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Construction is a risky industry. Therefore, organizations are seeking ways towards improving their safety performance. Among these, the integration of technology into health and safety leads to enhanced safety performance. Considering the benefits observed in using technology in safety, this study aims to explore digital technologies' use and potential benefits in construction health and safety.

An extensive bibliometrics analysis was conducted to reveal which technologies are at the forefront of others and how these technologies are used in safety operations. The study used two different databases, Web of Science (WoS) and Scopus, to scan the literature in a systemic way.

The systemic analysis of several studies showed that the digital technologies use in construction are still a niche theme and need more assessment. The study provided that sensors and wireless technology are of utmost importance in terms of construction safety. Moreover, the study revealed that artificial intelligence, machine learning, building information modeling (BIM), sensors and wireless technologies are trending technologies compared to unmanned aerial vehicles, serious games and the Internet of things. On the other hand, the study provided that the technologies are even more effective with integrated use like in the case of BIM and sensors or unmanned aerial vehicles. It was observed that the use of these technologies varies with respect to studies conducted in different countries. The study further revealed that the studies conducted on this topic are mostly published in some selected journals and international collaboration efforts in terms of researching the topic have been observed.

This study provides an extensive analysis of WoS and Scopus databases and an in-depth review of the use of digital technologies in construction safety. The review consists of the most recent studies showing the benefits of using such technologies and showing the usage on a systemic level from which both scientists and practitioners can benefit to devise new strategies in technology usage.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.

The purpose of this paper is to enhance the network lifetime of WSN. In wireless sensor network (WSN), the sensor nodes are widely deployed in a terrestrial environment to sense and evaluate the physical circumstances. The sensor node near to the sink will deplete more energy faster than other nodes; hence, there arises an energy hole and network partitioning problem in stationary sink-based WSN. Even though many mobile sink-based WSN is formulated to mitigate energy hole, inappropriate placement of sink leads to packet drop and affect the network lifetime of WSN. Therefore, it is necessary to have an efficient sink mobility approach to prevent an aforesaid problem.

In this paper, zone-based sink mobility (ZBSM) approach is proposed in which the zone formation along with controlled sink mobility is preferred for energy hole mitigation and optimal sink node placement. In ZBSM, the sink decides to move toward strongly loaded zone (SLZ) for avoiding network partitioning problems where the selection of SLZ can be carried out by using Fuzzy Logic.

The performance results confirm that the proposed scheme reduces energy consumption as well as enhances the network lifetime compared with an existing scheme.

A new optimal sink node placement is proposed to enhance the network lifetime and packet delivery ratio of WSN.

Presently there exists no way to directly measure strain at high temperatures in engine components such as the combustion chamber, exhaust nozzle, propellant lines, and turbine blades and shaft. The purpose of this paper is to address this issue.

Thermomechanical fatigue (TMF) prediction, which is a critical element for a blade design, is a strong function of the temperature and strain profiles. Major uncertainties arise from the inability of current instrumentation to measure temperature and strain at critical locations. This prevents the structural designer from optimizing the blade design for high temperature environments, which is a significantly challenging problem in engine design.

Being able to directly measure strains in different high temperature zones would deeply enhance the effectiveness of aircraft propulsion systems for fatigue damage assessment and life prediction. The state of the art for harsh environment, high temperature sensors has improved considerably over the past few years.

This paper lays down specifications for high temperature sensors and provides a technological assessment of these new sensing technologies. The paper also reviews recent advances made in harsh environment sensing systems and takes a peek at the future of such technologies.

As one of the tomographic imaging techniques, electrical capacitance tomography (ECT) is widely used in many industrial applications. While most ECT sensors have electrodes placed around a cylindrical chamber, the planar ECT sensor has been investigated for depth and defect detection. However, the planar ECT sensor has limited height and depth sensing capability due to its single-sided assessment with the use of only a single-plane design. The purpose of this paper is to investigate a dual-plane miniature planar 3D ECT sensor design using the 3 × 3 matrix electrode array.

The sensitivity map of dual-plane miniature planar 3D ECT sensor was analysed using 3D visualisation, the singular value decomposition and the axial resolution analysis. Then, the sensor was fabricated for performance analysis based on 3D imaging experiments.

The sensitivity map analysis showed that the dual-plane miniature planar 3D ECT sensor has enhanced the height sensing capability, and it is less ill-posed in 3D image reconstruction. The dual-plane miniature planar 3D ECT sensor showed a 28% improvement in reconstructed 3D image quality as compared to the single-plane sensor set-up.

The 3 × 3 matrix electrode array has been proposed to use only the necessary electrode pair combinations for image reconstruction. Besides, the increase in number of electrodes from the dual-plane sensor setup improved the height reconstruction of the test sample.

Drawing on image theory, the authors investigate how and when cross-cultural experience cultivates two core entrepreneurial sensing capabilities: opportunity recognition and creative behavior.

The authors develop and test a second-stage moderated mediation model across two studies. Study 1 consists of a sample of prospective entrepreneurs from the UK using perceptual scale measures (n = 153). Building on this, core findings are replicated using task-based measures on a sample of US participants (n = 342).

Results show that cross-cultural experience is positively related to both entrepreneurial sensing capabilities through the mediating role of self-image fluidity. No support is found for the moderating role of regulatory focus orientations.

These findings contribute to the burgeoning literature on multicultural experience and initiating skills in nascent venturing by providing insight on the mechanisms and boundary conditions relevant for entrepreneurial capabilities to emerge.

The results reinforce the need for educators, policymakers, and entrepreneurs to facilitate and encourage opportunities for cross-cultural and overseas experiences as they are influential for stimulating entrepreneurial skills.

Positive linkages between international mobility and entrepreneurial activity are of continued interest, yet individual-level mechanisms that explain this have been limited. The authors find that exposure to foreign cultures is potent for entrepreneurship as it can stimulate flexibility and exploration of the self-image and break frames of reference. This fosters greater tendencies for opportunity recognition and creative behaviors.

The purpose of this paper is to present an implementation of ultrasonic tomography simulation to investigate the laminar flow of stratified liquid between water and oil.

The velocity of ultrasonic waves varies in water, oil, and different composition of water and oil. The composition of water and oil can be determined from the measurement of this propagation time. Sixteen pairs of ultrasonic sensors are mounted non‐invasively around the periphery of an acrylic pipe. The grease is used as the coupling material to mount these ultrasonic sensors. Different compositions of water and oil are used and the propagation times of the ultrasonic waves through the medium are measured. The composition of the water and oil of the flow is determined from the reconstructed images.

The paper finds that information about the distribution of the components within the sensing zone is obtained from the sensors' measurements. These measurements are then used to reconstruct the cross‐sectional image which can be analyzed to provide information, such as concentration of the flow components, the flow condition, velocity, mass flow rate, and identification of the distribution of mixing zones in stirred reactors and interface measurement in complex separation processes. The image can also be analyzed quantitatively for subsequent use to improve process control or develop models to describe individual process.

The paper shows that industries which may benefit from this technique could be the raw material processing industry, large‐scale and intermediate chemical production, and food biotechnology.

This paper aims to give an overview about the state of the art and novel technologies used in gas sensing. It also discusses the miniaturization potential of some of these technologies in a comparative way.

In this article, the authors state the most of the methods used in gas sensing discuss their advantages and disadvantages and at last the authors discuss the ability of their miniaturization comparing between them in terms of their sensing parameters like sensitivity, selectivity and cost.

In this article, the authors will try to cover most of the important methods used in gas sensing and their recent developments. The authors will also discuss their miniaturization potential trying to find the best candidate among the different types for the aim of miniaturization.

In this article, the authors will review most of the methods used in gas sensing and discuss their miniaturization potential delimiting the research to a certain type of technology or application.

The purpose of this study is to introduce a new type of sensor which uses microwave metamaterials and direct-coupled split-ring resonators (DC-SRRs) to measure the dielectric properties of solid materials in real time. The sensor uses a transmission line with a bridge-type structure to measure the differential frequency, which can be used to calculate the dielectric constant of the material being tested. The study aims to establish an empirical relationship between the dielectric properties of the material and the frequency measurements obtained from the sensor.

In the proposed design, the opposite arm of the bridge transmission line is loaded by DC-SRRs, and the distance between DC-SRRs is optimized to minimize the mutual coupling between them. The DC-SRRs are loaded with the material under test (MUT) to perform differential permittivity sensing. When identical MUT is placed on both resonators, a single transmission zero (notch) is obtained, but non-identical MUTs exhibit two split notches. For the design of differential sensors and comparators based on symmetry disruption, frequency splitting is highly useful.

The proposed structure is demonstrated using electromagnetic simulation, and a prototype of the proposed sensor is fabricated and experimentally validated to prove the differential sensing principle. Here, the sensor is analyzed for sensitivity by using different MUTs with relative permittivity ranges from 1.006 to 10 and with a fixed dimension of 9 mm × 10 mm ×1.2 mm. It shows a very good average frequency deviation per unit change in permittivity of the MUTs, which is around 743 MHz, and it also exhibits a very high average relative sensitivity and quality factor of around 11.5% and 323, respectively.

The proposed sensor can be used for differential characterization of permittivity and also as a comparator to test the purity of solid dielectric samples. This sensor most importantly strengthens robustness to environmental conditions that cause cross-sensitivity or miscalibration. The accuracy of the measurement is enhanced as compared to conventional single- and double-notch metamaterial-based sensors.