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This paper presents a new approach of productivity estimation of cutter suction dredger operation through data mining and learning from real-time big data.

The paper used big data, data mining and machine learning techniques to extract features of cutter suction dredgers (CSD) for predicting its productivity. ElasticNet-SVR (Elastic Net-Support Vector Machine) method is used to filter the original monitoring data. Along with the actual working conditions of CSD, 15 features were selected. Then, a box plot was used to clean the corresponding data by filtering out outliers. Finally, four algorithms, namely SVR (Support Vector Regression), XGBoost (Extreme Gradient Boosting), LSTM (Long-Short Term Memory Network) and BP (Back Propagation) Neural Network, were used for modeling and testing.

The paper provided a comprehensive forecasting framework for productivity estimation including feature selection, data processing and model evaluation. The optimal coefficient of determination (R²) of four algorithms were all above 80.0%, indicating that the features selected were representative. Finally, the BP neural network model coupled with the SVR model was selected as the final model.

Machine-learning algorithm incorporating domain expert judgments was used to select predictive features. The final optimal coefficient of determination (R²) of the coupled model of BP neural network and SVR is 87.6%, indicating that the method proposed in this paper is effective for CSD productivity estimation.

This study was based on situated learning, by combining mobile learning and augmented reality, so that students could not only access information content in a real environment but also obtain such information via augmented reality, to support mobile learning.

The research included development of an augmented reality system combined with situational learning, used by students to learn about campus plants as part of the college life technology curriculum. Students took part in mobile learning, and an investigation was conducted into the computer learning behaviour of notebook users. College students were used as the experimental subjects. Data were collected using questionnaire surveys and were evaluated in order to identify the behavioural intentions of learners in outdoor learning activities.

The questionnaire survey covered environmental interactivity, system quality and textbook content. It was found that learners who used mobile learning augmented reality (MLAR) generally managed to browse all the contents of the textbook at each learning location, without spending too much time looking for information, and learners could quickly integrate this into the learning situation. Learners who used MLAR had a strong motivation to study plants at the learning site because they wanted to use the augmented reality technology to observe virtual plant models. Learners who used MLAR in their field learning liked using augmented reality for further learning, for example, using a magic wand to interact with the technology.

This study adopted a new approach to deliver elements of the life technology curriculum, integrating augmented reality into mobile learning. All participating students gave positive reviews of six aspects of the proposed system: their behavioural intentions, cognitive usefulness, cognitive ease of use, environmental interactivity, system quality and textbook content.

This research explores the appropriateness of using a digital learning system based on a multiplayer online animated game in firefighting education and training. Use of the game improved learning was effective. It can increase learners' understanding of the taught content and their willingness to learn.

The research applies digital learning based on a multiplayer online animated game coupled with 3D and virtual reality (VR) technology. To verify the effectiveness of this approach, participants were divided into two groups, an experimental group (using the game) and a control group (not using the game). T-tests were used to compare the learning of the two groups.

Firefighting knowledge was significantly better among the experimental group than the control group. Learning was explored in three different domains: basic firefighting knowledge, fire extinguisher operation and fire source identification; the latter two showed statistically significant differences. After learners acquired knowledge from multimedia, the addition of a VR exercise effectively helped them to remember what they learned and increased their understanding of the taught content.

The approach proposed in this study applies digital learning via a multiplayer online animated game to explore the appropriateness of such games in firefighting education and training. Use of the game improved learning and was effective. It can not only increase learners' understanding of the taught content, but also their willingness to learn.

Based on the social information processing theory, the purpose of this study is to propose a conceptualized moderated mediation model for testing the linkage between leader narcissism and employees’ innovative behavior through the mediating effect of employees’ cognitive dependency and the moderating effect of environmental uncertainty between employees’ cognitive dependency and their innovative behavior.

In this study, multisource data from 266 employees and their supervisors in 11 large high-tech Chinese companies were collected through a field study and an online survey. The hypotheses were tested using structural equation modeling and bootstrapping.

The results of this study show that leader narcissism has a negative impact on employees’ innovative behavior and that employees’ cognitive dependency plays a mediating role between leader narcissism and employees’ innovative behavior. Cognitive dependency and environmental uncertainty play moderated mediation roles between leader narcissism and employees’ innovative behavior.

In the future, longitudinal research and experimental methods can be used to avoid common method bias. Further studies could allow leaders to evaluate environmental uncertainty and explore the emotional path by which leader narcissism has negative effects on followers’ innovation from social information processing theory. In addition, future studies can explore cognitive dependency more deeply from the perspectives of forced obedience and active worship.

Organizations should warn leaders to control the dark side of narcissism and minimize environmental uncertainty to reduce barriers to innovation.

This study constructs the path of the effect of leader narcissism on employees’ innovation through employees’ cognitive dependency in a specific context, which enriches theoretical research on the link between leaders’ traits and employees’ innovative behavior. Along with the finding of leader narcissism’s negative effect on employees’ innovative behavior, this study explores the dark side of leader narcissism in the context of China’s high-tech firms and environmental uncertainty.

Based on the intrinsic motivation theory and spiritual leadership theory, the current study proposes a chain mediation model for testing the linkage between spiritual leadership and employees' innovative behavior through individual values and role identity.

In this study, 309 valid leader–subordinate matching questionnaires from 10 Internet enterprises and 21 manufacturing enterprises in China were collected through a field study. The hypotheses were tested using structural equation modeling and bootstrapping.

The results show that spiritual leadership has a positive impact on employees' innovative behavior. Uncertainty avoidance and creative role identity not only respectively play a mediating role but also play a chain mediating role in the process of spiritual leadership influencing employees' innovative behavior.

This study explores the influence of leadership style on employees' individual values, which has rarely been done in previous studies. Furthermore, the research explores the impact of personal values (uncertainty avoidance) on employee self-perception (creative role identity). And it enriches the relationship between spiritual leadership and employees' innovative behavior and reveals the deeper influence mechanism between them.

The purpose of this paper is to propose a robust correntropy assisted blind channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) for improved channel gains estimation and channel ordering and sign ambiguities resolution in non-Gaussian noise channel.

The correntropy independent component analysis with L₁-norm cost function is used for blind channel estimation. Then a correntropy-based method is formulated to resolve the sign and order ambiguities of the channel estimates.

Simulation study on Gaussian noise scenario shows that the proposed method achieves almost the same performance as the conventional L₂-norm based method. However, in non-Gaussian noise scenarios performance of the proposed method significantly outperforms the conventional and other popular estimators in terms of mean square error (MSE). To solve the ordering and sign ambiguities problems, an auto-correntropy-based method is proposed and compared with the extended cross-correlation-based method. Simulation study shows improved performance of the proposed method in terms of MSE.

This paper presents for the first time, a correntropy-based blind channel estimator for MIMO-OFDM as well as simulated comparison results with traditional correlation-based methods in non-Gaussian noise environment.

China's resource allocation mechanism in education has become an important factor in determining residential access to educational resources. The purpose of this paper is to analyze the impacts made by the individual natures of buyers, the external environment, as well as the characteristics of residential properties on the willingness price of buyers. The study's aim is to lay theoretical foundations for the determination of problems related with the matters under consideration.

Using the panel data of 54 districts and counties in Beijing, Shanghai, Guangzhou and Shenzhen, the study unifies macro factors and micro factors in a model for empirical analysis.

Basic education resources can affect housing prices via the “capitalization of education.” The degree of those educational resources’ influence on willingness price changes according to personal income levels, standards of living, housing price fluctuations, the convenience of the residential area and the degrees of urbanization in a district. The greater the buyer's income and standard of living is, the higher is their willingness price. Buyers in urbanized areas prefer increases in educational resources. Increased educational resources increase the values of residential downtown areas. In developed areas with private educational facilities, the role of educational resources in influencing property prices is relatively small.

This paper uses data concerning the consumption and investment of residential properties to build a theoretical model for the willingness price of buyers. It unifies macro factors and micro factors in a single model and presents new results about basic education resources and the willingness price of buyers under different conditions.

This paper aims to explore whether environmental, social and governance (ESG) performance is positively associated with firm investment efficiency (IE) in emerging economies. It also examines whether board cultural diversity can moderate the ESG–IE relationship.

This paper uses a cross-country sample of listed firms located in seven emerging countries over the 2011–2019 period. The authors use a fixed effect panel regression to empirically test the hypotheses. The authors also use a lagged model and a Heckman’s (1979) two-stage procedure to mitigate potential endogeneity issues. In addition, a two-stage least squares regression analysis was done as an additional robustness check.

This study finds that firms with stronger ESG performance have a higher investment efficiency. Interestingly, this study finds that board cultural diversity negatively moderates the impact of ESG performance on IE for firms operating in settings prone to overinvestment. This result suggests that ESG performance plays a less important role in mitigating managers' tendencies to overinvest when corporate boards have more foreign directors. However, the authors do not find such evidence in firms prone to underinvestment. These findings hold after using an alternative measure of IE and controlling for endogeneity concerns.

This paper adds to the existing body of knowledge in three dimensions. First, to the best of the authors’ knowledge, this is the first cross-country study that investigates the linkage between ESG performance and corporate IE in the context of emerging countries. Second, the authors have enriched the prior literature by examining the moderating effect of board cultural diversity on the positive association between ESG performance and corporate IE. Finally, this study has important implications for policymakers and capital suppliers in emerging countries, which strive to facilitate the efficient allocation of scarce resources.

This paper aims to propose a calibration model for kinematic parameters identification of serial robot to improve its positioning accuracy, which only requires position measurement of the end-effector.

The proposed model is established based on local frame representation of the product of exponentials (local POE) formula, which integrates all kinematic errors into the twist coordinates errors; then they are identified with the tool frame’ position deviations simultaneously by an iterative least squares algorithm.

To verify the effectiveness of the proposed method, extensive simulations and calibration experiments have been conducted on a 4DOF SCARA robot and a 5DOF drilling machine, respectively. The results indicate that the proposed model outperforms the existing model in convergence, accuracy, robustness and efficiency; fewer measurements are needed to gain an acceptable identification result.

This calibration method has been applied to a variable-radius circumferential drilling machine. The machine’s positioning accuracy can be significantly improved from 11.153 initially to 0.301 mm, which is well in the tolerance (±0.5 mm) for fastener hole drilling in aircraft assembly.

An accurate and efficient kinematic calibration model has been proposed, which satisfies the completeness, continuity and minimality requirements. Due to generality, this model can be widely used for serial robot kinematic calibration with any combination of revolute and prismatic joints.

Corporate governance has attracted enormous attention both in the area of law and in the area of financial economics. In comparative corporate governance studies, many people have devoted their energy to find a best corporate governance model. I argue that a functional analysis does not support the view that there is a single best corporate governance model in the world. I further use the transplantation of an English style takeover law into China to show that the importation of foreign law is not always based on careful analysis whether the imported foreign law is the best in the world. Furthermore, I use the subsequent adjustment of the transplanted English takeover law in China to show that the imported foreign law is subject to local political and economic conditions. If there is no best corporate govern model and the transplantation of foreign law into other countries with different social and political background does not achieve similar objectives, the search for a best corporate governance model is misguided. Just as tort law or constitutional law regimes may have diversified models, so do corporate governance regimes in countries with different historical, social and political backgrounds.