Search results

The purpose of this study is to ensure the successful implementation of a landing cushion for the new generation armored vehicles with significantly enhanced quality. Furthermore, to introduce a high-precision landing cushioning analysis model.

To accurately analyze the cushioning performance of the new generation armored vehicles, a nonlinear finite element dynamics model considering the complex travel system was established. The model considered the influence of various nonlinear factors to measure the dynamic response difference between the proposed and traditional models. The cushioning performance of airbags under different landing conditions and their various influence factors were analyzed.

The travel system has a large influence on the key points of the vehicle, whose rear end of the upper deck has a larger acceleration fluctuation compared with the traditional model. The increase in the body material stiffness is helpful to reduce this fluctuation. The established nonlinear finite element model can effectively analyze the landing cushioning performance of airborne armored vehicles. The area of the external airbag vent has a large influence on the cushioning performance, and the cushioning system has excellent cushioning performance under various operating conditions.

This study introduces the travel system, which is ignored by traditional analytical models. The interactions between various types of complex structures are included in the analysis process in its entirety, leading to valuable new conclusions. Quantitatively reveals the analytical errors of traditional simulation models in multiple dimensions and the reasons for their formation. Based on a high-precision simulation model, it is verified that the designed airbag cushioning system has an excellent cushioning effect for the new generation of heavy airborne armored vehicles.

The novelty of this work comes from the need for smooth landing with low overload for a new type of large-load airborne armored vehicle and provides a high-precision model that quantifies the traditional analytical modeling errors and error principle.

This paper aims to improve the kinematic modeling accuracy of a spatial three-degrees-of-freedom compliant micro-motion parallel mechanism by proposing a modified modeling method based on the structural matrix method (SMM).

This paper analyzes the problem that the torsional compliance equation of the circular notched hinge is no longer applicable because it is subject to bilateral restrained torsion. The torsional compliance equation is modified by introducing the relative length coefficient. The input coupling effect, which is often neglected, is considered in kinematic modeling. The symbolic expression of the input coupling matrix is obtained. Theory, simulation and experimentation are presented to show the validity of the proposed kinematic model.

The results show that the proposed kinematics model can improve the modeling accuracy by comparing the theoretical, finite element method (FEM) and experimental method.

This work provides a feasible scheme for CMPM kinematics modeling. It can be better applied to the optimization design based on the kinematic model in the future.

One major problem preventing further application and benefits from additive manufacturing (AM) nowadays is that AM build parts always end up with poor geometrical quality. To help improving geometrical quality for AM, this study aims to propose geometrical deviation identification and prediction method for AM, which could be used for identifying the factors, forms and values of geometrical deviation of AM parts.

This paper applied the skin model-based modal decomposition approach to describe the geometrical deviations of AM and decompose them into different defect modes. On that basis, the approach to propose and extend defect modes was developed. Identification and prediction of the geometrical deviations were then carried out with this method. Finally, a case study with cylinders manufactured by fused deposition modeling was introduced. Two coordinate measuring machine (CMM) machines with different measure methods were used to verify the effectiveness of the methods and modes proposed.

The case study results with two different CMM machines are very close, which shows that the method and modes proposed by this paper are very effective. Also, the results indicate that the main geometrical defects are caused by the shrinkage and machine inaccuracy-induced errors which have not been studied enough.

This work could be used for identifying and predicting the forms and values of AM geometrical deviation, which could help realize the improvement of AM part geometrical quality in design phase more purposefully.

This paper aims to propose a novel method based on a gesture primitives analysis of human daily grasping tasks for designing dexterous hands with various grasping and in-hand manipulation abilities, which simplifies the complex and redundant humanoid five-finger hand system.

First, the authors developed the fingers and the joint configuration with a series of gesture primitives configurations and the modular virtual finger scheme, refined from the daily work gesture library by principal component analysis. Then, the authors optimized the joint degree-of-freedom configuration with the bionic design analysis of the anatomy, and the authors optimized the dexterity workspace. Furthermore, the adaptive fingertip and routing structure were designed based on the dexterous manipulation theory. Finally, the effectiveness of the design method was experimentally validated.

A novel lightweight three-finger and nine-degree-of-freedom dexterous hand with force/position perception was designed. The proposed routing structure was shown to have the capability of mapping the relationship between the joint space and actuator space. The adaptive fingertip with an embedded force sensor can effectively increase the robustness of the grasping operation. Moreover, the dexterous hand can grasp various objects in different configurations and perform in-hand manipulation dexterously.

The dexterous hand design developed in this study is less complex and performs better in dexterous manipulation than previous designs.

The purpose of this paper is to investigate the effects of cultural beliefs on governance in a business network without a legal institutional framework. Particular emphasis is placed on the cross-country remittance mail operating network in Chaoshan, China, during the period 1860-1949. This investigation builds on Greif’s business governance theory and develops an analytical framework that considers cultural beliefs, agency relationships and multilateral punishment mechanisms. Furthermore, it uses the institutional analysis method to identify the institutional factors that sustained the remittance mail operating networks and their underlying mechanisms.

This paper adopts the qualitative research method. First, it investigates the history of the remittance mail operating network and agency relationships by searching through the contents of the relevant historical documents preserved in the official archives and information found in other records. Thereafter, it summarizes and demonstrates the cultural beliefs inferred from that research. The archival materials permit analysis of the interactions between cultural beliefs, agency relationships and multilateral punishment mechanisms by the institutional analysis method.

Due to the lack of legal institutions in China during the period under review, cultural beliefs played a central institutional role in cross-country business relations. Network governance was coupled with clan cultural beliefs in the remittance mail operating network. This relationship was the key to sustain the efficient operation of the remittance mail network.

In the West, corporate governance has been influenced by and has become an integral feature of Western culture and values. This is not necessarily so for the corporate governance in terms of Chinese culture and values. Thus, instead of mimicking the modes of developed countries, it is important for Chinese enterprises to seek a mode of corporate governance that is in accord with their local cultures. This may be an important focus for enterprise development.

This study examines the relative effects of human capital (HC), social capital (SC) and psychological capital (PC) on hotel employees’ job performance.

A sample of 417 employees from seven five-star hotels in China was recruited for the study. Both exploratory and confirmatory factor analyses were used to confirm the quality of measurement structures. Stepwise regression was used to examine the relative effects of the three capitals on hotel employees’ job performance.

PC was found to be the strongest predictor of self-reported job performance (SJP) among the three capitals under investigation. Education and work experience in the HC domain affected SJP, whereas SC dimensions did not. However, only education and work experience in the HC domain were found to affect supervisor-rated job performance (RJP).

Given the impact of PC on hotel employee’s SJP, human resource managers should attend to this capital in staff recruitment, retention and training and development.

This study provides a holistic comparative lens to examine the relative contribution of the three capitals on hotel employees’ job performance. This will help to further clarify the roles played by each of the capitals in hotel service work, thus advancing the development of the theories underlying each of the three capitals.

Recent attention to the developments focusing on the educational services has been noteworthy, with the educational environment specifically the smart campus emerging both as a domain and as an opportunity. As a domain worthy of exploration, a number of research efforts are being conceptualized around smart campus initiatives. The existing bouquet of research publications on smart campus provides a testimony of the enthusiasm and also exposes the heterogeneous attempts the domain has witnessed to date. The available evidence is still inadequate to provide clarity on the thrust areas of research around smart campus.

Given the understanding, this study intends to decode the domain to get an early impression of the focus of the research concentration around smart campus. Thereby the study resorts to an automated text-mining approach using Python on contents shortlisted systematically, and published between the period 2010 and May 2022, from select databases.

Based on the analysis it was possible to identify eight themes (i.e. smart campus characteristics, smart campus stakeholders, smart campus frameworks, smart campus technologies, smart campus infrastructure, smart campus evaluation, smart learning environment and smart campus applications) characterizing research efforts within the smart campus literature.

The themes around the smart campus showcase the thrust areas receiving attention. These characterize extant research endeavours in the smart campus domain and can offer useful pointers to researchers going forward. This awareness can also be beneficial to institutional leadership and technology providers intending to implement smart campus initiatives, contributing to the development of the educational environment.

The purpose of this paper is that the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment under the connection of the cone–hole docking mechanism.

An arc-shaped docking cone head with a posture-maintaining spring and two arc-shaped connecting rods that formed a ring round hole were designed to achieve large tolerance docking. Before active locking, the coordination between structures was used to achieve passive locking, which mitigated the docking impact of modular robots in unstructured environment. Using the locking ring composed of the two arc-shaped connecting rods, open-loop and closed-loop motion characteristics were obtained through the mutual motion of the connecting rod and the sliding block to achieve active locking, which not only ensured high precision docking, but also achieved super docking stability.

The cone–hole docking mechanism had the docking tolerance performance of position deviation of 6mm and pitch deviation of 8° to achieve docking of six degrees of freedom (6-DOF), which had a load capacity of 230 N to achieve super docking stability. Under the connection of the cone–hole docking mechanism, the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment.

Based on mechanical analysis of universal models, a cone–hole docking mechanism combining active and passive functions, six-dimensional constraints could be implemented, was proposed in this paper. The characteristics of the posture-maintaining spring in the cone docking head and the compression spring at the two ends of two arc-shaped connecting rods were used to achieve docking with large tolerance. Passive locking and active locking modules were designed, mitigating impact load and the locking did not require power to maintain, which not only ensured high precision docking, but also achieved super docking stability.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.