Zhiru Wang

R&D strategies play a decisive role in the promotion of enterprise innovation output and innovation ability. In order to thoroughly investigate the R&D strategies of iron and steel enterprises, an R&D strategy analysis framework based on R&D semantic topic analysis and outlier behavior detection was proposed. Additionally, empirical research on R&D layout and direction, R&D quality, and the achievement maintenance strategy of enterprises, from both macro and micro perspectives, was conducted. The feasibility of the R&D strategy analysis framework was verified. Additionally, the results show that, in terms of R&D topic layout strategy, most enterprises adopted a stable maintenance strategy after quickly completing the layout; regarding the R&D focus strategy, most enterprises focused on R&D fields and carried out strategic management; for R&D quality control strategy, some enterprises adopted a strategy of prolonging the duration of invention patents, and high-quality outputs with a long lifetime were developed rapidly. These research results have reference value for Chinese enterprises, to adjust their R&D strategies, and for the government, to formulate supporting policies.

This paper analyzes the temporal and spatial characteristics of green invention patent applications during 1985–2018. The results show that China’s green invention patent applications present five stages of slow development, slow growth, accelerating growth, rapid growth and booming. Green invention patent applications in the fields of energy conservation, alternative energy production and waste management have always been in the forefront, but there are relatively less green invention patent applications in transportation and nuclear power; which need to be further strengthened. Green invention patent applications show a high level of geographical agglomeration in space, mainly concentrated in the eastern region, followed by the central region, the western region and northeast region. During the study period, the differences among the four major regions, eastern, northeastern, central and western, showed a trend of first expanding and then narrowing, and the intra-regional differences were the main source of spatial differences. The number of green invention patent applications in the four regions also shifted in space during the research period. The temporal and spatial evolution characteristics are correlative to national and regional innovation policies. Aiming at solving the problems of unbalanced development in different categories of green invention patent applications and regions, this paper puts forward corresponding policy suggestions.

In order to better achieve active defense in the escalator risk management, this study based on the vulnerability theory, task driven theory, management error theory, proposed a Gray Relational Analysis (GRA) based fuzzy assessment of escalator accident risk approach. The risk assessment index system of subway station escalator accident was constructed based on the commonness and essence of management defects; the weight of risk index was calculated scientifically and reasonably by using Analytic Hierarchy Process (AHP); escalator accident risk was evaluated by the combination of GRA and Fuzzy approach. The results show that escalator equipment, environment, safety knowledge of riders are all in good condition in the station. However, ‘Maintenance’ of escalator in the Beijing subway station is in an extremely high risk level. The contributions of this studies are: (1) general risk elements analysis model for escalator accidents which enable to compose any risk factor possible to induce escalator accident in subway station; (2) GRA based risk assessment approach can avoid the problem when expend the range to left and right. It can also judge whether the continuous improvement effect of the object is significant by the difference degree of each risk level before and after.

Escalator accidents not only happen frequently but also have cascading effects. The purpose of this study is to block the formation of cascading accident networks by identifying and preventing critical hazards. A modified five-step task-driven method (FTDM) is proposed to break down passenger-related cascading escalator accidents. Three complex network parameters in complex network theory are utilized to identify critical and non-critical Risk Passenger Behavior (RPB) hazards and Other Hazards related with Risk Passenger Behavior (OH-RPB) in accident chains. A total of 327 accidents that occurred in the Beijing metro rail transit (MRT) stations were used for case studies. The results are consistent in critical and non-critical RPB and OH-RPB and prove that through combination of FTDM accident investigation model and complex network analysis method, critical and non-critical RPB and OH-RPB in a complicated cascading hazards network can be identified. Prevention of critical RPB can block the formation of cascading accident networks. The method not only can be used by safety manager to make the corresponding preventive measures according to the results in daily management but also the findings can guide the allocation of limited preventive resources to critical hazards rather than non-critical hazards. Moreover, the defects of management plan and product design can be re-examined according to the research results.

Although numerous studies have considered the topological characteristics and the impact of disruptions in subway systems, their results have not been verified by empirical data. To address this limitation, we used a data set containing 392 detailed records of disruptions to subway services in Beijing from 2011 to 2017. The Spearman rank correlation coefficient analysis results indicate that the delay duration exhibits no significant relationship with the topological characteristics, whereas the reverse is true for the relationship between the number of affected trains and the topological characteristics. The results also demonstrate that subway network expansion will not result in a paradox between convenience and vulnerability from an actual data perspective. Moreover, contrary to previous research results, no significant relationship was found to exist between service interruption impact and the transit and key bridge stations. However, a high degree of clustering, characterized by redundant tracks between neighbours, tends to provide protection against service disruption for stations. In terms of the spatial variation, the influence of the disruption is greater when the station is further from the centre of the line. These results can support sustainable design in subway network planning.

Synthetic aperture radar (SAR) image target recognition is a hot issue in remote sensing image application. High accuracy SAR target recognition is truly important in both military and civilian fields. Recently, convolutional neural networks (CNNs) have played an important role in the field of SAR image target recognition, however, most of the existing networks incurs some additional problems such as ignoring the influence of speckle noise on the target recognition process, so the recognition accuracy is low. To cope with these problems, this paper proposes a novel SAR image target recognition method based on CNN with frequency and spatial domain enhancement. First, the image is transformed by Gabor feature descriptor in different frequency directions to generate a plurality of feature maps. Then, the image is spatially enhanced using a Laplace transform. The feature maps which obtained by the frequency and spatial domain enhancement together with the original image are used as the network input. Finally, the improved deep residual network (ResNet) is used to complete the target recognition task. Experimental results demonstrate that the proposed method achieves a state-of-the-art accuracy on the MSTAR dataset.