVAc hybrid nanofiber yarn was produced in opposite charged nozzles set up. In another approach, PVAc particles were electrosprayed through one of the nozzles while nylon 66 nanofibers were producing through another one. Afterward, thermal treatment was carried out for 78 seconds on samples in different temperatures. The results indicate that tensile strength was improved up to 1.97 and 1.7 times in comparison to nylon 66 nanofiberous yarn by adding PVAc nanofibers and particles, respectively. FTIR analysis was also carried out to assess the hybrid sample composition after heat treatment.     

Use of tree pruning wastes for manufacturing of wood reinforced cement composites

Tree pruning wastes from six woody species, namely Acacia salicina, Conocarpus erectus, Ficus altissima, Leucaena glauca, Pithecellobium dulce and Tamarix aphylla, were used to manufacture high-quality wood reinforced cement composites (WRCCs). Hydrations experiments were conducted to screen the compatibility of the selected tree pruning wastes with cement. Additionally, various particle pretreatments and chemical additives were applied to enhance the compatibility of wood with cement. The best treatment for each species was selected and used to manufacture the WRCCs. The panels were produced under specific manufacturing variables and the mechanical properties and dimensional stability of the panels were determined. The results indicated that both board density and wood/cement (W/C) ratio had significant effects on the properties of WRCCs. With few exceptions, a W/C ratio of 1/2 and either 1200 kg m⁻³ or 1300 kg m⁻³ produced the optimal strength properties. The tree pruning wastes are suitable for use as raw materials in the manufacturing of WRCCs after pre-treatment of the wood particles with either cold or hot water and with addition 3% of CaCl₂, Al₂(SO₄)₃ or MgCl₂. Therefore, these wastes could be used as an alternative wood source for WRCCs.     

A population-based iterated greedy algorithm for the delimitation and zoning of rural settlements

In this paper we present a Population-Based Iterated Greedy (PBIG) algorithm for delimiting and zoning rural settlements. Each cadastral plots is allocated to a category (traditional–historical, common or none) considering restrictions such as the characteristics of the existing edifications and the building density. Since the problem has multiple solutions, heuristic search algorithms, as PBIG, are a good strategy to solve it. Besides the resolution of the problem according to the requirements of the laws, our work explores also new methods of delimitation. The comparison between both types of solutions can help to improve the current methodology. The algorithm, implemented using the Java programming language and integrated into an open-source GIS software, has been tested in rural settlements with different morphological characteristics, providing adjustable solutions to the specific needs of each rural settlement.     

Distributed and interoperable simulation for comprehensive disaster response management in facilities

Disaster-related simulations can be helpful for conducting various analysis on damage evaluations and response operations in damaged facilities. However, no single simulation can solve all the functional needs for complex disaster situations due to diverse disasters, damage types, and response efforts. To address these issues, the authors have developed a distributed simulation platform for a comprehensive analysis of facility damage and response operations, which can be flexibly applied to diverse disaster situations. The High Level Architecture is adopted to synchronize different federates such as simulation models and incoming data streams within an interoperable simulation environment. The developed simulation platform includes five different disaster-related federates such as the Fire Dynamics Simulator, USGS earthquake data feeds, OpenSees structure response simulation, evacuation simulation, and restoration simulation. The accuracy of interactions among different federates was confirmed with the case simulations of a facility fire evacuation and an earthquake restoration situation. The developed platform provides a flexible and interoperable distributed simulation environment for comprehensive disaster response management of unexpected disaster situations while promoting reusability and future extendibility of existing and newly-added disaster-related simulations.     

Luminous tiles: A new building device for smart architectures and applications

Advanced building materials are nowadays an active research domain. The integration of traditional materials and technologies in the field of electronics, photonics and computer science are leading to a new class of smart components that provide advanced functionalities and enable original applications.The LUMENTILE H2020 EU funded Project aims at the integration of existing and state-of-the-art technologies in the domain of large area electronic circuits, LED based lighting, embedded systems and communication. These technologies are blended with advancements in the manufacturing of ceramic tiles to obtain a new building component that can be managed as a common tile, while providing the possibility to self-illuminate and to sense the neighbor environment by means of dedicated sensors. The applications of these new material and technologies include indoor and outdoor architectural design, smart environments (also targeting improved safety and security issues), smart and high-efficiency lighting and art installations. State-of-the-art advancements are expected in the field of large area circuits and successful integration of heterogeneous materials, mainly focusing on ceramics and electronics.     

Testing of “Global Young's Modulus E” on a rehabilitated masonry bell tower in Venice

This paper shows the effectiveness of the techniques chosen for the rehabilitation of the historic “Sant'Andrea” masonry bell-tower in Venice. The achieved rehabilitation projects based on the indenting technique consisting in removing and replacing bricks in bad conditions, and on the isolation of the bells at the belfry quote, respect all the constraints represented by the aesthetic and structural features of the building. Moreover, the experimental analyses used to define the existing state of the structure are described in detail. The tower is also an interesting case study for the validation of the proposed method to determine the global young's modulus in a rehabilitated masonry bell tower. Rayleigh's method, using as input data the natural frequency obtained with an experimental accurate validation like the dynamic identification, was utilized to determine the global Young's modulus.     

A feasibility study of using smartphone built-in accelerometers to detect fall portents

Fall accidents contribute to nearly half of all fatalities in the construction industry in Taiwan. Detecting fall portents using a smartphone, which many people carry daily, may help reduce fall accidents if the accuracy is acceptable. We designed two experiments with three algorithms to evaluate how well a smartphone can detect both falls and fall portents in a tiling operation scenario. The experiments show that work-related motions barely affected the detection of falls, and the result had a sensitivity and specificity of 100% and 96.1%, respectively. However, for detecting portents, the work-related motions had quite a large impact on the gyroscope-based algorithm, which demonstrated an accuracy rate of only 4.3%, but had only limited impact on the accelerometer-based algorithm, which still show acceptable accuracy rates of 73.5% and 88.5%. We conclude that using a smartphone to detect falls and portents in a construction site is feasible.     

Properties of recycled aggregate concrete made with recycled aggregates with different amounts of old adhered mortars

This paper presents the experimental results of a study on comparing the difference in properties of recycled aggregates (RAs) with varying amounts of old adhered mortar obtained from different sources and evaluating the influence of the different RAs on the mechanical and durability properties of recycled aggregate concrete (RAC). Four concrete mixes (one with natural aggregate and three others with recycled aggregates) with 28 day target compressive strength varying from 30 MPa to 80 MPa are designed by using each RA to fully replace NA. The properties of RAC are also modeled by using the artificial neural networks (ANN) method.The experimental results show that the performance of RAs from different sources varied greatly and RA of good quality can be used to produce high strength concrete with hardened properties comparable to those of the corresponding natural aggregate concrete (NAC). The comparison of the predicted results based on the ANN models and the experimental values indicated that the ANN method could be used to evaluate the properties of RAC made with RAs derived from different sources. This will facilitate the wider application of RA in concrete.