Search results

In this chapter we consider the “Regularization of Derivative Expectation Operator” (Rodeo) of Lafferty and Wasserman (2008) and propose a modified Rodeo algorithm for semiparametric single index models (SIMs) in big data environment with many regressors. The method assumes sparsity that many of the regressors are irrelevant. It uses a greedy algorithm, in that, to estimate the semiparametric SIM of Ichimura (1993), all coefficients of the regressors are initially set to start from near zero, then we test iteratively if the derivative of the regression function estimator with respect to each coefficient is significantly different from zero. The basic idea of the modified Rodeo algorithm for SIM (to be called SIM-Rodeo) is to view the local bandwidth selection as a variable selection scheme which amplifies the coefficients for relevant variables while keeping the coefficients of irrelevant variables relatively small or at the initial starting values near zero. For sparse semiparametric SIM, the SIM-Rodeo algorithm is shown to attain consistency in variable selection. In addition, the algorithm is fast to finish the greedy steps. We compare SIM-Rodeo with SIM-Lasso method in Zeng et al. (2012). Our simulation results demonstrate that the proposed SIM-Rodeo method is consistent for variable selection and show that it has smaller integrated mean squared errors (IMSE) than SIM-Lasso.

While the normal wheel–rail contact model cannot be accurately used for light rail transit (LRT) wheel wear analysis with large wheelset lateral displacement and wheelset yaw angle, a modified semi-Hertzian contact model (MSHM) is proposed in the paper.

MSHM was first proposed to consider the wheelset motion with the lateral displacement and the yaw angle. Then, a dynamic model of an LRT was established and the influence of some key factors on wheel wear is analyzed. At last, after operating for a certain mileage, the predicted wheel wear is compared with the tested wheel wear.

Compared with the tested wheel wear, the predicted wheel wear shows a good agreement with the measured result, verifying the accuracy of MSHM.

Considering larger wheelset lateral displacement and yaw angle, MSHM can be used to calculate the wheel wear of the LRT with high accuracy.

The purpose of this paper is to examine the relationship between patent innovation activities and foreign trade competitiveness and analyze China's level of independent knowledge innovation internationally, especially in comparison with Japan.

The approach takes the form of a statistical and econometric analysis of granted patents and trade export effect of China and Japan, based on the monthly data of foreign trade import and export and of patents granted by China's national intellectual property bureau in Japan and China, respectively, from 2004 to 2007.

Through Johansen's co‐integration test, Granger causality test and other methods, this paper verifies that a country's inventions can directly promote export trade, and its pulling effect is more visible than the total patents. Tests also manifest that the innovative activities in Japan play a more significant role in enhancing its exports than in China. Comparison of large amounts of data shows that the gap between China and Japan on independent knowledge innovation is obvious.

These imply that in the era of knowledge economy, a country's sustainable capacity for independent innovation is the key to trade and national competitiveness.

China urgently needs to build a national innovation system; make great efforts to cultivate national competitive advantage centred on knowledge advantage; and improve its overall competitive strength.

The paper assesses the importance of innovation activities represented by patents from the quantitative view and the difference of impact degree between China and Japan.

The COVID-19 pandemic has spurred a concurrent outbreak of false information online. Debunking false information about a health crisis is critical as misinformation can trigger protests or panic, which necessitates a better understanding of it. This exploratory study examined the effects of debunking messages on a COVID-19-related public chat on WhatsApp in Singapore.

To understand the effects of debunking messages about COVID-19 on WhatsApp conversations, the following was studied. The relationship between source credibility (i.e. characteristics of a communicator that affect the receiver's acceptance of the message) of different debunking message types and their effects on the length of the conversation, sentiments towards various aspects of a crisis, and the information distortions in a message thread were studied. Deep learning techniques, knowledge graphs (KG), and content analyses were used to perform aspect-based sentiment analysis (ABSA) of the messages and measure information distortion.

Debunking messages with higher source credibility (e.g. providing evidence from authoritative sources like health authorities) help close a discussion thread earlier. Shifts in sentiments towards some aspects of the crisis highlight the value of ABSA in monitoring the effectiveness of debunking messages. Finally, debunking messages with lower source credibility (e.g. stating that the information is false without any substantiation) are likely to increase information distortion in conversation threads.

The study supports the importance of source credibility in debunking and an ABSA approach in analysing the effect of debunking messages during a health crisis, which have practical value for public agencies during a health crisis. Studying differences in the source credibility of debunking messages on WhatsApp is a novel shift from the existing approaches. Additionally, a novel approach to measuring information distortion using KGs was used to shed insights on how debunking can reduce information distortions.

The purpose of this paper is to survey and consider the implications of the literature justifying the value of teaching poetry. There has been a long tradition of literature education in the English departments of Chinese universities. English Poetry courses are offered within optional literature modules in senior stages of a BA in English language and literature. In 2000, the new national syllabus for tertiary English majors was issued. This syllabus has brought the teaching of English into line with the perceived practical needs of society. As a result, poetry courses have been under threat within the degree. A substantial number of university teachers have responded to this threat with articles arguing the value of teaching of poetry.

The China National Knowledge Infrastructure (CNKI), the largest database of academic journals in China, reveals that from 2000 to 2013, 102 articles about teaching English poetry to Chinese people learning English as a foreign language were published in Chinese academic journals, of which 67 are concerned with English majors. This literature examines these 67 articles.

These articles justify the purpose of teaching English poetry, evaluate the content of poetry courses and share pedagogical strategies. The issues within this discussion fall into three categories: why teach poetry; what to teach in poetry courses; and how to teach poetry. Because the commitment of Chinese teachers to sharing their beliefs about teaching English poetry is positioned in the context of increased advocacy for the creation of inter-disciplinary market-orientated graduates, discomfort, uncertainty and the desire for change emerge in this discussion. On the other hand, teachers looking for change express caution about the costs of changing pedagogical approaches on the development of the skills of close reading and analysis of poetical texts.

This investigation of the local Chinese context resonates with and contributes to the wider discussion of the challenges faced by English literature teachers in both second- (L2) and first-language (L1) contexts and warrants examination. It is difficult to say in advance how far such knowledge could contribute to any policy decisions that may be made in the future, but it is important that the voice of teachers contributes to the larger international debate about the value of humanities in tertiary-level education.

Although the study of factors that promote employee well-being is not a new research area, the impact of managerial caring and perceived insider status on subjective employee well-being is a relatively new and unexplored area within the management literature. Therefore, this study examined the relationship between managerial caring and subjective employee well-being while considering the mediating effect of perceived insider status. Based on social identity theory, the study hypothesized that perceived insider status mediates the link between managerial caring and subjective employee well-being.

The study analyzed data from 193 employees working across various industries in the United Arab Emirates using Process Macro Model 4.

The findings revealed a positive relationship between managerial caring and employee well-being, which was influenced by the mediating effect of perceived insider status.

The study’s results, which shed light on the process by which managerial caring positively affects employee well-being, provide valuable insights for developing a caring workplace. The findings make a significant contribution to the literature on managerial caring by explaining how the mediating role of perceived insider status influences the relationship between managerial caring and subjective employee well-being.

High temperature gradient induces high residual stress, producing an important effect on the part manufacturing during laser powder bed fusion (LPBF). The purpose of this study is to investigate the effect of the molten pool mode on the thermal stress of Ti-6Al-4V alloy during different deposition processes.

A coupled thermal-mechanical finite element model was built. The developed model was validated by comparing the numerical results with the experimental data in the maximum molten pool temperature, the molten pool dimension and the residual stress described in the previous work.

For the single-track process, the keyhole mode caused an increase in both the maximum stress and the high-stress area compared with the conduction mode. For the multitrack process, a lower tensile stress around the scanning track and a higher compressive stress below the scanning track were found in the keyhole mode. For the multilayer process, the stress along the scanning direction at the middle of the part changed from tensile stress to compressive stress with the increase in the deposition layer number. As the powder layer number increased, the stress along the scanning direction near the top surface of the part decreased while the stress along the deposition direction obviously increased, indicating that the stress along the deposition direction became the dominant stress. The keyhole mode can reduce the residual stress near the top of the part, and the conduction mode was more likely to produce a low residual stress near the bottom of the part.

The results provide a systematic understanding of thermal stress during the LPBF process.

Carbon dioxide (CO₂) has attracted special scientific interest over the last years mainly because of its relation to climate change and indoor air quality. Except for this, CO₂ can be used as an indicator of food freshness, patients’ clinical state and fire detection. Therefore, the accurate monitoring and controlling of CO₂ levels are imperative. The development of highly sensitive, selective and reliable sensors that can efficiently distinguish CO₂ in various conditions of temperature, humidity and other gases’ interference is the subject of intensive research with chemi-resistive zinc oxide (ZnO)-based sensors holding a privileged position. Several ZnO nanostructures have been used in sensing applications because of their versatile features. However, the deficient selectivity and long-term stability remain major concerns, especially when operating at room temperature. This study aims to encompass an extensive study of CO₂ chemi-resistive sensors based on ZnO, introducing the most significant advances of recent years and the best strategies for enhancing ZnO sensing properties.

An overview of the different ZnO nanostructures used for CO₂ sensing and their synthesis methods is presented, focusing on the parameters that highly affect the sensing mechanism and, thus, the performance of CO₂ sensors.

The selectivity and sensitivity of ZnO sensors can be enhanced by adjusting various parameters during their synthesis and by doping or treating ZnO with suitable materials.

This paper summarises the advances in the rapidly evolving field of CO₂ sensing by ZnO sensors and provides research directions for optimised sensors in the future.

A core challenge in background subtraction (BGS) is handling videos with sudden illumination changes in consecutive frames. In our pilot study published in, Sakkos:SKIMA 2019, we tackle the problem from a data point-of-view using data augmentation. Our method performs data augmentation that not only creates endless data on the fly but also features semantic transformations of illumination which enhance the generalisation of the model.

In our pilot study published in SKIMA 2019, the proposed framework successfully simulates flashes and shadows by applying the Euclidean distance transform over a binary mask generated randomly. In this paper, we further enhance the data augmentation framework by proposing new variations in image appearance both locally and globally.

Experimental results demonstrate the contribution of the synthetics in the ability of the models to perform BGS even when significant illumination changes take place.

Such data augmentation allows us to effectively train an illumination-invariant deep learning model for BGS. We further propose a post-processing method that removes noise from the output binary map of segmentation, resulting in a cleaner, more accurate segmentation map that can generalise to multiple scenes of different conditions. We show that it is possible to train deep learning models even with very limited training samples. The source code of the project is made publicly available at https://github.com/dksakkos/illumination_augmentation

In this study, the authors use the term “e-quality” to refer to information quality, system quality and service quality. This study aims to focus on e-quality, exploring and comparing users' perceptions of digital libraries and virtual communities in the hope that the results of this study can help lead to better understanding of the exact nature of e-quality as perceived by users.

A large-scale survey was conducted for data collection. Data collected from 334 users of digital libraries and virtual communities were used for data analysis.

The study finds that users are likely to perceive a higher level of information quality, system quality and service quality of digital libraries than of virtual communities.

The authors suggest that librarians do not need to have concerns over the challenge brought by virtual communities, which indeed have an increasing impact on the way a lot of people seek and gather information. Instead, they should encourage their users to use both digital libraries and virtual communities. The authors believe that the usage of these two types of information sources by users can efficiently inform each other, thus facilitating the e-quality of both digital libraries and virtual communities to reach excellence.

Building on the information systems (IS) success model, this study explores and compares users' perceptions of digital libraries and virtual communities in terms of e-quality, which the authors think presents a new view for digital library research and practice alike.