Accurate retrieval of the power equipment information plays an important role in guiding the full-lifecycle management of power system assets. Because of data duplication, database decentralization, weak data relations, and sluggish data updates, the power asset management system eager to adopt a new strategy to avoid the information losses, bias, and improve the data storage efficiency and extraction process. Knowledge graph has been widely developed in large part owing to its schema-less nature. It enables the knowledge graph to grow seamlessly and allows new relations addition and entities insertion when needed. This study proposes an approach for constructing power equipment knowledge graph by merging existing multisource heterogeneous power equipment related data. A graphsearch method to illustrate exhaustive results to the desired information based on the constructed knowledge graph is proposed. A case of a 500 kV station example is then demonstrated to show relevant search results and to explain that the knowledge graph can improve the efficiency of power equipment management.
Objective
The purposes of this study were to analyze the influencing factors of self-directed learning readiness (SDLR) of nursing undergraduates and explore the impacts of learning attitude and self-efficacy on nursing undergraduates.
Methods
A total of 500 nursing undergraduates were investigated in Tianjin, with the Chinese version of SDLR scale, learning attitude questionnaire of nursing college students, academic self-efficacy scale, and the general information questionnaire.
Result
The score of SDLR was 149.99±15.73. Multiple stepwise regressions indicated that academic self-efficacy, learning attitude, attitudes to major of nursing, and level of learning difficulties were major influential factors and explained 48.1% of the variance in SDLR of nursing interns.
Conclusions
The score of SDLR of nursing undergraduates is not promising. It is imperative to correct students’ learning attitude, improve self-efficacy, and adopt appropriate teaching model to improve SDLR.
Purpose
This study aims to explore the extrinsic and intrinsic motivational factors that affect accounting students’ acceptance behaviour towards the online component of blended learning (OCBL) in the context of COVID-19.
Design/methodology/approach
A sample of 354 accounting students from a Malaysian public university was selected. Confirmatory factor analysis, correlation and regression analysis and an independent sample t-test were used for data analysis.
Findings
The results showed that the predictor motivational variables in this study affected the acceptance behaviour of the participants except for perceived ease of use. Moreover, perceived value appeared to be the most influential factor. The results also indicated that postgraduates tend to accept the OCBL more than undergraduates.
Research limitations/implications
As the study participants were from only one public Malaysian university, generalisability is limited. In addition, this study only focussed on accounting students who were already enrolled in blended learning courses. Future studies could expand the population by considering those who have not signed up for such courses. Nevertheless, this study offers many theoretical and practical implications.
Originality/value
This study contributes to the OCBL literature, especially in accounting education, which was affected by the COVID-19 pandemic. It also offers practical suggestions for educational institutions and technology system designers to expand on the usage of OCBL and improve users’ acceptance of it.
In order to reduce the cost of grain container multimodal transport operations and improve collaborative management level of each link in grain container multimodal transport process, the paper presents an integrated business operation process and puts forward the architecture model of grain container multimodal transport system based on the Multi-Agent technology, further optimizing and integrating the management process of grain container multimodal transport operations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.