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The connection between women’s empowerment and health has been a growing concern among demographers and other social scientists, who theorize that empowering women – or enhancing their ability to define and make strategic life choices – will improve their reproductive health (Kabeer, 1999). The importance of empowering women became a central theme at the International Conference on Population and Development (ICPD) held in Cairo in 1994. The Cairo policy document codified the notion that women must be empowered in order for them and societies as a whole reach their reproductive health goals, including lowering fertility and population growth, stemming the spread of sexually transmitted diseases (STDs) and HIV/AIDS, and ensuring healthy pregnancy and delivery (Hodgson & Watkins, 1997; Sen & Batliwala, 2000).

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

We provide an overview of how artificial intelligence is transforming the identification, structuring, and prioritization of customer needs – known as the voice of the customer (VOC). First, we summarize how the VOC helps firms gain insights on using user-generated data. Second, we discuss the types of user-generated data and the challenges associated with analyzing each type of data. Third, we describe common methods, matched to the firms' goals and the structure of the data, that are used to analyze the VOC. Fourth, and most importantly, we map the methods to relevant applications, providing guidance to select the appropriate method to address the desired research questions.

Contemporary labor economics has a ready explanation for the role of job training in the labor market. The human capital framework pioneered by Becker (1962, 1993) and Mincer (1962) and now extended by many, many others sees training as an investment in productive capacity that benefits both workers and employers. Employers enhance the productivity of their firms by investing in the skills of their workers, and these productivity gains are passed on to workers in the form of higher wages. Key to all of this is the distinction between general and specific skill. According to the theory, employers will not pay for or provide general skills (i.e. those that are transferable and hence valuable to other employers), because they are averse to being “poached” by more high-wage employers. They will, however, invest in workplace-specific skills, which assure them a return on their training investments.

This paper traces the incorporation of western educational histories in the development of normal-school curricula during the late Qing Dynasty and the Republic of China (1901–1944). It uses publication networks to show how the study of comparative educational history facilitated the international circulation of knowledge in the teaching profession, and how the “uses” of educational history were shaped by larger geopolitical forces.

This paper analyzes the international exchange of texts between normal schools in China and Japan and, subsequently, between normal schools in China and the United States. A database of 107 publications in the field of western educational history that were adopted in China reveals specific patterns of textual citation, cross-reference, and canon-formation in the field of educational historiography.

With conclusions derived from a combination of social network analysis and clustering analysis, this paper identifies three broad stages in China's development of normal-school curricula in comparative educational history: “Japan as Teacher,” “transitional period” and “America as Teacher.”

Statistical analysis can reveal citation and reference patterns but not readers' understanding of the deeper meaning of texts – in this case, textbooks on the subject of western educational history. In addition, the types of publications analyzed in this study are relatively limited, the articles on the history of education in journals have not become the main objects of this study.

This paper uses both quantitative and qualitative methods to uncover the transnational circulation of knowledge in the field of comparative educational history during its formative period in China.

This study aims to uncover the constraints of automation and the affordances of augmentation related to implementing artificial intelligence (AI)-powered systems across different task types: mechanical, thinking and feeling.

Qualitative study involving 45 interviews with various stakeholders in artistic gymnastics, for which AI-powered systems for the judging process are currently developed and tested. Stakeholders include judges, gymnasts, coaches and a technology vendor.

We identify perceived constraints of automation, such as too much mechanization, preciseness and inability of the system to evaluate artistry or to provide human interaction. Moreover, we find that the complexity and impreciseness of the rules prevent automation. In addition, we identify affordances of augmentation such as speedier, fault-less, more accurate and objective evaluation. Moreover, augmentation affords to provide an explanation, which in turn may decrease the number of decision disputes.

While the unique context of our study is revealing, the generalizability of our specific findings still needs to be established. However, the approach of considering task types is readily applicable in other contexts.

Our research provides useful insights for organizations that consider implementing AI for evaluation in terms of possible constraints, risks and implications of automation for the organizational practices and human agents while suggesting augmented AI-human work as a more beneficial approach in the long term.

Our granular approach provides a novel point of view on AI implementation, as our findings challenge the notion of full automation of mechanical and partial automation of thinking tasks. Therefore, we put forward augmentation as the most viable AI implementation approach. In addition, we developed a rich understanding of the perception of various stakeholders with a similar institutional background, which responds to recent calls in socio-technical research.

This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.

The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.

Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.

The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.

For the case of many content features, This paper aims to investigate which content features in video and text ads more contribute to accurately predicting the success of crowdfunding by comparing prediction models.

With 1,368 features extracted from 15,195 Kickstarter campaigns in the USA, the authors compare base models such as logistic regression (LR) with tree-based homogeneous ensembles such as eXtreme gradient boosting (XGBoost) and heterogeneous ensembles such as XGBoost + LR.

XGBoost shows higher prediction accuracy than LR (82% vs 69%), in contrast to the findings of a previous relevant study. Regarding important content features, humans (e.g. founders) are more important than visual objects (e.g. products). In both spoken and written language, words related to experience (e.g. eat) or perception (e.g. hear) are more important than cognitive (e.g. causation) words. In addition, a focus on the future is more important than a present or past time orientation. Speech aids (see and compare) to complement visual content are also effective and positive tone matters in speech.

This research makes theoretical contributions by finding more important visuals (human) and language features (experience, perception and future time). Also, in a multimodal context, complementary cues (e.g. speech aids) across different modalities help. Furthermore, the noncontent parts of speech such as positive “tone” or pace of speech are important.

Founders are encouraged to assess and revise the content of their video or text ads as well as their basic campaign features (e.g. goal, duration and reward) before they launch their campaigns. Next, overly complex ensembles may suffer from overfitting problems. In practice, model validation using unseen data is recommended.

Rather than reducing the number of content feature dimensions (Kaminski and Hopp, 2020), by enabling advanced prediction models to accommodate many contents features, prediction accuracy rises substantially.

This paper examines the role of language in foreign subsidiary performance.

We develop hypotheses relating to the effects of language difference and its interplay with cultural distance and market size. Considering languages that can be directly used and that can be acquired by MNEs, we employ language variables representing major languages and a population of 60 home and 57 host countries to study the performance of a sample of 1,751 subsidiaries between 2002 and 2013.

Language difference is found to have a negative impact on subsidiary performance. The positive effects of cultural distance on performance become stronger when the language difference is smaller. The language effects are also more pronounced in small markets.

This study reveals that subsidiary success depends on language difference, and such effects are more pronounced in small markets. The results also suggest that MNEs need to give more attention to bridging language barriers when they invest in culturally distant countries so that they can benefit from the positive effects of cultural distance.

Given that there is no systematic research investigating the role of language in the foreign subsidiary performance of MNEs, we make an important contribution by presenting a quantitative investigation of the language–performance relationship. The novelty of the paper also lies in examining the interplay of language difference with cultural distance and market size.

The purpose of this paper is to examine how communication professionals enact an educational role aimed at improving organisational communication through communication training. Furthermore, this article analyses what this implementation means for the role of the communication professionals.

Qualitative interviews were conducted with seven communication professionals and ten managers in two organisations. The organisations were selected due to their involvement in developing and implementing communication training programmes. The interviews were then transcribed and analysed inductively.

This study demonstrates how communication professionals are expanding their professional role to become trainers in communication. The managers who participated reported increased awareness of the communication departments and the support they can provide. The communication departments became more visible in the organisations.

The study is qualitative and limited to two organisations. The managers' perspectives suggest that when communication professionals act as internal trainers, their role within an organisation is strengthened.

The results of this study indicate that in-house communication professionals enable managers to improve their communication, boosting their ability to implement simultaneous large-scale training and rendering the communication department more visible and available throughout the organisation.

This study adds to the existing discussion regarding the new roles of communication professionals in organisations by presenting two cases in which communication professionals are successfully functioning as internal communication trainers. The findings can help both researchers and practitioners gain insights into the future role of the communication profession.