Xin Wang

An effective approach is introduced to predict the magnitude of reservoir-triggered earthquake, based on support vector machines and fuzzy support vector machines methods. The main influence factors on RTE, including lithology, rock mass integrity, fault features, tectonic stress state, and seismic activity background in reservoir area, are categorized into 11 parameters and quantified by using analytical hierarchy process. Dataset on 100 reservoirs in China, including the 48 well-documented cases of RTE, are collected and used to train and validate the prediction models established with SVM and FSVM, respectively. Through numerical tests, it is found that both the SVM and FSVM models are effective in the prediction of the magnitude of RTE with high accuracy, provided that sufficient samples are collected. While the results of FSVM which is extended from SVM by introducing a fuzzy membership to reduce the influence of noises or outliers are found to be slightly less accurate than those of SVM in the current analysis of RTE cases. The reason might be attributed to the high discreteness of the sample data in the current study.

The growing Chinese middle class and their accumulation of wealth and economic capital have seen an increasing number of Chinese students pursuing their education in the West. Due to this growing number, motivations behind their decision to study abroad warrant scholarly treatment. This article discusses the motives of Chinese middle-class families and their children in seeking studying abroad. The paper reports on a recent study of 166 students on American campuses from 2017 to 2018. It uses Bourdieusian concepts of capital, habitus, and the idea of social mobility and social reproduction, to understand Chinese middle-class families’ strategic decisions around studying overseas in relation to employability, labour market competitiveness, and family support. Studying abroad, therefore, is construed by Chinese middle class families as a way of pursuing and preserving their social status and social mobility.

We explore the potential impact of CEO entrepreneurial orientation on firm choice of CSR activities. Integrating upper echelon theory and attention-based view of the firm, we find that CEO entrepreneurial orientation leads to more engagement in CSR innovation rather than corporate philanthropy. We find that the effect of CEO entrepreneurial orientation on firm choice of CSR activities varies under two situational contexts: state-owned enterprises and incoming/departing CEO. The hypotheses are tested using two different studies. Study 1 uses a cross-sectional survey of Chinese CEOs, whereas study 2 employs a longitudinal analysis of Chinese publicly listed firms from 2003 to 2017. Both studies support our theoretical hypotheses.

The sampling-based motion planner is the mainstream method to solve the motion planning problem in high-dimensional space. In the process of exploring robot configuration space, this type of algorithm needs to perform collision query on a large number of samples, which greatly limits their planning efficiency. Therefore, this paper uses machine learning methods to establish a probabilistic model of the obstacle region in configuration space by learning a large number of labeled samples. Based on this, the high-dimensional samples’ rapid collision query is realized. The influence of number of Gaussian components on the fitting accuracy is analyzed in detail, and a self-adaptive model training method based on Greedy expectation-maximization algorithm is proposed. At the same time, this method has the capability of online updating and can eliminate model fitting errors due to environmental changes. Finally, the model is combined with a variety of sampling-based motion planners and is validated in multiple sets of simulations and real world experiments. The results show that, compared with traditional methods, the proposed method has significantly improved the planning efficiency.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits. Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.

Knearest neighbor search is an important problem in location-based services and has been well studied on static road networks. However, in real world, road networks are often time-dependent; i.e., the time for traveling through a road always changes over time. Most existing methods forkNN query build various indexes maintaining the shortest distances for some pairs of vertices on static road networks. Unfortunately, these methods cannot be used for the time-dependent road networks because the shortest distances always change over time. To address the problem ofkNN query on time-dependent road networks, we propose a novel voronoi-based index in this paper. Furthermore, we propose a novel balanced tree, namedV-tree, which is a secondary level index on voronoi-based index to make our querying algorithm more efficient. Moreover, we propose an algorithm for preprocessing time-dependent road networks such that the waiting time is not necessary to be considered. We confirm the efficiency of our method through experiments on real-life datasets.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits. Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.