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Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

This paper aims to establish the wideband model of a sub-module in a modular multilevel converter (MMC) and analyze the switch transients of the sub-module.

The paper builds an MMC sub-module test circuit and conducts dynamic tests both with and without the bypass thyristor. Then, it builds the wideband model of the MMC sub-module and extracts the model parameters. Finally, based on the wideband model, it simulates the switch transients and analyzes the oscillation mechanism.

The dynamic testing shows the bypass thyristor will add oscillations during switch transients, especially during the turn-on process. The thyristor acts like a small capacitor and reduces the total capacitor in the turn-on circuit loop, thus causing under-damped oscillations.

This paper found that the bypass thyristor will influence the MMC sub-module switch transients under certain circumstances. This paper proposes a partial inductance extraction procedure for the MMC sub-module and builds a wideband model of the sub-module. The wideband model is used to analyze and explain the switch transients, and can be further used for insulated gate bipolar transistor switch oscillation inhibition and sub-module design optimization.

The purpose of this study is to develop an electromagnetic loading method for online measurement of the acoustoelastic coefficients and bus bar plane stress.

A method based on the combination of electromagnetic loading and the acoustoelastic effect is proposed to realize online measurement of acoustoelastic coefficients and plane stress. Electromagnetic loading is performed on the bus bar specimen, and the acoustoelastic coefficients and the bus bar plane stress are obtained by the ultrasonic method. An electromagnetic loading experimental platform is designed to provide electromagnetic force to the metal plate, including an electromagnetic loading module, an ultrasonic testing module and a stress simulation module.

The feasibility of the proposed electromagnetic loading method is proved by verification experiments. The acoustoelastic coefficients and plane stress measured using the electromagnetic loading method are more accurate than those measured using the traditional method.

The proposed electromagnetic loading method provides a new study perspective and enables more accurate measurement of the acoustoelastic coefficients and plane stress. The study provides an important basis for evaluating the operation status of electrical equipment.

In the background of the post-financial crisis era and the transition of China’s economic development, the frequent occurrence of workplace deviant behavior in the economic field, such as stealing and bribery, caused a huge impact on the enterprise. In recent years, the deviant behavior of employees has been increased noticeably. The purpose of this study is to explore the influence of paternalistic leadership on employee deviant behavior in workplace. To have a deep understanding of the relationship between paternalistic leadership and employee deviant behavior, the author’s design rule-oriented ethical climate and self-interest-oriented ethical climate as two mediators in this research model.

Based on social learning theory and stressor-emotion model, this study conducts an investigation of influence mechanism between paternalistic leadership and workplace deviant behavior. Time-lagged data was collected from 226 employees from six cities in China. To test the hypothesis that the authors developed in this paper, the authors use empirical models from the existing literature about paternalistic leadership on employee deviant behavior. They establish multiple linear regressions to test the hypotheses.

This study reveals the direct effect of authoritarian leadership on employee deviant behavior and the moderated roles of benevolent leadership and moral leadership, also analysis the mediated mechanism of self-interest-oriented ethical climate and rule-oriented ethical climate. The results show that the higher the degree of authority leaders show in the organization, the easier to stimulate workplace deviance of employee, self-interest-oriented ethical climate and rule-oriented ethical climate play mediated role between authoritarian leadership and workplace deviant behavior. The interaction of benevolent leadership and moral leadership with authoritarian leadership can weaken the self-interest-oriented ethical climate but has nothing to do with rule-oriented ethical climate.

This study has three main contributions to the previous literature. First, this study explores the relationship between authoritarian leadership and employee workplace deviance, which could enrich the research on these negative behaviors in the Chinese context. Second, this study unpacks the “black box” in which authoritarian leadership influences employee workplace deviant behavior. Third, this study further examines the impacts of different combinations of the three factors of paternalistic leadership.

The purpose of this paper is to present a method to calculate the transient induced voltages along the underground pipelines and analyze the transient interference generated in the pipelines due to the inductive coupling in the fault‐to‐ground condition of power lines in close proximity.

Based on finite difference‐time domain method, an improved method is proposed to calculate transient inductive interference in underground metallic pipelines due to a fault in nearby power lines. The frequency‐dependent problem in the analysis of transient interference is solved in phase domain. Compared with the traditional method, the disposal of phase‐modal transformation matrices’ frequency‐dependent characteristic is avoided and the calculation is simplified by using vector fitting approach and recursive algorithm greatly in the proposed method.

A novel improved method is proposed to calculate transient induced voltage distribution along underground metallic pipelines due to a fault in nearby power lines. Results show that the peak value of transient induced voltage at the most critical point is about 1.15 times of the magnitude in the steady state without the fault removed and the analysis of transient inductive interference is necessary in the fault‐to‐ground case of power lines.

In order to mitigate the interference from power lines to nearby pipelines, pipelines should be good grounded and positioned as far away from the power line as possible. In high soil resistivity areas, the common corridor should be avoided.

The paper presents a method to calculate the transient induced voltages along the underground pipelines and analyze the transient interference generated in the pipelines due to the inductive coupling in the fault‐to‐ground condition of nearby power lines. The proposed method is general and can also be applied to other transient interference studies such as crosstalk problems of communication networks and interference between power lines and aboveground pipelines or communication cables. Effects of various parameters upon the inductive interference generated in underground pipelines due to a fault in nearby power lines are analyzed to be a guide for controlling the inductive interference.

This study aims to evaluate the effectiveness of different prefabricated construction (PC) policies using a case study in Wuhan, considering the local context.

The effectiveness of PC policies is falling behind expectations. The main reason lies in an insufficient understanding of the policy impacts. An agent-based model was built by choosing the residential sector in a typical large city of Wuhan, China, as the study case. Different cost reduction scenarios were introduced for investigating the PC policy effectiveness. The proposed model and simulation approach can be used for other cities and generalized to the whole Chinese PC industry with the potential to include more local policies and corresponding data.

Simulation results show that carbon emission reduction will be between 60,000 and 80,000 tons with policy incentives, nearly double that of the no policy intervention scenario. The target of 30% PC in all new buildings by 2026 in China is achievable with the subsidy policies of linear cost reduction, or cost reduction conforms to the learning curve.

Simulation results of three kinds of policy show that subsidy policy optimization is necessary regarding reducing the level of subsidy needed. The carbon credit policy is not essential since it has little influence on PC development. Implementing the project procurement restriction policy is not recommended if the scale of development of PC is more important than achieving the development target.

This study can help the government and developers make better policy and strategic decisions on PC development and boost the sustainability transition of the construction industry.

The purpose of this study is to develop and validate empirically a research model that depicts the relationships between the identified key value proposition attributes of mobile value‐added services and the core factors of brand equity.

Survey data collected from 497 mobile value‐added service consumers were examined using structural equation modeling to validate the research model.

The results indicate that the mobile service attributes of personalization, identifiability, and perceived enjoyment have significant positive influences on the key brand equity factors, including brand loyalty, perceived quality, brand awareness, and brand associations. Additionally, the results confirm the significance of all four of the brand equity factors in interpreting consumer purchase intention in the context of mobile value‐added service consumption.

The research results provide insights into how mobile value‐added services may be better designed and delivered to enhance brand equity and, in turn, profits.

While the market potential of mobile value‐added services and the importance of brand equity have both been widely recognized, the development and empirical validation of a model that specifically depicts the determinants of mobile value‐added service consumption from a brand‐equity perspective has not yet been undertaken. Consequently, this study investigates the relationships among key m‐commerce attributes, core brand‐equity components, and consumer behaviors. The research results have extended the application and advanced the understanding of previous mobile‐commerce and brand‐equity theories in the context of mobile value‐added service consumption.

How do different corporate governance structures fare under conditions of fundamental environmental transformations? Treating governance structure as a knowledge distribution mechanism embedded in institutional frameworks, the paper aims to propose that the efficiency of this knowledge diffusing process will increase organizational survival under a punctuational change.

Using the case of Chinese banking industry during 1897-1927, a period of rapid technological, economic, and regulatory shifts.

Money shops (qianzhuang) with decentralized, open and extended governance structure were better able to adapt to rapid changes in the environment and had a higher survival chance than ticket stores (piaohao) with centralized, closed and internalized governance structure.

When exogenous shocks dramatically change the environment, decentralized, open and extended governance structures can more easily discover new habitats in which a modified form of organization can thrive.

By examining the Chinese banking industry during the fundamental shift of the environment at the turn of the twentieth century, this paper sheds new wisdom on the understanding of the current turbulent world and helps us discover new solutions to cope with the institutional transition necessary to survive and prosper in the new world environment and pave the road ahead.

To develop a process model of interorganizational systems (IOS) collaboration and systematic framework for understanding and classifying IOS technologies for interorganizational collaboration.

This paper synthesizes relevant concepts and findings in the IOS, economics, and management literature. It also presents empirical examples to illustrate key issues, practices, and solutions involved in IOS collaboration.

An integrative model of IOS collaboration is introduced and knowledge sharing, participative decision making, and conflict governance identified as three behavioral process elements underlying effective interorganizational collaboration. Extending Kumar and van Dissel's IOS framework to directly recognize these elements, a more complete collaboration‐oriented framework for characterizing key elements of interorganizational collaboration and classifying IOS technologies is developed.

This paper brings together diverse ideas into a systematic view of collaboration via interorganizational systems. It contributes to a deeper, fuller understanding of issues involved in achieving collaborative advantage with IOS technologies. The paper also identifies factors and relationships that researchers should consider in designing empirical studies, posing hypotheses about collaboration via IOS, and analyzing results.

The model and framework can serve as a check‐list of considerations that need to be dealt with by leaders of collaboration‐oriented IOS initiatives. The IOS framework and technology classification may also suggest ways in which IT vendors might provide better technological solutions, services, and software for interorganizational collaboration.

This new IOS collaboration model and framework provide more complete and useful guidance for researchers, educators, and practitioners.

Based on the weak seismic performance and low ductility of coupled shear walls, engineered cementitious composites (ECC) is utilized to strengthen it to solve the deformation problem in tall buildings more effectively and study its mechanical properties more deeply.

The properties of reinforced concrete coupled shear wall (RCCSW) and reinforced ECC coupled shear wall (RECSW) have been studied by numerical simulation, which is in good agreement with the experimental results. The reliability of the finite element model is verified. On this basis, a detailed parameter study is carried out, including the strength and reinforcement ratio of longitudinal rebar, the placement height of ECC in the wall limb and the position of ECC connecting beams. The study indexes include failure mode and the skeleton curve.

The results suggest that the bearing capacity of RECSW is significantly affected by the ratio of longitudinal rebar. When the ratio of longitudinal rebar increases from 0.47% to 3.35%, the bearing capacity of RECSW increases from 250 kN to 303 kN, an increase of 21%. The strength of longitudinal rebar has little influence on the bearing capacity of RECSW. When the strength of the longitudinal rebar increases, the bearing capacity of RECSW increases little. The failure mode of RECSW can be improved by lowering the casting height of the ECC beam in a certain range.

In this paper, ECC is used to strengthen the coupled shear wall, and the accuracy of the finite element model is verified from the failure mode and skeleton curve. On this basis, the casting height of the ECC casting wall limb, the strength and reinforcement ratio of longitudinal rebar and the position of the ECC beam are studied in detail.