The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation or data augmentation. Here, we proposed a DA method for the motor imagery EEG signal called brain-area-recombination. For the BAR, each sample was first separated into two ones by left/right brain channels, and the artificial samples were generated by (...) recombining the half-samples. We then designed two schemas corresponding to the single- and multi-subject scenarios. Extensive experiments using the classifier of EEGnet were conducted on two public datasets under various training set sizes. In both schemas, the BAR method can make the EEGnet have a better performance of classification. To make a comparative investigation, we selected two common DA methods, and the BAR method beat them. Further, using the proposed BAR for augmentation, EEGnet achieved up to 8.3% improvement than a typical decoding algorithm CSP-SVM, note that both the models were trained on the augmented dataset. This study shows that BAR usage can significantly improve the classification ability of deep learning to MI-EEG signals. To a certain extent, it may promote the development of deep learning technology in the field of BCI. (shrink)

Clarifying the causes of subway construction accidents has an important impact on reducing the probability of accidents and protecting workers’ lives and public property to a greater extent. A total of 138 investigation records of subway construction accidents from 2000 to 2020 were collected in this study. Based on a systemic analysis of 29 well-known accident causation models and the formative process of the subway construction accidents, we extracted the causative factors of subway construction accidents from the collected records. Furthermore, (...) a causation analysis index system of subway accidents was proposed based on fault tree analysis, where we considered subway construction accidents as the top event and the five dimensions, i.e., human, equipment, environment, management, and safety culture, as first-level intermediate events. Moreover, 17 causative factors were considered to be related to the severity of subway construction accidents. It is found that human factors are prone to be critical to high-risk accidents. Finally, a Bayesian network was formed to explore the causative factors of high-risk subway construction accidents. Based on the combined application of FTA and BN, this study discusses the complex influence factors and their action routes to unsafe accidents in subway construction sites, and makes efforts to correspond safety decision basis for the management of China subway construction. (shrink)

Environment is essentially in the category of culture and environmental research should be based on human value and culture. The study of the relationship between humans and their natural environment should also refer to human relations. Since the operational logic of social capital is the root of ecological crisis, the ultimate solution to this problem lies in human’s correct thinking, institutional, political and behavioral patterns in dealing with nature. Re-establishing human ecology therefore provides a cultural basis for the harmony between (...) human and nature and realistic basis for the psycho-physical harmony and spiritualization of humans. (shrink)

A scientific paper’s citation represents its influence, which is the most intuitive indicator to access the quality of papers. This paper mainly adopts the social network analysis method, using the authors and the keywords of sports industry papers in China to constitute the networks of collaboration and knowledge, to explore effects of the degree centrality of authors and keywords and the structural hole of authors and keywords on the citation of papers in the collaboration and knowledge networks and draw the (...) following conclusions: as for collaboration networks, the degree centrality at the paper level is positively correlated with citations; in the collaboration network, the positive correlation between the structural hole at the paper level and citations does not exist; within knowledge networks, an inverted- U shape was found between degree centrality and paper’s citation; and within knowledge networks, a positive correlation is in existence between the structural hole of papers and their citation. This study synthesizes the already widely used collaboration network with the knowledge network constructed through keywords, distinguishes from the previous network features focusing at the author level, and explores research projects of Chinese Sports Industry from the paper level, providing a new perspective for the research of sports industry in China, complementing the methods and ideas of sports industry research, as well as providing a reference for the research in other disciplinary fields. (shrink)

In terms of life space, individuals are usually settled in different spaces according to relationships of blood, geography, and profession. In pre-modern societies, ethics were realized through customs, conventions, taboos, magical practices, and politics. Because this was not an open process in which rationality was sufficiently employed, non-reflectiveness and non-criticality were its essence, and intuitions and feelings were its basic modes of existence. In modern societies, the logic of capital movement settles groups of people according to their economic dependence, and (...) interactions based on individuals’ desires and self-serving calculations have become widespread and frequent. A space for public interaction and life in which rationality is sufficiently employed and rational bases of the rules are constantly questioned thus finally came into being. Families and villages lost their centrality, resulting in a crisis of private interactions and life, and of its system of norms. (shrink)