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The detection of anomalies in multivariate time-series data is becoming increasingly important in the automated and continuous monitoring of complex systems and devices due to the rapid increase in data volume and dimension. To address this challenge, we present a multivariate time-series anomaly detection model based on a dual-channel feature extraction module. The module focuses on the spatial and time features of the multivariate data using spatial short-time Fourier transform (STFT) and a graph attention network, respectively. The two features are then fused to significantly improve the model’s anomaly detection performance. In addition, the model incorporates the Huber loss function to enhance its robustness. A comparative study of the proposed model with existing state-of-the-art ones was presented to prove the effectiveness of the proposed model on three public datasets. Furthermore, by using in shield tunneling applications, we verify the effectiveness and practicality of the model.

The reliability of the production line is closely linked to the operating status of the device. In order to ensure the reliability of equipment operation, this paper puts forward the visual modeling of the intelligent monitoring in the production line based on UML modeling. On the basis of the system analysis, a modeling which provides a unified visualization for all stages of the design and the realization of the system is built by the UML modeling language and includes the use-case model, and static class structure model and system dynamic structure model. Moreover the paper raise a specific business process, which is greatly shortened the cycle of developing system, improves the reliability of production systems and utilization of capacity and provides a reliable guarantee for automatic production.

This special issue focuses on all aspects on techniques and applications in cyber intelligence research. The purpose of this special issue is to provide a forum for presentation and discussion of innovative ideas, cutting-edge research results, and novel techniques, methods, and applications on all aspects of cyber intelligence. It includes selected papers from the 2018 International Conference on Applications and Techniques in Cyber Intelligence (ATCI2018) July 11-13, 2018, Shanghai, China, as well as an open call.The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the ten highest quality manuscripts were suggested for the editor in chief to accept for this special issue. This special issue will be published by Concurrency and Computation: Practice and Experience (CCPE) as special issues.A kind of cutting and nesting system for cloud manufacturing based on service-oriented architecture (SOA) is proposed by Li and Wang 1 , which deploys a nesting algorithm distributedly to a multicore computer cluster to provide the cutting and nesting service for numerous small and medium enterprises through uniform network service and to realize the integration with an existing enterprise system based on SOA. Wang and Zhu 2 propose an improved term frequency-inverse document frequency (TFIDF) model combined with the Word2vec model for weighing word vectors. In view of the inability of the Word2vec model to distinguish the importance of words with the text, TFIDF is further introduced to weighing Word2vec word vectors to achieve a weighted Word2vec classification model. To ensure the navigational safety of ships in the sea and reduce human errors, a set of navigational information systems with decision support function is developed by Liu et al. 3 A supervised learning framework with strong expansibility is established by Jia and Yang 4 for search-engine joint ranking problem. It can transform existing algorithms into corresponding learning algorithms, and design new algorithms under this framework. Jiang et al 5 present the game model in the social network environment by analyzing the decision-making process of conflict events and the factors to describe the evolution of conflict events.The interaction design of a driver communication system is studied by Zhao and Lin. 6 They carried out three driving simulation experiments to study three different ways of interaction interfaces and then promoted a questionnaire based on NASA Text Load Index to understand the subjective feelings and subjective workload of drivers in using these interaction interfaces. Xiaoyan 7 does the research on the mechanism of government subsidies and carbon tax influence on producers' decision-making by establishing an evolutionary game model between governments and producers and by integrating with prospect theory. Hu and Liu 8 propose an E-maintenance framework for public infrastructure, combining Building Information Modeling, Industry Foundation Classes, and Semantic Web technologies to he...