Search results

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

This chapter examines the significant role of non-fungible tokens (NFTs) and blockchain technology in fostering a sustainable economy in the metaverse. Blockchain allows the saving and transfer of decentralized and secure data. As a primary component of the metaverse economy, NFTs are distinct and secure virtual assets saved on the blockchain. These assets facilitate possessing, trading, and monetizing digital assets. These advancing technologies have also revolutionized the method by which creators and artists test and exchange their digital work, introducing a novel period of ownership and value in the digital realm. However, the negative environmental effects of some blockchain technologies constitute a considerable constraint, pushing a shift to a sustainable economy. Platforms like The Sandbox have implemented initiatives to address environmental concerns. As a case study, The Sandbox play-to-earn model with tokenized assets showcases its ability to create value and encourage user participation. It shows the ability of NFTs and blockchain to support a sustainable economy.

This study aims to describe the current conceptualisation of self-management of dementia by family carers in the literature and from the views of dementia professionals and family carers, and to establish a more comprehensive concept of self-management of dementia by family carers.

A hybrid concept analysis included three phases: the theoretical phase reviewed the literature on self-management of dementia by family carers; the fieldwork phase interviewed professionals and family carers; and the analytical phase synthesised and discussed the findings from the previous two phases.

The findings revealed that self-management of dementia by family carers encompasses four domains: supporting care recipients, self-care, sustaining a positive relationship with care recipients, and personal characteristics and skills.

The findings highlighted the essential elements of the construct of self-management of dementia by family carers. The findings can be used as a conceptual framework of self-management and are useful in designing and evaluating self-management support interventions for family carers.

The Metaverse, an emergent Web 3.0 platform, offers users immersive virtual reality experiences. This study employs a case study approach to explore the concept of sustainability within the Metaverse. It examines the environmental, social, and economic implications of virtual interactions and the role of sustainable technologies in shaping user behavior and virtual economies. Through selected case studies, the research provides insights into the potential and challenges of integrating sustainable practices in the Metaverse, with implications for stakeholders ranging from policymakers to end-users.

In this chapter, we explore the dark side of the metaverse and the need for user protection. While the metaverse offers multiple opportunities it also poses significant risks for users, such as privacy concerns, addiction, harassment, and cyberbullying. First, we discuss the various threats that users may encounter such as online harassment, assaults, cyberbullying, hate speech, identity theft, and virtual property theft. As per the Center for Countering Digital Hate, an incident of violation occurs every seven minutes within VRChat, a popular virtual reality game. The level of misconduct in the metaverse can surpass the extent of internet harassment. Virtual reality gaming has been associated with various health issues like sleep deprivation, and insomnia as well as mental health concerns such as depression, anger, and anxiety. We examine how these issues may impact user’s physical and mental health. The sensors and devices used in the metaverse collect a vast amount of user biometric data and spatial data. Interactions between users and metaverse could be leaked. We examine different methods that improve user protection, including everyone from enhanced security protocols via the application of privacy-enhanced technology to several avatars, two-factor authentication, and user educational and awareness programs. Moreover, we explore how the newest technologies, like blockchain and artificial intelligence, play a role in making user safety more important. We finished the course with the study of the case of Second Life, the virtual reality gaming platform, and pointing out some of the problems that exist within it.

The purpose of this study is to identify motivations for the uptake of crowdfunding by micro-entrepreneurs in an emerging economy and the extent to which these vary by entrepreneur characteristics, sector and crowdfunding model.

The authors conduct qualitative analyses of data collected in interviews with 57 micro-entrepreneurs in Morocco, all of whom used crowdfunding in fundraising.

The authors identify six key motives for crowdfunding adoption by micro-entrepreneurs including financing needs, legitimacy seeking, sense of achievement, network-building, entrepreneurial and marketing competence enhancements. They also find evidence for moderation effects of fundraiser characteristics on likelihood of adoption, including gender, age, education, training experience and sectoral affiliation. Furthermore, the authors show that the relative importance of different motives varies by the type of crowdfunding model used.

The original aspects of the study include the examination of adoption motives in an emerging market context and the distinguishing between entrepreneurs’ adoption motives based on different gender, age, education, training experience, sectoral affiliation and crowdfunding model used. Moreover, the authors show that enhancement of competencies is a more dominant motive in the emerging market context than mentioned in earlier studies in developed contexts.

In the 21st century, libraries are experiencing a significant decline in users due to shifting reading habits and the impact of technology, necessitating library transformation and a heightened emphasis on library marketing. Special libraries, in particular, rely heavily on patrons for survival, often due to their private ownership and limited resources. This paper aims to discuss the aforementioned objectives.

This paper examines the Taste Library, a special library in Hong Kong, and analyzes its current practices based on an interview with its founder, website content, and social media presence. The 7Ps Marketing Mix model is employed to assess the strengths and weaknesses of the library's current market position.

The Taste Library's existing practices exhibit limitations in attracting young patrons. To address this issue, we propose marketing strategies focused on enhancing social network presence, offering digitized content, and engaging in school outreach.

By concentrating on youth marketing, this study offers valuable insights for special libraries in developing strategic plans for transitioning and maintaining sustainability.

Few studies concentrate on marketing small special libraries, particularly in the East, within today's digitized economy.

This study aims to investigate the relationship between prevention and panic of COVID-19 and distress tolerance, happiness and emotional intelligence (EI) in undergraduate and postgraduate accounting students in Iraq. In other words, this study seeks to answer whether or not different types of prevention and fear of COVID-19 can lead to improved distress tolerance, happiness and EI.

The study’s statistical population comprises 298 undergraduate and 138 postgraduate students in Iraq who were selected as the sample size using the Cochran sampling method. In this study, partial least squares regression (PLS) have been used to investigate the effect of independent variables on the dependent variable.

The results showed a positive and significant relationship between COVID-19 prevention and distress tolerance and happiness, but no significant relationship was observed between COVID-19 prevention and EI. Also, no significant relationship was observed between fear of COVID-19 and distress tolerance and happiness, but there was a positive and significant relationship between fear of COVID-19 and EI.

The present study’s results can provide valuable information to everyone and help the development of science and knowledge because so far, and to the best of the authors’ knowledge, no research has examined the impact of prevention and panic of COVID-19 on distress tolerance, happiness and EI in students.

Malaysian rice wines (tapai) manufactured in small-scale industries are usually formulated based on personal experiences under minimally controlled conditions for generations, especially in Sabah, one of the East Malaysian states. However, the quality and safety of rice wines were receiving increased attention to ensure better quality control, particularly those produced on an industrial scale. Therefore, this research aims to determine the fermentation dynamics and consumers’ acceptance of Malaysian rice wines produced using different sasad (a local term for starter culture from Sabah).

The physicochemical [total soluble solids (TSS), alcohol content, total titratable acidity (TTA) and pH] and microbiological [total yeast and mould count (TYMC) and total lactic acid bacteria (LAB) count] changes in Malaysian rice wines were determined to better understand the fermentation process for future process optimisation. Additionally, sensory evaluations were conducted to determine the consumers’ preferences for the rice wines.

The overall fermentation dynamics of rice wines exhibited similar trends with slight variations between the samples, demonstrating the effect of microbial compositions of sasad on the quality of final rice wines. Additionally, consumer acceptance tests showed that rice wines with darker shades of yellow and a stronger alcoholic aroma were preferable.

This is the first research that provides important insights into both the fermentation dynamics and consumers’ acceptance of Malaysian traditional rice wines, enriching the rice wine literature from the academic perspective and contributing to the production of safe and high-quality rice wines.