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The purpose of this paper is to semantically annotate the content of digital images with the use of Semantic Web technologies and thus facilitate retrieval, integration and knowledge discovery.

After a review and comparison of the existing semantic annotation models for images and a deep analysis of the characteristics of the content of images, a multi-dimensional and hierarchical general semantic annotation framework for digital images was proposed. On this basis, taking histories images, advertising images and biomedical images as examples, by integrating the characteristics of images in these specific domains with related domain knowledge, the general semantic annotation framework for digital images was customized to form a domain annotation ontology for the images in a specific domain. The application of semantic annotation of digital images, such as semantic retrieval, visual analysis and semantic reuse, were also explored.

The results showed that the semantic annotation framework for digital images constructed in this paper provided a solution for the semantic organization of the content of images. On this basis, deep knowledge services such as semantic retrieval, visual analysis can be provided.

The semantic annotation framework for digital images can reveal the fine-grained semantics in a multi-dimensional and hierarchical way, which can thus meet the demand for enrichment and retrieval of digital images.

This paper aims to reorganize the relevant information of Chinese ancient architectures with the use of Semantic Web technologies and thus facilitate its deep discovery and usage.

This paper proposes an ontology model for Chinese ancient architectures based on architectural narratives theory. To verify the availability of the ancient architecture ontology, we designed and implemented three experiments, including semantic retrieval based on SPARQL query, semantic reasoning with the use of Jena reasoner and visual analysis based on the Chinese Online Digital Humanities Resources Platform.

The proposed ontology provided a solution for the semantic annotation of the unstructured information of Chinese ancient architectures. On this basis, deep knowledge services such as semantic retrieval, semantic reasoning and visual analysis can be provided.

The proposed semantic model of ancient architectures can effectively improve the organization and access quality of the semantic content of Chinese ancient architectures.

This paper focuses on the semantic modelling for the unstructured information of Chinese ancient architectures to semantically describe the related entities (e.g. persons, events, places and times) and uncover their relationships, and thus it made contribution to the deep semantic annotations on ancient architectures.

The purpose of this paper is to test whether self-verification striving serves as an individual difference antecedent of emotional labor and explore whether various emotional labor tactics acted as mediating mechanisms through which self-verification striving relates to employee outcomes.

The sample used in this paper consisted of supervisor–subordinate dyads working in six hotels in South Korea and used multi-level analyses and the Monte Carlo method to test the research hypotheses presented in this paper.

Self-verification striving was positively and directly related to job performance as well as two out of three forms of emotional labor (i.e. the expression of naturally felt emotions and deep acting). Self-verification striving also indirectly related to job satisfaction through the expression of naturally felt emotions and indirectly related to job performance through deep acting.

The findings of this paper suggest that organizations should consider self-verification striving as an employment selection criterion and provide training programs to help their customer service employees engage in appropriate types of emotional labor.

This paper is the first to explore the underlying mechanisms through which self-verification striving relates to employee outcomes. It also empirically bolsters the notion that expressing naturally felt emotions is an important means of authentic self-expression that positively contributes to job satisfaction. Further, the authors found that self-verification striving positively relates to job performance partially through deep acting. Moreover, they have shown that self-verification striving, as an individual differences variable, is an antecedent of different types of emotional labor.

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.

A quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.

The proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.

CFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.

The purpose of this paper is to highlight the significance of relationship quality factors (customer satisfaction, e‐trust, and e‐commitment) on positive word of mouth (WOM) in online retailing.

The relative importance of site characteristics in online retailing on customer satisfaction was examined and the relationship among customer satisfaction, trust, and commitment in offline was identified. This paper then proposes a conceptual model of the relationship among site characteristics, relationship quality, and WOM in online retailing. AMOS 5.0 was used to test for the hypothesized relationships.

All of site characteristics in online retailing have a positive influence on customer satisfaction. Communication of site characteristics has a positive effect on customer satisfaction more than the other factors (shopping convenience, site design, informativeness, and security). Customer satisfaction affects positively e‐commitment more than it does e‐trust. E‐commitment affects positively WOM more than it does e‐trust. This paper identifies the causal relationship among site characteristics, relationship quality, and WOM. Further, the relative importance of customer satisfaction in relationship quality of online retailing is examined.

Results provide important insights into the impact of site characteristics in online retailing on customer satisfaction compared to other previous researches. In addition, e‐trust and e‐commitment are identified as important antecedents of e‐WOM.

The purpose of this study is to identify latent classes of work values that influence the career choices of Korean workers through a person-centred approach. Because work values may be diverse in individuals, investigating the various combinations of those values will help understand individual's decisions to take, maintain and leave a job.

The authors used a total of 15,103 datasets collected at the national level in South Korea. Data were analyzed by using latent class analysis (LCA); a three-step approach was employed to address classification.

As the results of this study, Class 3, “seeking balanced work values rather than income,” presented the highest level of job satisfaction, whereas Class 1, “seeking job security and income,” exhibited the lowest.

Employing an assessment tool to identify the distinct combinations of work values that individuals possess and then providing them with appropriate training and development programs and customized Human Resource (HR) policies aligned with the classes will be essential tasks for HRD (Human Resource Development)/HRM (Human Resource Management) practitioners.

This study aims to investigate three organizational-level factors (geographical proximity, technological similarity and organizational identity integration) that influence the likelihood of post-mergers and acquisition (M&A) joint knowledge creation between inventors from the target and acquiring firms.

Analyzing post-M&A joint patent filing activities from 136 M&A deals in high-tech industries, the authors conduct a zero-inflated negative binomial regression analysis to estimate the likelihood of joint knowledge creation.

The results indicate that close geographical proximity and technological similarity are positively associated, whereas the integration of organizational identity is negatively associated with post-M&A joint knowledge creation.

Managers searching for an ideal acquisition target firm for joint production of new technologies or products should consider factors such as location, prior knowledge base and post-acquisition integration strategies.

The proposed model is a comprehensive framework that considers physical, cognitive and identity dimensions as antecedents of post-M&A joint knowledge creation. This study analyzes joint patenting activities to measure post-M&A joint knowledge creation between target and acquiring firm inventors.

Global value changes continued to expand until the late 2000s. On the other hand, regional value chains have formed around major regional hubs due to the expansion of domestic demand in emerging economies, such as China, and strengthened trade protectionism since the global financial crisis. Such changes lead to the reorganisation of value chains, focusing on domestic markets (reshoring) or neighbouring countries (nearshoring). In particular, the importance of supply chain risk management has been highlighted following disruptions to the supply network due to the COVID-19 outbreak in December 2019. In this regard, major countries such as the USA and the EU are rapidly shifting to regional value chains for stable and sustainable production, rather than primarily aiming for production efficiency targeted at reducing costs. Industries in particular are more exposed to such supply chain risks under the existing structure and it now has become extremely important for businesses to take reaction to such risks. This is especially important for major industries in a country such as automobile or semiconductor manufacturing industries in South Korea. The aim of this study, therefore, is to establish the basis for the simultaneous growth of ports and linked industries by examining the existing structure of the global value chain for the automotive industry, which has a strong presence in South Korea’s domestic economy. In this regard, this research carries out a supply chain analysis focusing on the imports and exports of automotive parts. It also analyses the current structural risks and suggests risk management measures to secure a stable supply chain.

This study identifies whether the Internet search index can be used as effective enough data to identify agricultural and livestock product demand and compare the accuracy of the prediction of major agricultural and livestock products purchases between these prediction models using artificial neural network, linear regression and a decision tree.

Artificial neural network, linear regression and decision tree algorithms were used in this study to compare the accuracy of the prediction of major agricultural and livestock products purchases. The analysis data were studied using 10-fold cross validation.

First, the importance of the Internet search index among the 20 explanatory variables was found to be high for most items, so the Internet search index can be used as a variable to explain agricultural and livestock products purchases. Second, as a result of comparing the accuracy of the prediction of six agricultural and livestock purchases using three models, beef was the most predictable, followed by radishes, chicken, Chinese cabbage, garlic and dried peppers, and by model, a decision tree shows the highest accuracy of prediction, followed by linear regression and an artificial neural network.

This study is meaningful in that it analyzes the purchase of agricultural and livestock products using data from actual consumers' purchases of agricultural and livestock products. In addition, the use of data mining techniques and Internet search index in the analysis of agricultural and livestock purchases contributes to improving the accuracy and efficiency of agricultural and livestock purchase predictions.

The purpose of this paper is to promote the theoretical innovation of socialist economics with Chinese characteristics in these areas.

We must “excavate new materials, discover new problems, propose new ideas, and construct new theories from the practice of China’s reform and development.”

Giving full play to the government’s role in realizing optimal allocation of resources required for the public economy to better exert its control, influence and guidance, and at least assume the following three responsibilities. The first is to iron out the economic cycle. The second is to lead the industry to upgrade. The third is to ensure national economic security.

Some deep-rooted issues still need to be further studied in order to establish the scientific and practical nature of the socialist economics with Chinese characteristics. For instance, why is the theory of a socialist economy with Chinese characteristics summarized from the development practice in China a scientific theory?