QingHui Wang, Zhong-Dong Huang, JingRong Li and Jia-Wu Liu
Realistic force sensation can help operators better feel and manipulate parts for virtual assembly (VA). Moreover, for VA of mechanical parts, it is necessary to consider their…
Abstract
Purpose
Realistic force sensation can help operators better feel and manipulate parts for virtual assembly (VA). Moreover, for VA of mechanical parts, it is necessary to consider their tolerance levels so as to apply proper assembly forces. Out of the three common assembly fit types, the type of clearance fit is the focus of virtual manual assembly, as parts with such fit type require precise force feedback to assist users’ assembly operations.
Design/methodology/approach
This study proposes a novel force rendering model for VA of mechanical parts with clearance fits. By decomposing an actual assembly operation into three consecutive states, the corresponding forces are formulated.
Findings
A prototype system is designed and developed to implement the model, and comparative case studies are conducted to investigate the users’ performance with the other three common approaches, namely, a typical WIMP (window-icon-menu-pointer) interface with CAD software, a physics simulation with collision detection and the approach that combines physics simulation and geometric constraints restriction. The results have shown that the proposed model is more realistic by providing continuous and realistic force feedback to the users.
Originality/value
The users’ feeling of immersion and their operational efficiency are greatly enhanced with the force sensation provided.
Details
Keywords
Abstract
Purpose
This study aims to review the literature on graph-theoretic mining methods for node importance in both static and dynamic world city networks, which is correspondingly categorised by graph-theoretic node importance mining on network topologies and transmission mechanisms.
Design/methodology/approach
The authors overview the graph-theoretic indicators of node importance: centrality and power. Then, the methods of graph-theoretic node importance mining on network topologies are assessed with node relevance, centrality- and power-based measurements, heterogeneous fusion and other miscellaneous approaches. The latest progress in transmission mechanisms is also reviewed in this study involving network evolution, node immunisation and robustness in dynamics. Finally, the findings are analysed and future directions in this field are suggested.
Findings
The method development of node importance mining is driven by complex application-based problems within a transmission mechanism. Fusion measurements, based on centrality and power, are extended by other graph mining techniques in which power has a significant role. In conclusion, the trends of node importance mining focus on power-embedded fusion measurements in the transmission mechanism-based complex applications.
Originality/value
This is the first systematic literature review of node importance from the view of graph-theoretic mining.
Details
Keywords
Su Yong and Gong Wu-Qi
Abnormal vibrations often occur in the liquid oxygen kerosene transmission pipelines of rocket engines, which seriously threaten their safety. Improper handling can result in…
Abstract
Purpose
Abnormal vibrations often occur in the liquid oxygen kerosene transmission pipelines of rocket engines, which seriously threaten their safety. Improper handling can result in failed rocket launches and significant economic losses. Therefore, this paper aims to examine vibrations in transmission pipelines.
Design/methodology/approach
In this study, a three-dimensional high-pressure pipeline model composed of corrugated pipes, multi-section bent pipes, and other auxiliary structures was established. The fluid–solid coupling method was used to analyse vibration characteristics of the pipeline under various external excitations. The simulation results were visualised using MATLAB, and their validity was verified via a thermal test.
Findings
In this study, the vibration mechanism of a complex high-pressure pipeline was examined via a visualisation method. The results showed that the low-frequency vibration of the pipe was caused by fluid self-excited pressure pulsation, whereas the vibration of the engine system caused a high-frequency vibration of the pipeline. The excitation of external pressure pulses did not significantly affect the vibrations of the pipelines. The visualisation results indicated that the severe vibration position of the pipeline thermal test is mainly concentrated between the inlet and outlet and between the two bellows.
Practical implications
The results of this study aid in understanding the causes of abnormal vibrations in rocket engine pipelines.
Originality/value
The causes of different vibration frequencies in the complex pipelines of rocket engines and the propagation characteristics of external vibration excitation were obtained.
Details
Keywords
Manjula Shukla and Piyush Pandey
In the post-pandemic period and following widespread inoculation against the infection, this research aims to pinpoint the variables that affect consumers' behavioural intentions…
Abstract
Purpose
In the post-pandemic period and following widespread inoculation against the infection, this research aims to pinpoint the variables that affect consumers' behavioural intentions (BIs) towards online food delivery (OFD) services. The study goes further to investigate the potential impact of vaccine confidence (VC) in modifying the association between consumers' BI to utilise OFD services and their actual usage behaviour (UB).
Design/methodology/approach
Using information gathered through a structured questionnaire from 372 Indian customers, a proposed model based on the technology acceptance model (TAM) and theory of planned behaviour (TPB) models was put to the test using structural equation modelling (SEM).
Findings
Results demonstrate that perceptions of ease of use, attitude (ATT) and perceived behavioural control (PBC) have a favourable and significant impact on behaviour intention amongst Indian OFD users. Contrary to what the TAM and TPB models had predicted, perceived usefulness (PU) and subjective norms (SN) did not significantly affect the BI of the sample of Indian OFD users. Furthermore, the association between BI and actual UB of OFD users is not moderated by the consumers' VC.
Practical implications
The study contributes by shedding light on the variables that affect Indian OFD users' BIs after the coronavirus disease 2019 (COVID-19) pandemic era and mass immunisation and whether VC has a role to play in affecting consumer behaviour, which will aid OFD service providers, eateries and marketers in redesigning their marketing plans.
Originality/value
The present study is the first in making a literary contribution through analysis of the moderating effect of VC on the relationship between BI and actual UB. Additionally, this study presents evidence from India, one of the first nations to implement widespread COVID-19 inoculation.
Details
Keywords
Jun Huang, Haijie Mo and Tianshu Zhang
This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt…
Abstract
Purpose
This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.
Design/methodology/approach
Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.
Findings
This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.
Originality/value
This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.
Details
Keywords
Hossein Dehdarirad, Javad Ghazimirsaeid and Ammar Jalalimanesh
The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the…
Abstract
Purpose
The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.
Design/methodology/approach
To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.
Findings
A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.
Originality/value
Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.