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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 research aimed to capture undergraduate students' experiences in the transition from face-to-face (F2F) learning to online learning. This study explored their perceptions regarding the effectiveness of online learning in their academic lives, challenges encountered and suggestions for enhancing online learning in the post-COVID-19 era.

This study employed a concurrent mixed-methods research design and selected 118 undergraduate students using a multistage random sampling technique from four colleges in Assam. Standardized questionnaires and open-ended interview schedules were used.

Undergraduate students reported a positive attitude and satisfaction with online learning, valuing its adaptability to their schedules, its role as a motivating factor for self-learning, its effect on making them more technically proficient and enhancing their communication skills to articulate their thoughts. However, the challenges identified by the students have the potential to overshadow the promises of online learning. This research provided more constructive suggestions under the themes of “content delivery”, “systemic and infrastructural issues”, “pedagogy” and “capacity building” to enhance their experiences with online learning.

Our research findings would assist educational institutions in adopting innovative approaches for simpler and more efficient online learning experiences post-COVID-19 pandemic. Institutions should prepare themselves and design dual-mode courses for F2F and online learning.

The paper addressed a relevant topic in this era of online learning by examining undergraduate students’ viewpoints that added complementary information to the current body of literature on online learning in rural India. The insights gleaned from their experiences would be beneficial for the development of best practices for online learning in the coming decades.

This research aims to investigate the leadership strategies employed by two higher education institutions in Malaysia as they navigated the shift to online delivery of their computer science programs in response to the demands of Education 4.0.

A phenomenological, comparative case study approach was used to delve into the leadership and management practices of these institutions during the transition to online learning. Data were collected through interviews and document analysis.

This study explores the leadership strategies employed by two higher education institutions in Malaysia during their transition to online learning due to the COVID-19 pandemic. Five key themes emerged from the data: leadership and team coordination, training and skill development, adaptation to new assessment methods, resource management and work culture and environment. Both institutions demonstrated effective leadership, continuous training and adaptability in assessment methods. However, differences were noted in resource management and work culture. Institution A's leader had to liaise with various departments and personally invest in equipment, while Institution B was already well-equipped. The work culture at Institution A demonstrated flexibility and mutual understanding, while Institution B used key performance indicators to measure progress. Despite these differences, both leaders successfully managed the shift to online teaching, underscoring the importance of effective leadership, continuous training, flexibility, resource management and a supportive work culture in managing change. The study also highlighted the distinct roles of curriculum leaders in both institutions, with Institution A's leader focusing on multiple activities, while Institution B's leader was able to focus solely on curriculum change due to their institution's preparedness.

This study provides a rich, qualitative exploration of the strategies and challenges faced by program leaders in managing the shift to online teaching during the COVID-19 pandemic. Future research could build on these findings by conducting similar studies in other educational contexts or countries to compare and contrast the strategies and challenges faced by program leaders. Additionally, future research could also employ quantitative methods to measure the effectiveness of different strategies in managing the shift to online teaching. This could provide a more comprehensive understanding of the factors that contribute to successful change management in educational institutions.

This study provides valuable insights for program leaders, educators and policymakers in managing change in educational institutions. The themes identified in this study – effective leadership, continuous training and skill development, flexibility in adapting to new assessment methods, effective resource management and a supportive work culture and environment – can serve as a guide for program leaders in managing future changes in their institutions. Moreover, the strategies employed by the program leaders in this study, such as forming a powerful coalition, providing training on online tools and prioritizing student welfare, can be adopted or adapted by other program leaders in managing change.

This study presents a unique contribution to the existing literature by offering a comparative analysis of change management strategies in two distinct educational institutions during the shift to online teaching due to the COVID-19 pandemic. It uncovers the nuanced differences in leadership styles, resource management and pedagogical adaptations, providing a rich, context-specific understanding of the change process. The study fills a research gap by examining the practical application of Kotter's 8-Step Change Model and the McKinsey 7S Model in real-world educational settings. The findings offer valuable insights for other institutions navigating similar changes, thereby extending the practical and theoretical understanding of change management in higher education.

The purpose of this paper is to propose a new deep learning-based model to carry out better maintenance for naval propulsion system.

This model is constructed by integrating different deep learning algorithms. The basic idea is to change the connection structure of the deep neural network by introducing a residual module, to limit the prediction output to a reasonable range. Then, connect the Deep Residual Network (DRN) with a Generative Adversarial Network (GAN), which helps achieve data expansion during the training process to improve the accuracy of the assessment model.

Study results show that the proposed model achieves a better prediction effect on the dataset. The average performance and accuracy of the proposed model outperform the traditional models and the basic deep learning models tested in the paper.

The proposed model proved to be better performed naval propulsion system maintenance than the traditional models and the basic deep learning models. Therefore, our model may provide better maintenance advice for the naval propulsion system and will lead to a more reliable environment for offshore operations.

This culminating chapter reviews the impacts of the pandemic on global systems of education. Drawing on the insights of the preceding chapters, this chapter offers three ideas for the future. First, schools of education should engage in innovative learning experiences including in person, online and hybrid learning opportunities. Second, staff support and development are key areas for future growth. Similarly, the third area for future growth is deeper consideration of student well-being and development. The pandemic placed these ideas at the forefront of conversation, and schools of education are positioned to continue that conversation, taking action to create transformative educational experiences.

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead to instability of emerging markets. The study covers a sample of five geographical areas of emerging economies, including Mexico, Korea, South Africa, Turkey, and Malaysia. It used the backward multiple‐regression technique to examine the relationship between monthly changes of stock price indices as dependent variable and the associated predicting local as well as international variables, which represent possible causes of increasing price volatility and initiating crises in emerging stock markets. The study covered monthly data for a period of forty‐eight months from January 1997 to December 2000. The study revealed that stock trading volume and currency exchange rate respectively represent the highest positive correlation to the emerging stock price changes; thus represent the most predicting variables of increasing price volatility. International stock price index, deposit interest rate, and bond trading volume were moderate predicting variables for emerging stock price volatility. While changes in inflation rate showed the least positive correlation to stock price volatility, thus represents the least predicting variable.

The former residences of historical figures are typical landscape elements of historic districts, which are characterised by the styles of these residences and spiritual historical figures cultures. The purpose of this paper is to determine how the former residences respond once the historical figures living there have passed.

The history of human culture and progression of urban construction – which are submerged in societal transformation – is recorded for old Beijing city. Narrative space theory is used and methods such as a content analysis, map overlay and the Geographic Information System are employed to analyse the selected 300 former residences of historical figures in old Beijing city.

The results are as follows: the political setting played a key role in the evolution process, three political narrative areas in the inner city and one cultural narrative area in the outer city form the narrative spatial structure of the former residences of historical figures, “government construction” and “resident construction” are the main reasons for the loss and destruction of narrative spaces and ordinary life is an important channel for showcasing the history of former residences. The narrative spaces of these residences carry double histories, namely, the development of human history and of city construction.

Different from former studies that focus on the preservation of the single historical building, this study explores the integral logic of historic buildings in the whole city through narrative space theory to get a combination of culture and space.

The purpose of this study is to develop a manufacturing technology using hybrid selective laser melting/hot isostatic pressing (SLM/HIP) process to produce full density net-shape components more rapidly and at lower cost than processing by SLM alone.

Ti-6Al-4V powder was encapsulated in situ by the production of as-SLMed shell prior to the HIP process. After HIPping, the SLM shell is an integral part of the final component. Finite element (FE) modelling based on pure plasticity theory of porous metal coupled with an iterative procedure has been adopted to simulate HIPping of the encapsulated Ti-6Al-4V powder and SLMed shell. Two demonstrator parts have been modelled, designed, produced and experimentally validated. Geometrical analysis and microstructural characterisation have been carried out to demonstrate the efficiency of the process.

The FE model is in agreement with the measured data obtained and confirms that the design of the shell affects the resulting deformed parts. In addition, the scanning electron microscope (SEM) and Electron backscatter diffraction EBSD (EBSD) of the interior and exterior parts reveal a considerably different grain structure and crystallographic orientation with a good bonding between the SLMed shell and HIPped powder.

An approach to improve SLM productivity by combining it with HIP is developed to further innovate the advanced manufacturing field. The possibility of the hybrid SLS/HIP supported by FEA simulation as a net shape manufacturing process for fabrication of high performance parts has been demonstrated.