Search results

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

This paper aims to identify consumers' health information consultation patterns by analyzing information sources to better understand consumers' health information needs and behavior in the context of multisource health information.

Haodaifu Online, an online health consultation (OHC) website in China, was used as a research data source, and 20,000 consultation cases were collected from the website with Python. After screening and cleaning, 1,601 consultation cases were included in this study. A content analysis-based mixed-methods research approach was applied to analyze these cases.

The results indicate that with the participation of OHC, there are 15 patterns of consumer health information consultation. Besides OHC, health information sources reported by consumers included medical institutions family/friends and the Internet. Consumers consult on a wide range of health issues including surgical conditions obstetrical and gynecological conditions and other 20 subjects. Consumers have multiple information needs when using OHC: getting prescriptions, diagnosing diseases, making appointments, understanding illnesses, confirming diagnoses and reviewing costs. Through further analysis it was found that consumers’ health information consultation patterns were also significantly different in health issues and health information needs.

This study broadens one’s understanding of consumer health information behavior, which contributes to the field of health information behavior, and also provides insight for OHC stakeholders to improve their services.

Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.