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The purpose of this study is to optimize the operational efficiency of the entire system by developing a reasonable maintenance strategy for wind turbines that improves component reliability and safety while reducing maintenance costs.

A hybrid incomplete preventive maintenance (PM) model based on boundary intensity process is established to give dynamic PM intervals for wind turbines using an iterative method with reliability as a constraint; the selection method of PM and replacement is given based on the cost-effectiveness ratio, which in turn determines the optimal number of PM for wind turbines.

The reliability is used to obtain the components’ maintenance cycle, and the cost-effectiveness ratio is used to select the number of maintenance times, thus, getting the optimal maintenance strategy. The validity of this paper’s method is verified by arithmetic cases, which provides a new method for formulating a reasonable PM strategy for wind turbines.

The wind turbine preventive maintenance strategy for Boundary intensity process proposed in this paper can scientifically formulate the maintenance strategy, optimize the cost-effectiveness per unit of time of the wind power generation system, and solve the problems of difficulty in formulating a reasonable maintenance strategy for the wind turbine components and high operation and maintenance costs.

In this paper, the authors describe the failure pattern by a Boundary intensity process, establish a hybrid incomplete PM model by introducing a failure intensity increment factor and an age reduction factor and establish a maintenance strategy optimization model with comprehensive consideration of reliability and cost-effectiveness ratio. Finally, the validity of the model in this paper is verified by arithmetic case analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0153/

This research clarifies the connotations and dimensions of artificial intelligence (AI) technology stimulation and establishes a stimulus scale to explain the relationship between AI technology stimuli and smart customer experience.

This is an empirical study that uses SPSS 24.0 software to perform hypothesis testing on the path relationships between model elements.

Two dimensions of AI technology stimuli (i.e. passion and usability) have a significant, positive impact on smart customer experience; the moderating effects of contrasting dimensions of technology readiness (i.e. optimism and discomfort) are significantly different; smart customer experience has a significant, positive impact on the word-of-mouth (WOM) intentions of consumers.

There are several limitations. Most importantly, the data collected in this study are only from consumers who use intelligent customer service robots in the catering industry. Future research can consider exploring relevant AI technologies in other sectors.

This study has several implications that guide catering companies to develop various positioning and strategies for remaining competitive effectively.

Based on arousal theory, customer experience theory and WOM marketing theory, this is the first novel research project that empirically discusses the dimensions of AI technology stimuli, smart customer experience and WOM intentions with regard to the moderating effect of the technology readiness of consumers toward AI technology.

This study aims to use corporate social responsibility (CSR) reporting focused on poverty alleviation in China as a case to demonstrate a unique interplay between the state and private enterprises. It illustrates how CSR reporting has influenced both the mechanisms and outcomes of their interactive relationship, contributing to the construction of symbolic power.

Drawing on Bourdieu’s theory of symbolic power, this study explores how symbolic power has been constructed and reinforced between the state and private enterprises. It highlights the unique role of CSR reporting in facilitating an alignment between private enterprises objectives and state goals, ultimately reinforcing symbolic and social order. The empirical materials examined are the CSR reports prepared by the top 20 private enterprises in China from 2017 to 2022.

Major private business enterprises in China actively engage with the state’s objectives on poverty alleviation as reflected through their CSR reporting practices. This engagement is evidenced by shifts in keywords, dominant language and reporting structure, which closely align with the state’s stance on the issue. As a result, these enterprises receive heightened public recognition, which in turn helps reinforce the symbolic power and its influence on corporate behaviour.

This paper contributes to the CSR accounting literature by revealing a strategic role of CSR reporting that extends beyond conventional compliance levels commonly observed in Western liberal democratic societies. It serves as a function that facilitates interaction between the state and private enterprises in a symbolic power relationship, where both parties mutually benefit from the alignment of interests in poverty alleviation and social positioning.

Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

Automatic segmentation of brain tumor from medical images is a challenging task because of tumor's uneven and irregular shapes. In this paper, the authors propose an attention-based nested segmentation network, named DAU-Net. In total, two types of attention mechanisms are introduced to make the U-Net network focus on the key feature regions. The proposed network has a deep supervised encoder–decoder architecture and a redesigned dense skip connection. DAU-Net introduces an attention mechanism between convolutional blocks so that the features extracted at different levels can be merged with a task-related selection.

In the coding layer, the authors designed a channel attention module. It marks the importance of each feature graph in the segmentation task. In the decoding layer, the authors designed a spatial attention module. It marks the importance of different regional features. And by fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

To verify the effectiveness of the DAU-Net, experiments were carried out on the BRATS 2018 brain tumor magnetic resonance imaging (MRI) database. The segmentation results show that the proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 89% in the complete tumor, which is an improvement of 8.04 and 4.02%, compared with fully convolutional network (FCN) and U-Net, respectively.

The experimental results show that the proposed method has good performance in the segmentation of brain tumors. The proposed method has potential clinical applicability.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

The purpose of this study is to systematically analyze the evolution of health tourism development, identify relevant themes and segments of health tourism research and offer future research directions and practical implications for academic researchers and tourism practitioners worldwide using China as an example.

Using a bibliometric analysis, the present study comprehensively analyzes the theme, segments and the evolution of health tourism research over the past 40 years in China.

Major findings show that health tourism research in China could be divided into four stages with different characteristics, and three segments, including wellness tourism, health and wellness tourism and medical tourism. Findings also reveal the trend of health tourism development tends to be industrialized, diversified and systematic under the guidance of recent policies. Theoretically, based on the theoretical framework developed by Hall (2011), the present study contributes to the establishment and extension of the framework for health tourism within the context of China. Practically, findings can provide health tourism-related policy implications for the future development of health or health sector-integrated tourism.

The study proposes possible collaboration between government and academia in terms of health tourism-related policy formulation.

Through 40-year bibliometric analysis of health tourism evolution in China, the present study explores the main themes of health tourism development, identifies the segments of health tourism and analyzes the development stages of health tourism. Findings should be of use to international readers to better understand the uniqueness of health tourism development and find out possible future health tourism development research directions. As a result, major contributions of this paper are the comprehensive analysis of the evolution of health tourism research and the implications on other countries and regions to adopt a pragmatic approach to explore the trend and unique characteristics of health tourism for future development.

本研究旨在系统地分析中国健康旅游的演变过程, 探索健康旅游研究的相关主题及细分领域, 并为全球学术研究人员及旅游从业者提供未来的研究方向。

此研究通过文献计量学的研究方法, 全面分析了中国近40年健康旅游研究的主题、细分以及演变。

中国健康旅游研究根据其发展特点可以分为四个阶段及三个细分主题：分别是养生旅游, 康养旅游及医疗旅游。调查结果还表明, 在近期政策的引导下, 健康旅游发展趋于产业化、多元化和系统化。从理论意义来说, 本研究基于Hall (2011) 提出的理论框架, 构建了中国背景下的健康旅游框架。从实践意义来说, 研究结果可以为健康和旅游业相关部门提供政策建议。

此研究还有助于促进政府和学术界在健康旅游政策制定方面的合作。

此研究通过对中国近40年健康旅游的研究进行文献计量分析, 探索了健康旅游发展的主题, 分析了健康旅游的细分市场以及发展阶段。研究结果有助于学术界及旅游业更好地了解健康旅游发展的独特性及未来健康旅游的研究方向。因此, 本研究的主要贡献是全面地分析了健康旅游研究的演变, 并有助于其他国家/地区探索未来健康旅游的发展趋势和其独特特征。

El propósito del presente estudio es analizar sistemáticamente la evolución del desarrollo del turismo de salud, identificar temas y segmentos relevantes de la investigación en turismo de salud y ofrecer direcciones de investigación futuras e implicaciones prácticas para investigadores académicos y profesionales del turismo en todo el mundo utilizando a China como ejemplo.

Mediante un análisis bibliométrico, el presente estudio analiza exhaustivamente la temática, los segmentos y la evolución de la investigación sobre turismo de salud en los últimos 40 años.

Los principales hallazgos muestran que la investigación del turismo de salud en China podría dividirse en cuatro etapas con diferentes características y tres segmentos, incluido el turismo de bienestar, el turismo de salud y bienestar y el turismo médico. Los hallazgos también revelan que la tendencia del desarrollo del turismo de salud tiende a ser industrializado, diversificado y sistemático bajo la guía de políticas recientes. El presente estudio hace aportes tanto teóricos como prácticos. Teóricamente, basado en el marco teórico desarrollado por Hall (2011), el presente estudio contribuye al establecimiento y extensión del marco para el turismo de salud en el contexto de China. En la práctica, los hallazgos pueden proporcionar implicaciones políticas relacionadas con el turismo de salud para el desarrollo futuro de la salud o el turismo integrado en el sector de la salud.

El estudio también propone una posible colaboración entre el gobierno y la academia en términos de formulación de políticas relacionadas con el turismo de salud.

A través del análisis bibliométrico de 40 años de la evolución del turismo de salud, el presente estudio explora los temas principales del desarrollo del turismo de salud, identifica los segmentos del turismo de salud y analiza las etapas de desarrollo del turismo de salud. Los hallazgos deberían ser de utilidad para los lectores internacionales para comprender mejor la singularidad del desarrollo del turismo de salud y descubrir posibles direcciones futuras de investigación sobre el desarrollo del turismo de salud. Como resultado, las principales contribuciones de este documento son el análisis exhaustivo de la evolución de la investigación en turismo de salud y las implicaciones en otros países y regiones para adoptar un enfoque pragmático para explorar la tendencia y las características únicas del turismo de salud para el desarrollo futuro.

City wall is an important symbol of ancient Chinese cities with unique geographical and cultural characteristics. Thus, the preservation of this historic landmark is considered significantly important. However, numerous residential construction activities and changes in ecological environment have destructed a great portion of the city walls in recent years. This study looks into the preservation of the ancient city walls from the systematic perspective and in line with the actual characteristics of Longdong Region to provide guideline measures for the protection and restoration of such landmark. Cognition and preservation are adopted extensively to investigate the specific situation of and the factors that influence the ancient city walls in this region. Preservation strategies for the city walls, including the “Axis-Point” system, planning control, and authenticity readability, are presented. The ancient city walls in Longdong Region can be preserved by protecting the entire region, the city, and the main wall body. The systematic method and preservation strategies at the “macro perspective,” “medium perspective” and “micro perspective” levels can solve the preservation problems of the ancient city walls in Longdong Region effectively.

Asks on whose behalf the black woman poet in the USA speaks, what type of language she uses and what audience she has. Points out that an earlier lack of tradition meant that originally white styles of language were used and aimed at the white audience. Looks at the rise of the blues era and the “blueswoman”. Considers the work of Phillis Wheatley, Alice Dunbar Nelson, Anne Spencer and Angelina Grimke together with Margaret Walker and singers such as Ma Rainey and Bessie Smith. Finally, outlines the development of a political era and the growing sexual freedom of black women and the impact their writings.

This paper aims to compare the Greek and Chinese rhetorical traditions and explore their influences on today’s business and marketing communication across relevant cultures. In particular, it uses the Aristotelian persuasive orientations as reference points to introduce the Chinese rhetoric, and interpret cultural differences in persuasion from a historical and sociocultural perspective. It has been found that Greek and Chinese rhetoric and persuasion were developed to meet the needs of the social and cultural environments and this rule still applies to today’s business communication. The logical approach has been emphasised in the English rhetorical tradition while both qing (emotional approach) and li (logical approach) are the focus of persuasion in the Chinese tradition. This difference is also the root of cultural differences in modern business communication. Findings from both English and Chinese texts and data are examined to substantiate our focal argument.