Search results

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.

Automatic optical inspection (AOI) systems have been widely used in many fields to evaluate the qualities of products at the end of the production line. The purpose of this paper is to propose a local-to-global ensemble learning method for the AOI system based on to inspect integrated circuit (IC) solder joints defects.

In the proposed method, the locally statistically modeling stage and the globally ensemble learning stage are involved to tackle the inspection problem. At the former stage, the improved visual background extraction–based algorithm is used for locally statistically modeling to grasp tiny appearance differences between the IC solder joints to achieve potential defect images for the subsequent stage. At the latter stage, mean unqualified probability is introduced based on a novel ensemble learning, in which an adaptive weighted strategy is proposed for revealing different contributions of the base classifier to the inspection performance.

Experimental results demonstrate that the proposed method achieves better inspection performance with an acceptable inspection time compared with some state-of-the-art methods.

The approach is a promising method for IC solder joint inspection, which can simultaneously grasp the local characteristics of IC solder joints and reveal inherently global relationships between IC solder joints.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

To further promote application of BIM technology in construction of prefabricated buildings, influencing factors and evolution laws of willingness to apply BIM technology are explored from the perspective of willingness of participants.

In this paper, a tripartite game model involving the design firm, component manufacturer and construction firm is constructed and a system dynamics method is used to explore the influencing factors and game evolution path of three parties' application of BIM technology, from three perspectives, cost, benefit and risk.

The government should formulate measures for promoting the application of BIM according to different BIM application willingness of the parties. When pursuing deeper BIM application, the design firm should pay attention to reducing the speculative benefits of the component manufacturer and the construction firm. The design firm and the component manufacturer should pay attention to balancing the cost and benefit of the design firm while enhancing collaborative efforts. When the component manufacturer and the construction firm cooperate closely, it is necessary to pay attention to balanced distribution of interests of both parties and lower the risk of BIM application.

This study fills a research gap by comprehensively investigating the influencing factors and game evolution paths of willingness of the three parties to apply BIM technology to prefabricated buildings. The research helps to effectively improve the building quality and construction efficiency, and is expected to contribute to the sustainability of built environment in the context of circular economy in China.

This paper aims to obtain a texture dental model with real images and improve the rendering effect of the dental model.

The paper proposes a semiautomatic method to construct a realistic dental model with real images based on two-dimensional/three-dimensional (2D/3D) registration. First, a 3D digital dental model and three intraoral images are obtained by a 3D scanner and digital single-lens reflex camera. Second, the camera projection poses for every intraoral images are calculated by using the single-objective optimization algorithm. Third, with camera poses, the preliminary projection texture mapping is performed; besides, the seam between two textures is marked. Finally, the marked regions are fused based on the image pyramid to eliminate obvious seams.

The paper provides a method to construct a realistic dental model. The method can map three intraoral images to the dental model. The experimental results show that the textured dental model without obvious distortion, dislocation and seams is constructed with simple interactions.

The proposed method can be applied to the digital smile design system to improve the communication efficiency between doctors, patients and technicians.

With the development of intelligent technology, deep learning has made significant progress and has been widely used in various fields. Deep learning is data-driven, and its training process requires a large amount of data to improve model performance. However, labeled data is expensive and not readily available.

To address the above problem, researchers have integrated semi-supervised and deep learning, using a limited number of labeled data and many unlabeled data to train models. In this paper, Generative Adversarial Networks (GANs) are analyzed as an entry point. Firstly, we discuss the current research on GANs in image super-resolution applications, including supervised, unsupervised, and semi-supervised learning approaches. Secondly, based on semi-supervised learning, different optimization methods are introduced as an example of image classification. Eventually, experimental comparisons and analyses of existing semi-supervised optimization methods based on GANs will be performed.

Following the analysis of the selected studies, we summarize the problems that existed during the research process and propose future research directions.

This paper reviews and analyzes research on generative adversarial networks for image super-resolution and classification from various learning approaches. The comparative analysis of experimental results on current semi-supervised GAN optimizations is performed to provide a reference for further research.

This paper aims to predict the effect of the hub cavity leakage on the overall performance with numerical simulations in the fan/booster of a high bypass ratio turbofan engine.

Simulations are conducted for leakage at the fan, the outlet of guide vane and the three-stage booster, as well as hub leakage (contain cavities and sealing). The results obtained are compared to the corresponding simulations without hub leakage.

The rotor/stator interaction locations are evaluated to discover a better location. The results show that the seal tooth structure produces secondary flow and turbulence in the root of blade suction surface, which increases the aerodynamic loss. The sealing clearance should be controlled to shrink the turbulent region and decrease the leakage.

This work can provide a theoretical guidance and technical support for the compressor design, which avoid many repeated manufactures and reduce waste of resources.

This work improves the understanding of the impact mechanism of hub cavity leakage on the performance when the clearance size of seal is variable.

To raise public awareness of protecting Buddhist temples, this study considers Hebei Province of China as an example, and explores the value of architectural planning and design of Buddhist temples. After 11 Buddhist temples in Hebei Province of China are selected, the paper adopts a Delphi method and questionnaire survey method, establishes the value evaluation system from four dimensions: historical value, artistic value, scientific value, and sociocultural value; and calculates the value of the Buddhist temples’ architectural planning and design according to expert rating. Research results indicate the following. Puning Temple, Jinhe Temple, and ShiEn Temple rank at the top because they are complete extant ancient buildings and have beautiful architectural styles. Chongguang Temple and other Buddhist temples have low comprehensive score because they are severely damaged and other reasons. The comparative study indicates that Buddhist temples at different historical periods have different architectural heritage values, and different influencing factors exert different effects on the architectural heritage value. The study establishes an evaluation indicator system, studies the value of Buddhist temples’ architectural planning and design, and achieves certain innovative research perspective. The evaluation of the value of Buddhist temples’ architectural planning and design can help the public gain a better understanding of the value of temple architectural culture. This understanding benefits the preservation of the temple building heritage.

As intelligent technology advances, practical applications often involve data with multiple labels. Therefore, multi-label feature selection methods have attracted much attention to extract valuable information. However, current methods tend to lack interpretability when evaluating the relationship between different types of variables without considering the potential causal relationship.

To address the above problems, we propose an ensemble causal feature selection method based on mutual information and group fusion strategy (CMIFS) for multi-label data. First, the causal relationship between labels and features is analyzed by local causal structure learning, respectively, to obtain a causal feature set. Second, we eliminate false positive features from the obtained feature set using mutual information to improve the feature subset reliability. Eventually, we employ a group fusion strategy to fuse the obtained feature subsets from multiple data sub-space to enhance the stability of the results.

Experimental comparisons are performed on six datasets to validate that our proposal can enhance the interpretation and robustness of the model compared with other methods in different metrics. Furthermore, the statistical analyses further validate the effectiveness of our approach.

The present study makes a noteworthy contribution to proposing a causal feature selection approach based on mutual information to obtain an approximate optimal feature subset for multi-label data. Additionally, our proposal adopts the group fusion strategy to guarantee the robustness of the obtained feature subset.

Developing nursing leadership has become a key policy priority to achieve universal health coverage. This study aims to explore the current status, developing trends and research frontiers in the field of nursing leadership.

In total, 1,137 articles and reviews on nursing leadership from 1985 to 2022 were retrieved from the Web of Science Core Collection database. Trends of publications, journals, countries/regions, institutions, documents and keywords were visualized and analyzed using Microsoft Excel and CiteSpace software.

Nursing leadership research showed an overall increase in number despite slight fluctuations in annual publications. The USA was the leading country in nursing leadership research, and the University of Alberta was the most productive institution. The Journal of Nursing Management was the most widely published journal that focused on nursing leadership, followed by the Journal of Nursing Administration. Keyword analysis showed that the main research hotspots of nursing leadership are improvement, practice and impact of nursing leadership.

This article summarizes the current state and frontiers of nursing leadership for researchers, managers and policy makers, as well as follow-up, development and implementation of nursing leadership. More research is needed that focuses on the improvement, practice and impact of nursing leadership, which are cyclical, complementary and mutually reinforcing. Longitudinal and intervention studies of nursing leadership, especially on patient prognosis, are also particularly needed.