Search results

The application of smart contract can greatly reduce transaction costs and improve transaction efficiency. The existing smart contract are expensive, single application scenario and inefficient. This paper aims to propose a new smart contract model to solve these problems.

By investigating the research history, models and platforms, this paper summarizes the shortcomings of existing smart contracts. Based on the content and architecture of traditional contract, a smart contract model with wider application scope is designed.

In this paper, several models are used to describe the operation mechanism of smart contracts. To facilitate computer execution, a decomposition method is proposed, which divides smart contracts into several sub-contracts. Then, the advantages and deployment methods of smart contract are discussed. On this basis, a specific example is given to illustrate how the application of smart contract will change our life.

Smart contract is gradually applied to more fields. In this paper, the structure and operation mechanism of smart contract system in reality are given, which will be beneficial to the application of smart contract to more complex systems.

The purpose of this study is to answer whether and how supervisor–subordinate instrumental or expressive ties based on enterprise social media (ESM) might enhance employee performance.

Drawing on social exchange theory, this study developed a theoretical model to explore the influencing mechanism of different supervisor–subordinate ties based on ESM on employee job performance. The model was empirically tested through 219 ESM users.

The results revealed that supervisor–subordinate instrumental ties based on ESM play a positive role in employee job performance, while supervisor–subordinate expressive ties based on ESM are not significantly related to employee job performance. Supervisor–subordinate instrumental ties and expressive ties based on ESM can positively influence employee job performance through the mediating effect of organizational trust. Besides, perceived performance climate can weaken the relation of organizational trust to job performance, and then weaken the indirect relations via the mediating of organizational trust.

Our findings advance the understanding of ESM use through various underlying mechanisms and have the potential of guiding organizations to fine-tune their social media usage strategies.

The purpose of this study is to explore the relationship between information overload and employees' workplace anxiety in the context of enterprise social media (ESM).

This study built a theoretical model to analyze the relationships among employees' perceptions of information overload on ESM, supervisor-subordinate instrumental and expressive ties on ESM and workplace anxiety. PLS-SEM was used to test the model through 219 questionnaires collected online.

The results revealed that information overload on ESM plays a positive role in employees' workplace anxiety. Supervisor-subordinate instrumental ties based on ESM can weaken the relationship between information overload and employees' workplace anxiety, but expressive ties can strengthen the positive relationship between information overload and workplace anxiety.

Little is known about whether information overload on ESM will affect employees' workplace anxiety and how leaders can mitigate this effect through ESM. Hence, this study developed a theoretical model and conducted an empirical study to open up a research opportunity to examine the relationships among information overload on ESM, supervisor-subordinate instrumental and expressive ties on ESM and employees' workplace anxiety. The study also has the potential to guide organizations in fine-tuning their social media usage strategies.

An accurate and fast dynamic analysis innovative approach for vehicle parts is provided for engineering practice.

This paper presents an innovative dynamic analysis approach for vehicle parts based on parallel optimization algorithm with CUDA.

This project is supported by the National Science Foundation of China (No. 51805076, No. U1708255 and No. 51775093), the Fundamental Research Funds for the Central Universities (No. N170503011) and the Natural Science Foundation of Liaoning Province, China (No. 20180551058).

This paper presents an innovative approach for vehicle parts using parallel optimization algorithm based on CUDA, which can improve the computing accuracy and speed effectively.

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

As an important connecting component, the reliability of aluminium alloy welded joints influences the whole structural effectiveness and stability of equipment. The purpose of this paper is to propose a novel reliability estimation approach to the welded joints based on time-transformed Wiener process with automatic image measurement of crack growth. The crack length information of the welded joints is incorporated into reliability analysis to reflect the product time-varying characteristics.

The proposed approach is superior to other crack growth estimations in that it innovatively introduce a non-contact and flexible photogrammetry technique.First, on-line crack growth images of aluminium alloy welded joints are acquired by the designed monitor system. Second, crack length is calculated with image measurement, then the crack growth data during the manufacturing process is prepared. Finally, a time-transformed Wiener process is used to modeling the degradation, and reliability estimation is carried out with Wiener model. The approach has been validated on five 7075-T7351 welded joint samples.

The method has a twofold task: first, the extraction of crack length growth data by a sequence of image processing. The main step is to model the crack skeleton with crack skeleton tree, and remove it edges to calculate the length of crack; second, the prediction of crack growth and reliability estimation.

The limitation of proposed method should not be ignored. The pixel/mm scale should be calibrated in advance that means once we have built the monitor system, the relative position of the CCD camera and the surveyed crack cannot change anymore. It has reduced the flexibility. To improve this, we can obtain binocular vision in crack image measurement. The 3-D measurements could solve calibration problem and provide more information, such as the depth and the orientation of crack to research. Therefore, future work can be centered on the improvement of monitor system and measurement precision.

In the paper a novel method to estimate reliability of crack growth from welded joint based on image measurement has been presented. This method could be widely applied in different filed of manufacturing systems, reliability engineering and structural analysis.

This paper aims to address the collision problem between robot and the external environment (including human) in an unstructured situation. A new collision detection and torque optimization control method is proposed.

Firstly, when the collision appears, a second-order Taylor observer is proposed to estimate the residual value. Secondly, the band-pass filter is used to reduce the high-frequency torque modeling dynamic uncertainty. With the estimate information and the torque value, a variable impedance control approach is then synthesized to guarantee that the collision is avoided or the collision will be terminated with different contact models and positions. However, in terms of adaptive linear force error, the variation of the thickness of the boundary layer is controlled by the new proximity function.

Finally, the experimental results show the better performance of the proposed control method, realizing the force control during the collision process.

Origin approach and origin experiment.

The wear of an abrasive single-crystal diamond (SCD) grit affects the machining quality of the sapphire wafer. This paper aims to investigate the influence of crystallographic orientation on the wear characteristics of SCD grit scratching on sapphire.

The wear characteristics of two SCD grits (SCD100 and SCD111) with different crystallographic orientations were systematically investigated. The wear mechanism involved in the scratching process was explored. The wear morphology, scratching forces and friction coefficient during the scratching process were measured and analyzed.

The experiment results show that the wear progress of the two SCD grits is obviously different. The wear resistance of SCD111 grit is greater than that of SCD100 grit in normal wear stage. However, the SCD100 grit could remove more sapphire material than SCD111 grit. The SCD grits mainly sustain extrusion stress and shear stress during scratching on sapphire. The crystallographic orientation of SCD grits plays a significant role in the wear progress during scratching on sapphire.

The results of the experimental studies could provide a theoretical foundation for improving the fabrication of abrasive diamond tools.

Project risk management (PRM) and human resource management (HRM) are the two critical success factors (CSFs) for international project management. This paper aims to correlate these two CSFs, identify the human resource (HR) barriers, develop a hybrid model for risk management and develop strategies to overcome the HR barriers to effective risk management in international projects.

In total, 20 key HR barriers have been identified through a literature survey and verified by project professionals. These HR barriers are ranked according to their ability to trigger other barriers by analysing their interactions using the decision-making trial and evaluation laboratory (DEMATEL) method. Based on Ulrich’s revised model for HR functions, a hybrid framework for international PRM has been proposed.

DEMATEL analysis categorized nine barriers as cause barriers and 11 as affected barriers. The “PROJECTS” model proposed for HR strategy development suggests eight strategies to overcome these nine cause barriers. The hybrid PRM framework developed includes the effect of the HR dimension.

This paper presents the generalized prioritization of HR barriers to international PRM. For a specific international project, the HR barriers and their prioritization may change slightly. The hybrid framework for PRM and the strategy development model suggested are yet to be validated.

Correlating two CSFs in international project management, i.e. HRM and PRM and ranking the HR barriers using the DEMATEL method is the uniqueness of this research paper. The hybrid framework developed for PRM based on HR functions in Ulrich’s revised model and the proposed new HR strategy development model “PROJECTS” are unique contributions of this paper.

Synergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.

The synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.

The findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.

In a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.