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1 – 10 of 361Dangshu Wang, Jiaan Yi, Luwen Song, Xuan Deng, Xinxia Wang and Zhen Dong
This paper aims to solve the problems of large hard switching loss and unclear resonant parameter design in the existing inverter power supply topology.
Abstract
Purpose
This paper aims to solve the problems of large hard switching loss and unclear resonant parameter design in the existing inverter power supply topology.
Design/methodology/approach
This paper proposes a simple and reliable two-stage isolated inverter composed of series quasi-resonant push-pull and external freewheeling diode full-bridge inverter. The power supply topology is analyzed, the topology mode is analyzed, the mathematical model of the converter is established and the DC gain of the converter is deduced. The relationship between the load and the output gain of the resonant tank is presented, a new resonant parameter design method is proposed, and the parameter design of the resonant element of the converter is clarified.
Findings
The resonant components of the converter are designed according to the proposed resonant parameter design method, and the correctness of the method is verified by simulation and the development and testing of a 500 W experimental prototype. After experimental tests, the peak efficiency of the experimental prototype can reach 94%. Because the experimental prototype achieves soft switching, the heat generation of the switch is greatly reduced, so the heavy heat sink is removed, and the volume is reduced by about 30% compared with the traditional power supply, and the total harmonic distortion of the output voltage is about 2%.
Originality/value
The feasibility of the scheme is verified by experiments, which is of great significance for improving the efficiency of the inverter power supply and parameter optimization.
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Dilpreet Kaur Dhillon and Kuldip Kaur
The growth of the Indian economy is accompanied by the rising trend of energy utilisation and its devastating effect on the environment. It is vital to understand the nexus…
Abstract
Purpose
The growth of the Indian economy is accompanied by the rising trend of energy utilisation and its devastating effect on the environment. It is vital to understand the nexus between energy utilisation, climate and environment degradation and growth to devise a constructive policy framework for achieving the goal of sustainable growth. This study aims to analyse the long- and short-run association and direction of association between energy utilisation, carbon emission and growth of the Indian economy in the presence of structural break.
Design/methodology/approach
The study probes the association and direction of association between variables at both aggregate (total energy utilisation, total carbon emission and gross domestic product [GDP]) and disaggregates level (coal utilisation and coal emission, oil utilisation and oil emission, natural gas utilisation and natural gas emission along with GDP) over the time period of 50 years, i.e. 1971–2020. Autoregressive distributed lag model is used to examine the association between the variables and presence of structural break is confirmed with the help of Zivot–Andrews unit root test. To check the direction of association, vector error correction model Granger causality is performed.
Findings
Aggregate carbon emissions are affected positively by aggregate energy consumption and GDP in both short and long run. Bidirectional causality exists between total emissions and GDP, whereas a unidirectional causality runs from energy consumption towards carbon emission and GDP in the long run. At disaggregate level, consumption of coal energy impacts positively, whereas GDP influences coal emission negatively in the long run only. Furthermore, consumption of oil and GDP influences oil emissions positively in the long run. Lastly, natural gas is the energy source that has the fewest emissions in both short and long run.
Originality/value
There is a rapidly growing body of research on the connections and cause-and-effect relationships between energy use, economic growth and carbon emissions, but it has not conclusively proved how important the presence of structural breaks or changes within the economy is in shaping the outcomes of the aforementioned variables, especially when focusing on the Indian economy. By including the impact of structural break on the association between energy use, carbon emission and growth, where energy use and carbon emission are evaluated at both aggregate and disaggregate level, the current study aims to fill this gap in Indian literature.
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Qi Kang, Carlos E. Carpio, Chenggang Wang and Zeng Tang
This research examined the impacts of diversified income from trading caterpillar fungus on pastoral households' livestock production and income. The specific objectives were to…
Abstract
Purpose
This research examined the impacts of diversified income from trading caterpillar fungus on pastoral households' livestock production and income. The specific objectives were to identify the main factors underlying participation in caterpillar fungus trade and to explore the impacts of a diversified income from trading fungus on livestock production activities and income.
Design/methodology/approach
Data were collected from a pastoral household survey (n = 503) in five Tibetan Autonomous Prefectures. The authors employed propensity score matching (PSM) procedures to estimate the effects of participation in trading caterpillar fungus.
Findings
Pastoral households participating in caterpillar fungus activities maintain smaller herds, sell fewer animals for profit, slaughter more livestock for family consumption and experience fewer livestock deaths compared to nonparticipants. There is also some evidence that pastoral households participating in caterpillar fungus activities have a higher annual income compared to nonparticipants.
Research limitations/implications
A direct measure of grassland degradation was not included due to the data limitation. The estimated average treatment effects could differ under different observed households' characteristics.
Originality/value
This study fills a gap in the literature on the impacts of diversified income on livestock production activities. The authors provide a new perspective on the controversy over the extraction of caterpillar fungus. This study contributes to exploring the dual role of income diversification in addressing poverty and grassland resource degradation for Tibetan pastoral communities.
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Yi-Kang Liu, Xin-Yuan Liu, E. Deng, Yi-Qing Ni and Huan Yue
This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the…
Abstract
Purpose
This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the stress intensity factors (SIFs) at the crack tip.
Design/methodology/approach
A computational fluid dynamics (CFD) model is used to calculate the aerodynamic pressure exerted on two cracked surfaces. The simulation uses the viscous unsteady κ-ε turbulence model. Using this CFD model, the spatial and temporal distribution of aerodynamic pressure inside longitudinal, oblique and circumferential cracks are analyzed. The mechanism behind the pressure variation in tunnel lining cracks is revealed by the air density field. Furthermore, a response surface model (RSM) is proposed to predict the maximum SIF at the crack tip of circumferential cracks and analyze its influential parameters.
Findings
The initial compression wave amplifies and oscillates in cracks in tunnel linings, resulting from an increase in air density at the crack front. The maximum pressure in the circumferential crack is 2.27 and 1.76 times higher than that in the longitudinal and oblique cracks, respectively. The RSM accurately predicts the SIF at the crack tip of circumferential cracks. The SIF at the crack tip is most affected by variations in train velocities, followed by the depth and length of the cracks.
Originality/value
The mechanism behind the variation of aerodynamic pressure in tunnel lining cracks is revealed. In addition, a reliable surrogate model is proposed to predict the mechanical response of the crack tip under aerodynamic pressures.
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Andrea Lucherini and Donatella de Silva
Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings…
Abstract
Purpose
Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings are particularly complex materials to be modelled and predicted, which can be extremely useful especially for performance-based fire safety designs. In addition, many parameters influence their performance, and this challenges the definition and quantification of their material properties. Several approaches and models of various complexities are proposed in the literature, and they are reviewed and analysed in a critical literature review.
Design/methodology/approach
Analytical, finite-difference and finite-element methods for modelling intumescent coatings are compared, followed by the definition and quantification of the main physical, thermal, and optical properties of intumescent coatings: swelled thickness, thermal conductivity and resistance, density, specific heat capacity, and emissivity/absorptivity.
Findings
The study highlights the scarce consideration of key influencing factors on the material properties, and the tendency to simplify the problem into effective thermo-physical properties, such as effective thermal conductivity. As a conclusion, the literature review underlines the lack of homogenisation of modelling approaches and material properties, as well as the need for a universal modelling method that can generally simulate the performance of intumescent coatings, combine the large amount of published experimental data, and reliably produce fire-safe performance-based designs.
Research limitations/implications
Due to their limited applicability, high complexity and little comparability, the presented literature review does not focus on analysing and comparing different multi-component models, constituted of many model-specific input parameters. On the contrary, the presented literature review compares various approaches, models and thermo-physical properties which primarily focusses on solving the heat transfer problem through swelling intumescent systems.
Originality/value
The presented literature review analyses and discusses the various modelling approaches to describe and predict the behaviour of swelling intumescent coatings as fire protection for structural materials. Due to the vast variety of available commercial products and potential testing conditions, these data are rarely compared and combined to achieve an overall understanding on the response of intumescent coatings as fire protection measure. The study highlights the lack of information and homogenisation of various modelling approaches, and it underlines the research needs about several aspects related to the intumescent coating behaviour modelling, also providing some useful suggestions for future studies.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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Hamid Reza Saeidnia, Elaheh Hosseini, Shadi Abdoli and Marcel Ausloos
The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the…
Abstract
Purpose
The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.
Design/methodology/approach
By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.
Findings
(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.
Originality/value
This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.
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Wei Liu, Zongshui Wang, Ling Jian and Zhuo Sun
This study applies parasocial relationship theory to identify the role of broadcaster characteristics in the highly interactive business setting of live streaming commerce.
Abstract
Purpose
This study applies parasocial relationship theory to identify the role of broadcaster characteristics in the highly interactive business setting of live streaming commerce.
Design/methodology/approach
A total of 401 online questionnaires were distributed to individuals with live streaming showroom shopping experience, and SmartPLS software was used to analyse the data and test the hypotheses.
Findings
Broadcasters' characteristics are positively associated with viewers' parasocial relationships, thus further enhancing viewers' attitudinal and behavioural loyalty towards that broadcaster's streams. Parasocial relationships mediate the effects of most broadcaster characteristics (except for expertise) on attitudinal and behavioural loyalty. In addition, parasocial relationships have a stronger positive effect on viewer behaviours for hedonic products and under high match-up.
Originality/value
The broadcaster is a key indicator of the success of live streaming commerce. This study establishes a well-organized framework to understand how broadcaster characteristics influence viewer loyalty towards that broadcasters' streams based on parasocial relationship theory.
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Lifu Li, Kyeong Kang, Anqi Zhao and Yafei Feng
Although prior studies have studied the relationship between online consumers' attitudes and buying behaviour, the research focussing on online consumers' impulse buying…
Abstract
Purpose
Although prior studies have studied the relationship between online consumers' attitudes and buying behaviour, the research focussing on online consumers' impulse buying behaviours and exploring the role of celebrity endorsement is limited. Drawing on the social presence and the social facilitation theory, this paper establishes a research model based on the stimuli–organism–response (S–O–R) model and the motivation theory. It explores how live streamers impact online consumers' impulse buying behaviours under specific social and cultural backgrounds, with celebrity endorsement as a moderating variable.
Design/methodology/approach
To test the research model, the online questionnaire method has been conducted in this study. This paper utilises Chinese online consumers as samples and promotes an online survey. Using the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), 433 valid questionnaires have been analysed on SmartPLS.
Findings
First, live streamers' attractive appearance positively correlates with online consumers' hedonic attitude and positively impacts their utilitarian attitude to live shopping. Second, live streamers' real-time interaction positively affects consumers' utilitarian attitudes because of their professional marketing and communication skills. Third, their hedonic and utilitarian attitudes positively influence online consumers' impulse buying behaviours. Finally, this paper presents that celebrity endorsement negatively moderates the relationship between online consumers' hedonic attitudes and impulse buying during live shopping.
Originality/value
This research combines the S–O–R model and the motivation theory and analyses related social influencing factors to study online consumers' impulse buying behaviours. Meanwhile, it explores the celebrity endorsement factor as a moderate role and identifies the different effects between live streamers and celebrities in live shopping, which is of great significance to the strategy of live shopping marketing and the literature on online consumers' behaviours.
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Wei-Zhen Wang, Hong-Mei Xiao and Yuan Fang
Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing…
Abstract
Purpose
Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.
Design/methodology/approach
The proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.
Findings
The experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.
Originality/value
The proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.
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