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Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

Parallel processing technology was applied to accelerate the calculation speed of the water quality forecasting model. The parallel algorithm proposed was based on the message-passing interface (MPI). It mainly aims at enhancing the computation speed of the water quality forecasting model of Jiaozhou Bay, and decomposes the material transport issue into many sub-duties. The model was run in a MPI message cluster system. The result indicates that, by using this method, the computation efficiency for solving material transportation module is increased by approximately more than 60%.

Numerous smog events have occurred in recent years in China. Their hazards in mining and industrial cities are more serious than clear days. The samples were collected in the mining and industrial city of Handan. During the smog episode, PM₁₀ and PM_2.5 concentrations reach up to 980 μg/m³ and 660 μg/m³, respectively. Under SEM (scanning electron microscope) analysis, the particles consist of soot, fly ash and minerals, which could be from coal mines, power plants, steel mills and auto exhausts. Compared with the samples collected on a clear day, the increased PM₁₀ particles are mainly composed of organic matter, especially aromatic compounds. The Pb content in PM₁₀ of the smog day reaches 507.4 ng/m³ and could be caused by vehicle emissions.

This paper examines the association between the quality of management schools and sustainability and investigates whether ethical behavior of firms moderates relationship between the quality of management schools and sustainability.

The sample consists of 500 country-year observations over the period of 2014-2017. Sustainability is collected from the Global Sustainable Competiveness Index reports for 2014, 2015, 2016 and 2017, while the quality of management schools and ethical behavior of firms are collected from the Global Competiveness Report for the same years.

The findings of this study suggest that the quality of management schools is positively associated with sustainability. When testing for the moderating effect of ethical behavior of firms on the association between quality of management schools and sustainability, results show that the positive association becomes positive and more significant for countries where firms operate with high ethical behaviors, while the association becomes insignificant for settings where firms operate with low ethical behaviors. Findings also show that the quality of management schools and ethical behavior of firms play a complimentary role in improving sustainability.

The findings emphasize the role played by business schools and business ethics in improving sustainability. These results may have policy implications for governments aiming to improve sustainability by emphasizing on education for sustainable development in management schools’ 2019 programs enforcing standards dealing with business ethics and controlling firms’ 2019 compliance with them.

The findings of this study highlight the importance of education, as proxied by the quality of management schools, in the development of sustainable societies and economic systems. To the best of the author's knowledge, this is the first study that tries to empirically link business schools programs to sustainability efforts and how business ethics may affect this association.

Various networked organizational forms already exist in the market today, however, all of them share the same problem – lack of fast and objective procedures for partners’ selection when addressing a particular project. The purpose of this paper is to solve such problems by offering an alternative to the existing global market layout, dominated by large corporations.

This research belongs to the category “fuzzy decision making and multi-attributive decision making,” since it is using methodologies such as the analytical hierarchy process (AHP), the fuzzy-AHP approach, and the Technique for Order of Preference by Similarity to Ideal Solution.

The authors defend that appropriate partner selection is a vital success factor in any collaboration.

The authors have designed a sustainable partner network solution for the field of machinery. Nevertheless, the proposed approach is adaptable to other fields also, whereas the focal player or project owner selects the best partner based on a set of criteria.

The paper includes a feasibility case study for the approval of findings, where several small and medium enterprises (SMEs) from the field of machining collaborate to achieve a common goal.

The research focuses on production enterprises (especially for SMEs) and is intended to improve their competitiveness. Small enterprises combining into a network makes it possible to compete with large corporations and helps to decrease project initiation time and project realization risks.

The main idea is to collect information about the available resources of SMEs into a new temporary entity and to utilize those resources for the realization of the tasks of a particularly large project, while meeting customer expectations. In addition, this work also suggests a calculation tool for faster partner evaluation (assessment) based on various criteria for each particular project.

This paper investigates customer knowledge management activities of Taiwan’s plastic industries. The results demonstrate that the bulk of customer knowledge comes from data related to customer purchase orders and complaints. Furthermore, marketing, production, and research and development are the main departments that developed and reuse customer knowledge. The benefits derived from knowledge management for enterprises do not vary with the position of the vendor on the business scope. In addition, the benefits derived by customers from knowledge management are directly related to the benefits gained by the five major business functions, while the benefits derived from the customer knowledge management are also directly related to customer satisfaction. Summarizing the above results, an Acquisition‐Development‐Reuse (ADR) model is proposed and can provide the enterprises with a systematic reference model when the business attempts to construct a customer knowledge management system.

This paper aims to propose a method of the safety boundary protection for unmanned aerial vehicles (UAVs) in the icing conditions.

Forty icing conditions were sampled in the continuous maximum icing conditions in the Appendix C of the Federal Aviation Regulation Part 25. Icing numerical simulations were carried out for the 40 samples and the anti-icing thermal load distribution in full evaporation mode were obtained. Based on the obtained anti-icing thermal load distribution, the surrogated model of the anti-icing thermal load distribution was established with proper orthogonal decomposition and Kriging interpolation. The weather research and forecasting (WRF) model was used for meteorological simulations to obtain the icing meteorological conditions in the target area. With the obtained icing conditions and surrogated model, the anti-icing thermal load distribution in the target area and the variation with time can be determined. According to the energy supply of the UAVs, the graded safety boundaries can be obtained.

The surrogated model can predict the effects of five factors, such as temperature, velocity, pressure, median volume diameter (MVD) and liquid water content (LWC), on the anti-icing thermal load quickly and accurately. The simulated results of the WRF mode agree well with the observed results. The method can obtain the graded safety boundaries.

The method has a reference significant for the safety of the UAVs with the limited energy supply in the icing conditions.

To fabricate a selective laser melting (SLM)-processed AlSi10Mg part with almost full density and free of any apparent pores, this study aims to investigate the effect of ambient argon pressure and laser scanning speed on the particles splash during the AlSi10Mg powder bed laser melting.

Based on the discrete element method (DEM), a 3D model of random distribution of powder particles was established, and the 3D free surface of SLM forming process was dynamically tracked by the volume of fluid, where a Gaussian laser beam acts as the energy source melting the powder bed. Through the numerical simulation and process experimental research, the effect of the applied laser power and scanning speed on the operating laser melting temperature was studied.

The process stability has a fundamental role in the porosity formation, which is process-dependent. The effect of the processing conditions on the process stability and the resultant forming defects were clarified.

The results shows that the pores were the main defects present in the SLM-processed AlSi10Mg sample, which decreases the densification level of the sample.

The optimal processing parameters (argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm ) applied during laser melting can improve the quality of selective laser melting of AlSi10Mg,

It can provide a technological support for 3D printing.

Based on the analysis of the pore and balling formation mechanisms, the optimal processing parameters have been obtained, which were argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm. Then, a near-fully dense sample free of any apparent pores on the cross-sectional microstructure was produced by SLM, wherein the relative density of the as-built samples is larger than 97.5%.

Food service establishments and online food delivery companies use a revenue share model based on a commission rate. Because of the asymmetry of bargaining power, many food service establishments are vulnerable to a high commission rate. What is missing in the ongoing discussion about the revenue share model is the perspective of food consumers, who are the third party in the multi-sided market.

Within a willingness-to-pay (WTP) framework, we study if food consumers have preferences for the commission rate charged by food delivery companies to food service establishments. With 456 random consumers in the United States, we conduct a controlled experiment in which information is used as treatment in two groups. In the first group, the provided information only relates to the revenue share model (i.e. economic). In the second group, participants also received information about price control initiatives (i.e. economic and political).

Based on WTP-space mixed logit model results, there is a significant effect of information on preferences for the commission rate. While participants in the control group exhibited no aversion to the commission rate, participants who received treatment had a significant and negative WTP. The magnitude of the effect is estimated at -$1.08 for participants in the first treatment and -$2.28 for participants in the second treatment.

To date there is no applied research on the preferences of consumers in the online food order and delivery industry with respect to upstream conditions (i.e. commission rates).

This paper aims to examine the role of trust in colleagues and its relationships with the factors of the theory of reasoned action (TRA). Specifically, this study examines the relationships among perceived social pressure about knowledge sharing, attitude toward knowledge sharing, behavioural intent to share knowledge, trust in colleagues and knowledge-sharing behaviour.

The methodology adopted was a questionnaire survey of employees working in 34 member institutions of the Singapore Association for Private Education (SAPE). These institutions form the entire member list of the SAPE as of 2020. A total of 297 employees completed a self-administered and anonymous survey using a cross-sectional design. Multiple linear regression was used to test the conceptual framework.

On the mediation effects, full mediation was found to affect attitude toward knowledge sharing on knowledge-sharing behaviour, and partial mediation was found to affect perceived social pressure on knowledge-sharing behaviour. On the moderation effects, trust in colleagues moderates both perceived social pressure and knowledge-sharing behaviour and attitude toward knowledge sharing and knowledge-sharing behaviour positively. Specifically, as the level of trust in colleagues increases, the impact of direct relationships also increases.

Data for the current study were obtained at a single point in time and self-reported. The findings may be biased because of common method variance. Furthermore, this study was conducted in a specific industry in Singapore, i.e. the private education institutions, which limits the generalisability of the research.

The results of this study indicate that managers need to encourage a higher level of trust between employees. Policies and processes could be enacted to promote building quality and trusting relationships between employees.

This study contributes to knowledge-sharing behaviour by integrating the role of trust with the TRA. This study extends the conceptual model of the TRA by providing a new theoretical perspective that takes into account the position of trust in knowledge sharing.