Xueyan Yang, Changxi Ma, Changfeng Zhu, Bo Qi, Fuquan Pan and Chengming Zhu
For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the…
Abstract
Purpose
For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.
Design/methodology/approach
The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.
Findings
By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.
Originality/value
Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.
Details
Keywords
Baiping Yan, Dazhuo Huang, Junjie Hong and Chengming Zhang
This paper aims to present the design and fabrication of a rotary magnetostrictive energy generator, using to harvest the rotation energy of human knee joint.
Abstract
Purpose
This paper aims to present the design and fabrication of a rotary magnetostrictive energy generator, using to harvest the rotation energy of human knee joint.
Design/methodology/approach
A rotary magnetostrictive energy generator is presented in this paper. The harvester consists of six movable flat Terfenol-D rods, surround by the picked-up coils respective, and alternate permanent magnet (PM) array fixed in the upper cover of the stator. The harvester rotates like as a stepper motor, which has rotary electromagnetic power generating effect and impacted magnetostrictive power generating effect in its rotation. Modeling and simulation are used to validate the concept. A prototype of harvester is fabricated and subjected to the experimental characterization.
Findings
The size of proposed structure is control as 77 cm3, and its mass is about 0.21 kg. Huge induced voltage generated in the short-time impact situation, and that induced voltage in the harvester can up to 18.6 V at 0.32 s stepper rotation. Also, the presented harvester has good harvesting effects at low frequency human walking situation, which is suitable to be used for future researches of wearable knee joint applications.
Originality/value
A new concept of magnetostrictive harvester is presneted, which will be benefit for the application of human knee joint wearable. Also, this concept will give us more idea for collection of human movement energy.
Details
Keywords
Chengming Huang, Sultan Sikandar Mirza, Chengwei Zhang and Yiyao Miao
This study aims to determine the impact of corporate digital transformation on the audit opinions of auditors in A-share nonfinancial listed companies in China. It also examines…
Abstract
Purpose
This study aims to determine the impact of corporate digital transformation on the audit opinions of auditors in A-share nonfinancial listed companies in China. It also examines how corporate internal control and corporate social responsibility (CSR) disclosure levels moderate this effect. This study fills a gap in the literature by investigating the impact of digital transformation on business performance, especially in the Chinese context, where digital transformation is rapidly progressing. This study also offers practical guidance for practitioners on whether and how to undergo a digital transformation and enhance their internal governance and social responsibility practices.
Design/methodology/approach
This study uses a sample of 2,637 Chinese A-share nonfinancial listed companies from 2009–2022, after excluding firms with ST, ST* or PT status; negative revenue; and missing data for three or more consecutive years. Digital transformation index data is collected from firms’ annual reports, and the other microlevel data from the Wind and CSMAR databases. The authors winsorize the data at 1% for outliers, resulting in 17,305 firm-year observations. This study uses fixed-effects logistic regression with clustered robust standard errors to analyze the binary dependent variable. This study also performs various robustness checks, such as probit model, multilevel fixed effects model and IV 2SLS estimations, to confirm the validity of the results.
Findings
This study reveals that digital transformation leads to standard unqualified audit opinions, meaning that companies that invest more in digital technologies and capabilities has more tendency to receive standard unqualified audit opinions, which signify the reliability and credibility of their financial reporting. This study also finds that corporate internal control and CSR disclosure levels positively moderate the effect of digital transformation on audit opinions. This study further conducts heterogeneity analysis and shows that the positive effect is originated by the state-owned enterprises, firms audited by non-Big4 auditing firms, firms with high internal control levels and firms with low CSR disclosure levels. The results are robust to different econometric methods.
Originality/value
This study contributes to the literature by providing empirical evidence on how digital transformation influences audit quality and credibility and how internal governance and social responsibility practices strengthen this influence. This study also has practical implications for practitioners by providing advice on whether and how to pursue a digital transformation and improve their internal governance and social responsibility practices. This study demonstrates its originality by reviewing the existing literature from three theoretical perspectives: stakeholder, signaling and reputation, and identifying the research gap that the study addresses. This study also compares its findings with previous studies and discusses the implications and limitations of its research. This study also proposes directions for future research based on its findings.
Details
Keywords
Amin Helmzadeh and Shahram M. Kouhsari
The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the…
Abstract
Purpose
The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the proposed method is to minimize the sum of squared errors (SSE) due to mismatches between simulation results and corresponding field measurements. Assuming that the network configuration is known, a limited number of erroneous branch parameters will be detected and corrected in an optimization procedure.
Design/methodology/approach
Proposing a novel formulation that utilizes network voltages and last modified admittance matrix of the simulation model, suspected branch parameters are identified. These parameters are more likely to be responsible for large values of SSE. Utilizing a Gauss-Newton (GN) optimization method, detected parameters will be modified in order to minimize the value of SSE. Required sensitivities in optimization procedure will be calculated numerically by the real time simulator. In addition, by implementing an efficient orthogonalization method, the more effective parameter will be selected among a set of correlated parameters to avoid singularity problems.
Findings
Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high efficiency of the proposed optimization method.
Originality/value
Incorrect branch parameter detection and correction procedures are investigated in real time simulators.