Fuzhou Melbourne Polytechnic

Abstract Metalens, a metasurface with a focusing phase, has been the focus of research due to its immense potential for use in imaging and display technology. Traditional lens and optical imaging systems rely on phase accumulation, however metalens with subwavelength structures provide a disruptive path for miniaturized optical imaging systems by allowing unfettered modulation of incident light's phase and amplitude. Recently, extensive efforts have been devoted to exploring new design strategies, new functionalities, and possible applications. This paper reviews the development, principle, classification, and research status of metalens. In particular, this review focuses on the progress and challenges of improving imaging quality and expanding imaging diversity, including improvements of resolution, enhancement of depth of field, extension of field of view, and achromatism. Lastly, the prospects of metalens in the future display are summarized, and the application potentials of metalens in novel 3D display, intelligent and bionic display, as well as nano‐pixelate light‐emitting display (NLED) are emphasized.

The importance of organizational ambidexterity was stressed in different fields of management. This study was using a distinct method to measure the differences in the degree of ambidexterity to bridge the gap with the previous studies and to provide more insights in the successful management of exploitation and exploration. This study surveyed Taiwanese small and medium-sized enterprises (SMEs) to test the hypotheses. We issued 1000 questionnaires in total and received 234 valid ones. Results indicate exploitative and explorative capabilities exerting non-linear effect on performance. Likewise, ambidexterity and its interaction with market orientation have positive influence on firm performance. This study used structural equation modeling to analyze data, as this approach is known to be particularly advantageous for the exploratory nature of this study. We also used hierarchical regression analysis to test interaction and moderating effects. The study contributes to the literature in two ways. First, we offer a clearer understanding of the complete concept of social capital, including inter-firm and intra-firm social capital, and how contributes to improving and extending existing exploitative capabilities. Second, this study outlines how market orientation can have different effects on an ambidextrous strategy that is adopted to improve Taiwanese SMEs performance.

Drawing on integrated concepts of marketing strategy and destination image, this study proposes and develops a model of antecedent and consequence behaviour for sustainable tourism. A survey of 505 tourists was conducted. In the antecedent model, perceived risk may indirectly affect travel behaviour through psychological involvement and destination image. In the consequence model, we found that marketing strategy was related to increased destination impression and thus enhanced sustainable tourism intention. Specifically, it is not surprising that in a big data environment, new technology sharing may also enhance the positive evaluation of destinations that encourage sustainable behaviour.

For a greener society, good corporate environmental information disclosure is crucial. This study empirically examines the influence of media attention and state-owned equity, and their interaction on corporate environmental information disclosure by A-share heavily polluting firms in the Shanghai and Shenzhen stock markets from 2015 to 2019. The results show that state-owned equity can improve the level of corporate environmental information disclosure; however, it mainly affects financial environmental information disclosure. Media attention also improves the level of corporate environmental information disclosure, but only for non-financial environmental information. Moreover, media attention and state-owned equity have a certain substitution effect on environmental information disclosure: a higher state-owned equity ratio weakens the positive effect of media attention on environmental information disclosure. To improve environmental information disclosure, the government must clarify disclosure standards to improve the comparability of environmental information. In addition, media and shareholders can fully leverage their external and internal supervisory roles to promote the environmental responsibilities of firms. Our findings can be useful for further promoting corporate environmental information disclosure and developing relevant policies.

The world is facing enormous challenge of climate change and global warming due to increased emission level. In order to overcome such challenges, economies are adopting energy efficient techniques to control the carbon emissions and improves environmental sustainability. This study analyses the influencing factors of environmental quality from a global perspective throughout the last three decades. In this regard, advanced time series approaches are used to identify the association between factors such as economic growth, energy efficiency (E.N.E.F.), and carbon emissionscovering global data over the period 1990Q 4 -2020Q 4 . From the time series methods, this study observed the stationarity of all variables at first difference. The empirical outcomes also validates the long-run equilibrium relationship between the variables. Due to asymmetric distribution of the variables, this study uses the novel Quantile-on-Quantile (Q.Q.) regression approach, which reveals that increasing economic growth harms environmental quality by increasing the carbon emissions level. However, E.N.E.F. is a prominent factor of environmental sustainability, that reduces the level of carbon emissions in the atmosphere. Employing the pairwise Granger causality test, this study observed the unidirectional causality from economic growth to carbon emissions, while a two-way causal nexus is found between economic growth -E.N.E.F. and E.N.E.F.carbon emissions. Based on the empirical results, this study suggests that economic growth should be regulated in a sense that it contribute towards the improvement of E.N.E.F., which ultimately leads to reduce the emissions level and promote environmental sustainability.

With the popularity of the Internet and mobile terminals, the development of e-commerce has become hotter. Therefore, e-commerce research starts to focus on the statistics and prediction of the cargo volume of logistics. This study briefly introduced the back-propagation (BP) neural network model and principal component analysis (PCA) method and combined them to obtain an improved PCA-BP neural network model. Then the traditional BP neural network model and the improved PCA-BP neural network model were used to perform the empirical analysis of the cold chain logistics demand of fruits and vegetables in city A from 2010 to 2018. The results showed that the main factors that affected the local cold chain logistics demand were the growth rate of GDP, the added value of primary industry, the planting area of fruits and vegetables, and the consumption price index of fruits and vegetables; both kinds of neural networks model could effectively predict the cold chain logistics demand, but the predicted value of the PCA-BP neural network model was more fitted with the actual value. The prediction error of the BP neural network model was larger, and the fluctuation was obvious within the prediction interval. Moreover, the time required for the prediction by the PCA-BP neural network model was less than that by the BP neural network model. In summary, the improved PCA-BP neural network model is faster and more accurate than the traditional BP model in predicting the cold chain logistics demand.

Abstract This study explores the relationship between economic, social, and governance (ESG) activities and initial public offering (IPO) price stabilisation actions using IPOs listed on the Hong Kong stock exchange between 2004 and 2021 as samples. We find that IPO issuers that actively conduct ESG activities have higher ESG scores, which enhances price stabilisation. Furthermore, ex‐ante volatility serves as a potential channel through which ESG activities affect price stabilisation. Providing ethical and economic implications for companies, policymakers, and investors, our findings suggest that ESG activities are vital drivers of price stabilisation.

Temporal knowledge graph (TKG) embedding has received increasing attention in the academia. However, most existing methods are extensions of traditional translation models. Due to their intrinsic limitations, it is often difficult for such methods to effectively model essential characteristics of TKG, namely three basic relation patterns including symmetry/antisymmetry, inversion, and composition. In this paper, a new 3-Dimensional Rotation Temporal Embedding (3DRTE) method is proposed. Firstly, we selectively fuse temporal and relational features of fact triples by taking advantages of self-attention mechanism in processing sequential information. Then, entities are modelled as points in three-dimensional space, and the relations are interpreted as two isoclinic rotations between entities with Quaternion. Experimental results on several public datasets show that our method obtains state-of-the-art results.

Graph embedding models are widely used in knowledge graph completion (KGC) task. However, most models are based on the assumption that knowledge is completely certain, and this is inconsistent with real-world situations. Although there are multiple studies on uncertain knowledge embedding tasks, they often use knowledge confidence to learn embedding and cannot make full use the structural and uncertain information of knowledge. This paper presents a new embedding model named Structural and Uncertain Knowledge Embedding (SUKE), which comprises two components: an evaluator and a confidence generator. For unknown triples, the evaluator learns the structural and uncertain information to evaluate its rationality and obtain a candidate set. The confidence generator then determines the confidence of the candidate set to achieve KGC. To verify the effectiveness of the proposed model, confidence prediction, triple evaluation, and fact classification tasks are performed on three data sets. Experimental results show that SUKE performs better than mainstream embedding methods. The model proposed in this paper can help advance the research on the embedding of uncertain knowledge graphs.

E-commerce has grown rapidly due to the impact of the Covid-19. After combing theoretical studies, it was found that some scholars have verified the effects of the product information display on consumers' purchase intention. The mainly product information display methods are graphic, short video and live-streaming on current e-commerce platforms. Although with the explosion of product information and the popularity of the new form of live e-commerce, which product information display method can stimulate consumers' purchase intention more effectively? This study was conducted by means of an experiment. It was found that male consumers' purchase intentions are more likely to be influenced by live-streaming, followed by short videos, and finally by graphics.

The ecological benefit of forest has an important influence on the sustainable development of society, thus, forest management has become a critical strategic action. Forest preservation is an inclusive process which depends on collaboration among a wide range of stakeholders. Forestry companies, who own and manage forest resources, are responsible for forest preservation and ecological construction, which is called corporate ecological environmental responsibility (CEER). Most existing analyses, however, were limited to corporate environmental responsibility (CER) and ignored the ecological responsibility of forestry enterprises. Therefore, in order to better play the role of forestry companies in forest preservation, it is urgent to define the content and the measurement of CEER. This paper established a CEER index system based on the characteristics of forestry enterprises. Furthermore, evaluated the CEER level of forestry enterprises using the combined evaluation method based on the GINI criterion, which is more effective and reasonable. It is found that forestry ecological environmental responsibility emphasizes ecological improvement and has shifted from traditional environmental protection to ecological construction. Qingshan Paper, Sun Paper, and Yong’an Forestry perform the best in CEER among all forestry companies. In addition, the results showed a low level but an obvious upward trend in forestry CEER and a noticeable heterogeneity in the performance of CEER in different forestry industries. Our findings can be useful for further promoting the ecological benefits of forest companies and developing relevant policies.

Purpose: This study aims to determine the influence of Foreign Direct Investments (FDI) on economic growth in Sub-Saharan Africa (SSA). It examines the endogenous growth theory and the Environmental Kuznets Curve (EKC) theory, and how they relate to the regional data.Method: Using panel quantile autoregression models, this study explores the relationship between FDI inflows into SSA with energy consumption, carbon emissions, and economic growth. The study is based on data from 1975 to 2018.Result: The study findings conclusively demonstrate that foreign direct investment has a significant impact on the economic growth of the SSA region. Furthermore, the study reveals that energy consumption and carbon emissions in the SSA have consistently increased throughout the study period, with foreign direct investment being identified as the primary driver of this trend. These findings are consistent with the Environmental Kuznets Curve (EKC) hypothesis, as well as the endogenous growth theory, which suggests that FDI operations can have negative consequences on the host environment.Practical Implications for Economic Growth and Development: The study suggests that Sub-Saharan Africa should manage FDI carefully to balance economic growth with environmental sustainability by promoting green investments and creating an investment-friendly environment.

Characteristic hotels often rely on the development of cultural and commercial cycle. The recognition, absorption and utilization degree of the local cultures by the operators will have an influence on the organizational performance. The empirical research on Three Lanes and Seven Alleys in Fuzhou and its surrounding areas has proved that the characteristic hotels can promote the accumulation of cognitive capital through the knowledge transfer of the operators, and the positive influence can be produced on the organizational performance of the characteristic hotels with the cognitive capital as an intermediary. The scientific grasping of knowledge transfer and cognitive capital by the related companies will be conductive to improving the organizational performance and promoting the development of the characteristic hotel industry.

Addressing the current issue of limited control methods for badminton serving devices, this paper proposes a vision-based multimodal control system and method for badminton serving. The system integrates computer vision recognition technology with traditional control methods for badminton serving devices. By installing vision capture devices on the serving device, the system identifies various human body postures. Based on the content of posture information, corresponding control signals are sent to adjust parameters such as launch angle and speed, enabling multiple modes of serving. Firstly, the hardware design for the badminton serving device is presented, including the design of the actuator module through 3D modeling. Simultaneously, an embedded development board circuit is designed to meet the requirements of multimodal control. Secondly, in the aspect of visual perception for human body recognition, an improved BlazePose candidate region posture recognition algorithm is proposed based on existing posture recognition algorithms. Furthermore, mappings between posture information and hand information are established to facilitate parameter conversion for the serving device under different postures. Finally, extensive experiments validate the feasibility and stability of the developed system and method.

For the development of agricultural modernization, an automatic recognition network for crop diseases with the advantages of high efficiency, non-destructiveness and continuity is indispensable. In this paper, we construct a 13-layers convolutional neural network for common citrus diseases recognition, which improving the efficiency and reducing overfitting by using a stack of small kernel and dropout, etc. Finally, we conduct comparative experiments with other networks. The experiment results show that the performances of our network are better than CNN and AlexNet. It indicates that the network we constructed is an effective citrus diseases recognition method, which can provide technical support for the identification and prevention of citrus diseases.

The teaching objective of business English is not only to strengthen students’ English proficiency level but also to train students’ practical ability. Traditional teaching has many problems, such as emphasizing theory over practice. By analyzing the situation of teaching business English courses, we aim to establish a teaching model and multi-evaluation model with the Internet and mobile terminals. Through the effective application of information technology, the guiding role of teachers is highlighted to overcome the time and space limitations and achieve the integration of knowledge learning and practice. The use of information technology in teaching business English courses improves students' practical ability for business activities in the business context and thus promotes he improvement of the teaching quality.

The concepts of the system collaboration and coordination are confused in the theoretical cycle. The concepts of collaboration and coordination and the difference and connection between them are analyzed, and six dialectical relationships are proposed: Collaboration emphasizes cooperative behavior and coordination emphasizes state or relationship; Collaboration emphasizes multi-win-win situation and coordination emphasizes equilibrium and overall optimization; Coordination is of external nature, and collaboration is of internal nature; From coordination to collaboration, coordination is the means to achieve collaboration; Coordination which can drive collaboration is the guarantee of system collaborative precession; Collaboration which can promote coordination is the inevitable requirement of coordinated development. In this way, it is conductive to clarifying the concepts of them, and the researches on the issues related to collaboration or coordination can be made well in the true sense through rationally recognizing the difference and connection between them.

With ever-changing educational circumstances, teaching management methods are constantly innovated. Especially, the teaching management practice has produced a large amount of student data information. The students’ data covers a wide range of contents, including students’ daily test results, students’ rewards, and punishments records as well as basic personal information. Thus, how to achieve the accurate screening and efficient use of valuable data information is worth discussing. At the present stage, the existing technologies and conditions have used these data fully. Therefore, by finding the methods for the scientific use of student data and mining the information value, we can better guide students to learn, strengthen student management, and help students improve their grades with positive supervision and early warning. In this context, based on a brief review of related theories and techniques, this study developed an early warning mechanism for student performance based on machine learning. This paper summarizes the theories and technologies related to educational data mining and proposes the design of the student performance early warning system based on machine learning according to the system requirements analysis, overall architecture design, multi-source heterogeneous data acquisition, and preprocessing.

Live streaming e-commerce has exploded recently. While the live streaming traffic is dominated by the top live streamers, merchants and ordinary live streamers attempt to establish self-operating live streaming, but the number of fans and sales performance are far approaching of the top live streamers. By using the experimental approach, it is found that a significant difference in the purchase intention in three different live streaming scenarios: top live streaming, merchants’ self-operating live streaming, and ordinary live streaming. As well as a significant difference in the evaluation from three dimensions: live streamer, product, and live streaming room. More precise analysis results demonstrate that top live streamers are much higher than other streamers in all dimensions after pairwise comparison investigation. Based on the results of the experimental analysis and with reference to consumers' evaluation of the top live streamers, this study provides executable improvement suggestions for merchants’ self-operating live streaming and ordinary live streaming.

In the current situation that the development trend and scale of Chinese foreign cooperation in running schools are gradually improving and expanding, the evaluation of Chinese foreign cooperation in schools is analyzed from the qualitative aspect. There is less quantitative analysis and research through the establishment of mathematical models. Thus, we applied the correlation research between big data analysis and in-depth learning technology to the analysis. Under the background of big data analysis, the Chinese foreign cooperative school contains a large amount of data, which contains various knowledge and laws. With the data analysis of different dimensions, the convolution neural network in-depth learning technology is used to evaluate the Chinese foreign cooperative school running mode in China. Convolutional neural network (CNN) is used to establish the nonlinear relationship model between the proportion of "students trained under the Chinese foreign cooperative school running mode" and various influencing factors in "Chinese students studying abroad" from 2003 to 2020. The purpose is to evaluate and analyze the Chinese foreign cooperative school running mode in China and provide a reference for the development, decision-making, and reformation of Chinese foreign school running mode.