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Presently, 6 Degree of Freedom (6DOF) visual pose measurement methods enjoy popularity in the industrial sector. However, challenges persist in accurately measuring the visual pose of blank and rough metal casts. Therefore, this paper introduces a 6DOF pose measurement method utilizing stereo vision, and aims to the 6DOF pose measurement of blank and rough metal casts.

This paper studies the 6DOF pose measurement of metal casts from three aspects: sample enhancement of industrial objects, optimization of detector and attention mechanism. Virtual reality technology is used for sample enhancement of metal casts, which solves the problem of large-scale sample sampling in industrial application. The method also includes a novel deep learning detector that uses multiple key points on the object surface as regression objects to detect industrial objects with rotation characteristics. By introducing a mixed paths attention module, the detection accuracy of the detector and the convergence speed of the training are improved.

The experimental results show that the proposed method has a better detection effect for metal casts with smaller size scaling and rotation characteristics.

A method for 6DOF pose measurement of industrial objects is proposed, which realizes the pose measurement and grasping of metal blanks and rough machined casts by industrial robots.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

This study aims to conduct a thorough literature review to map current studies on international marketing capabilities (IMCs) applying dynamic capabilities view (DCV). The aim of this study is to increase the chances for more conceptual and terminological rigor in future research in this particular research area.

This is a systematic literature review following the established review process of reviews in leading (international) marketing journals. A multilevel analytical approach was adopted, combining inductive coding with deductive coding and following the logic of antecedents-phenomena-consequences.

Synthesis of 20 rigorously selected previous empirical studies on IMCs applying DCV reveals that academic interest in these capabilities is well justified and growing and there are some well researched antecedents to focal capabilities (e.g. inter-organizational capabilities, outside-in market orientation) as well as their prevalent consequences (e.g. export and innovation performance). There is little knowledge of moderators to these links, especially with regard to consequences. This review illustrates that the current research lacks consistency in how key constructs are defined and measured, provides the guide to future conceptualization and measurement of so-called International Dynamic Marketing Capabilities (IDMCs) and proposes some concrete research directions.

The authors extend prior research in the investigated topic by critically evaluating prior works, providing improved conceptualization of IDMCs as well as concrete research agenda for IDMCs structured along recommendations for Theory, Context and Methods (TCM framework).

This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.

The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.

The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.

The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

Amidst the complicated nature of the UAE’s facilities management (FM) industry, the need to recalibrate the existing performance measurement (PM) system measures and criteria has been resonating to ensure their ability to capture the FM industry trends and dynamics, thus enhancing organizational excellence. Therefore, this research aimed to propose a specific PM tool to the country’s FM industry to accurately assess performance and establish strategic enhancements.

The study reviewed literature on the available PM systems to gather the available measures, which were presented to a focus group of seven participants, who were purposively selected based on their expertise in FM and PM implementation in the UAE to adjust them and add ones relevant to the UAE’s FM industry.

The focus group conducted various changes, from retaining certain measures and criteria, renaming them to simplify or make them more representative of the industry, ranking them based on their importance to limit their numbers, to finally categorizing them as enablers or results. Consequently, the final proposed tool was composed of nine dimensions with 51 measures as performance enablers and three dimensions with 11 measures as performance results. Seven measures were added by the experts, who highlighted their increasing popularity in the UAE’s FM industry.

Through addressing the critical void in literature, this paper develops a specific PM tool aligning with the intricacy of the UAE’s FM industry, thus providing proactive contribution to the industry’s effective and sustainable growth.

In a coaxial ultrasonic flow sensor (UFS), wall thickness is a vital parameter of the measurement tube, especially those with small inner diameters. The paper aims to investigate the influence of wall thickness on the transient signal characteristics in an UFS.

First, the problem was researched experimentally using a series of measurement tubes with different wall thicknesses. Second, a finite element method–based model in the time domain was established to validate the experimental results and further discussion. Finally, the plane wave assumption and oblique incident theory were used to analyze the wave propagation in the tube, and an idea of wave packet superposition was proposed to reveal the mechanism of the influence of wall thickness.

Both experimental and simulated results showed that the signal amplitude decreased periodically as the wall thickness increased, and the corresponding waveform varied dramatically. Based on the analysis of wave propagation in the measurement tube, a formula concerning the phase difference between wave packets was derived to characterize the signal variation.

This paper provides a new and explicit explanation of the influence of wall thickness on the transient signal in a co-axial UFS. Both experimental and simulated results were presented, and the mechanism was clearly described.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.