Daxin Tian, Weiqiang Gong, Wenhao Liu, Xuting Duan, Yukai Zhu, Chao Liu and Xin Li
This paper aims to introduce vehicular network platform, routing and broadcasting methods and vehicular positioning enhancement technology, which are three aspects of the…
Abstract
Purpose
This paper aims to introduce vehicular network platform, routing and broadcasting methods and vehicular positioning enhancement technology, which are three aspects of the applications of intelligent computing in vehicular networks. From this paper, the role of intelligent algorithm in the field of transportation and the vehicular networks can be understood.
Design/methodology/approach
In this paper, the authors introduce three different methods in three layers of vehicle networking, which are data cleaning based on machine learning, routing algorithm based on epidemic model and cooperative localization algorithm based on the connect vehicles.
Findings
In Section 2, a novel classification-based framework is proposed to efficiently assess the data quality and screen out the abnormal vehicles in database. In Section 3, the authors can find when traffic conditions varied from free flow to congestion, the number of message copies increased dramatically and the reachability also improved. The error of vehicle positioning is reduced by 35.39% based on the CV-IMM-EKF in Section 4. Finally, it can be concluded that the intelligent computing in the vehicle network system is effective, and it will improve the development of the car networking system.
Originality/value
This paper reviews the research of intelligent algorithms in three related areas of vehicle networking. In the field of vehicle networking, these research results are conducive to promoting data processing and algorithm optimization, and it may lay the foundation for the new methods.
Details
Keywords
Li Shaochen, Zhenyu Liu, Yu Huang, Daxin Liu, Guifang Duan and Jianrong Tan
Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship…
Abstract
Purpose
Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship between hands and operated objects and lack the modeling of subtle hand motions, which leads to a decline in accuracy for fine-grained action recognition. This paper aims to model the hand-object interactions and hand movements to realize high-accuracy assembly action recognition.
Design/methodology/approach
In this paper, a novel multi-stream hand-object interaction network (MHOINet) is proposed for assembly action recognition. To learn the hand-object interaction relationship in assembly sequence, an interaction modeling network (IMN) comprising both geometric and visual modeling is exploited in the interaction stream. The former captures the spatial location relation of hand and interacted parts/tools according to their detected bounding boxes, and the latter focuses on mining the visual context of hand and object at pixel level through a position attention model. To model the hand movements, a temporal enhancement module (TEM) with multiple convolution kernels is developed in the hand stream, which captures the temporal dependences of hand sequences in short and long ranges. Finally, assembly action prediction is accomplished by merging the outputs of different streams through a weighted score-level fusion. A robotic arm component assembly dataset is created to evaluate the effectiveness of the proposed method.
Findings
The method can achieve the recognition accuracy of 97.31% and 95.32% for coarse and fine assembly actions, which outperforms other comparative methods. Experiments on human-robot collaboration prove that our method can be applied to industrial production.
Originality/value
The author proposes a novel framework for assembly action recognition, which simultaneously leverages the features of hands, objects and hand-object interactions. The TEM enhances the representation of dynamics of hands and facilitates the recognition of assembly actions with various time spans. The IMN learns the semantic information from hand-object interactions, which is significant for distinguishing fine assembly actions.
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Keywords
Hanwen Chen, Siyi Liu, Xin Liu and Jiani Wang
The paper aims to examine the corporate social responsibility (CSR) activity of audit firms.
Abstract
Purpose
The paper aims to examine the corporate social responsibility (CSR) activity of audit firms.
Design/methodology/approach
Using hand-collected data on all Chinese audit firms’ CSR activities from 2007 to 2020, this study constructs two measures to proxy for audit firms’ CSR engagement: a dummy variable to indicate whether an auditor engages in CSR activities in year t and the frequency with which auditors conduct CSR activities in year t. The authors use ordinary least squares regression as a baseline methodology, along with the entropy balancing method and instrumental variable approach to alleviate potential endogeneity concerns.
Findings
The baseline results show that socially responsible audit firms provide higher quality audit services than their counterparts. In particular, the authors find that clients audited by socially responsible audit firms are less likely to receive an aggressively clean opinion. Moreover, the findings suggest that CSR activities related to community and employees are more relevant in improving audit quality compared with those related to other dimensions of CSR. Further analyses show that capital markets and audit clients react positively to audit-firm CSR activity. Audit firms engaging in CSR increase their audit inputs in response to risky clients, as compared with their counterparts. Finally, cross-sectional analyses show that the positive relationship is more pronounced for non-Big 4 and non-industry experts and is attenuated by within-firm geographic dispersion. In terms of client characteristics, the positive effect of audit-firm CSR is stronger when their clients face the higher financial risk or have lower CSR awareness than others. Taken together, these findings are consistent with the ethical view of audit-firm CSR engagement.
Practical implications
The study advances investors’ understanding of audit-firm CSR engagement and helps them evaluate the credibility of audited financial reports. Besides, the findings may also help guide the audit firms to conduct more CSR activities and help guide the audit clients to choose CSR audit firms.
Originality/value
To the best of the authors’ knowledge, this study provides the first large-sample evidence by empirically examining the association between audit-firm CSR activity and audit service performance. Besides, this paper also explores audit-firm CSR activity from two competing perspectives, thereby providing a comprehensive understanding of this issue. Finally, this work responds to the call for more CSR research in emerging markets.
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Keywords
Hui Liu, Charles Cullinan and Junrui Zhang
Companies may be defendants in lawsuits that are unresolved at year-end. This paper aims to consider whether the financial statements of companies facing litigation claims…
Abstract
Purpose
Companies may be defendants in lawsuits that are unresolved at year-end. This paper aims to consider whether the financial statements of companies facing litigation claims (pending litigation) are more time-consuming to audit due to the complexity and subjectivity of contingent liabilities associated with pending litigation. The authors consider whether auditors tailor their approach to pending litigation based on two distinct factors in the Chinese business environment: the client’s government ownership status and the legal development of the region in which the company is based.
Design/methodology/approach
Data on litigation against companies and their audit report lags were obtained for 18,029 firm-year observations of Chinese companies from 2008 to 2017. The sample was subsequently divided based on whether the company was a state-owned enterprise (SOE) and based on whether the company was based in a region of China with a more-developed and more market-oriented legal system.
Findings
The overall results indicate that audits of companies with pending litigation take 2.9 days longer than those of companies without pending litigation. For companies with multiple pending claims, each additional claim is associated with 1.9 more days of audit report lag. These effects are weaker for SOEs and for companies in regions of China with less developed legal systems. The results are consistent with the idea that auditors tailor their response to pending litigation based on the risk profile of the client, including consideration of SOE status and regional legal development.
Originality/value
This paper is the first to consider the potential effect of pending litigation (including claims not disclosed or recognized in financial statements) on audit report lags and how environmental business factors can influence this relationship.