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The purpose of this study is to estimate different data models on house prices using statistical models and the variables which are controlled by real estate policy.

This study used several statistical techniques, such as Vector auto-regression (VAR), Johansen co-integration and variance decomposition, which aim to assess the significant effect of macroeconomic factors on Chinese house prices.

The results show that land supply and other variables have negative effects on house prices. The results also indicate that financial mortgages for real estate have positive effects on house prices and the area of vacant houses as well as the area of housing sold.

This study only covers three cities in China because of limitations of data for other cities.

This study proposes policy suggestions according to the empirical results obtained.

The purpose of this study is to model the global dynamic hysteresis properties with an improved Jiles–Atherton (J-A) model through a unified set of parameters.

First, the waveform scaling parameters β, λ_k and λ_c are used to improve the calculation accuracy of hysteresis loops at low magnetic flux density. Second, the Riemann–Liouville (R-L) type fractional derivatives technique is applied to modified static inverse J-A model to compute the dynamic magnetic field considering the skin effect in wideband frequency magnetization conditions.

The proposed model is identified and verified by modeling the hysteresis loops whose maximum magnetic flux densities vary from 0.3 to 1.4 T up to 800 Hz using B30P105 electrical steel. Compared with the conventional J-A model, the global simulation ability of the proposed dynamic model is much improved.

Accurate modeling of the hysteresis properties of electrical steels is essential for analyzing the loss behavior of electrical equipment in finite element analysis (FEA). Nevertheless, the existing inverse Jiles–Atherton (J-A) model can only guarantee the simulation accuracy with higher magnetic flux densities, which cannot guarantee the analysis requirements of considering both low magnetic flux density and high magnetic flux density in FEA. This paper modifies the dynamic J-A model by introducing waveform scaling parameters and the R-L fractional derivative to improve the hysteresis loops’ simulation accuracy from low to high magnetic flux densities with the same set of parameters in a wide frequency range.

The paper aims to propose a virtual reality (VR) wisdom teaching model in open university English course from the perspective of “Metaverse”. The study aims to testify the stimulation for English learning and the effectiveness of English-expressing with VR tools for adult learners from the practice in a pilot reform project.

The paper opted for an exploratory study using ICARE Design Model as the framework, under the grounded theories of constructivism and multi-modal teaching. The study compared the evaluation data of one-semester English learning performance between the experimental class (67 students) with VR practice and the controlled class (67 students), including speaking test score, qualitative feedback and in-depth experience analysis. The data were complemented by reflection paper analysis, including manual evaluation (the criteria of semantics, pronunciation, fluency and completeness), questionnaire survey (in the form of five-point Likert scale) and semi-structured interview.

The paper provides empirical insights about the VR wisdom teaching model in English language teaching and learning in a Chinese Open University. The empirical results suggest that “3I” features of VR technology could make up for the shortcomings of traditional English classes in open universities in China, and VR resources designed with curriculum teaching materials could also be helpful for students’ command of knowledge points and language skills. What’s more, the sense of authentic experience in virtual could promote the teaching and learning effect in college English classes.

The present study focuses on a wisdom mode of foreign language teaching and learning for adult learners in open education, so the research results may lack generalizability. Therefore, researchers are encouraged to further explore the deep integration of VR/artificial intelligence in foreign language teaching and learning.

This paper fulfills an identified need to study how VR tools provide an engaging, fun and immersive language learning environment, to enhance autonomous learning and learning engagement.

The development of social networks enhances the interaction between people, which brings new challenges to the research of group decision-making (GDM). This study aims at the problem that the synergy and redundancy due to interaction among decision-makers are ignored in the previous GDM, a trust-enhanced consensus reaching model based on interaction among decision-makers with incomplete preferences is proposed.

Firstly, confidence level is introduced to improve the hesitation phenomenon that should be considered when calculating trust degree; Secondly, a new trust propagation operator is developed to deal with indirect trust relationships; Thirdly, trust degree is transformed into interaction index to quantify the synergy and redundancy in decision-making. Fuzzy capacities of decision-makers are used to replace traditional weights, and the final scores of alternatives are obtained through Choquet integral.

The proposed model using fuzzy capacity can reflect the synergy or redundancy among decision-makers and improve the accuracy of final ranking result and reduce the loss of information.

This study proposes a trust-enhanced consensus reaching model, which develops a new trust propagation operator to ensure the continuous attenuation of trust in propagation process. And the proposed model uses fuzzy capacity to improve the enhancement or attenuation on the scores of alternatives.