Since the time series data have the characteristics of a large amount of data and non-stationarity, we usually cannot obtain a satisfactory result by a single-model-based method to detect anomalies in time series data. To overcome this problem, in this paper, a combination-model-based approach is proposed by combining a similarity-measurement-based method and a model-based method for anomaly detection. First, the process of data representation is performed to generate a new data form to arrive at the purpose of reducing data volume. Furthermore, due to the anomalies being generally caused by changes in amplitude and shape, we take both the original time series data and their amplitude change data into consideration of the process of data representation to capture the shape and morphological features. Then, the results of data representation are employed to establish a model for anomaly detection. Compared with the state-of-the-art methods, experimental studies on a large number of datasets show that the proposed method can significantly improve the performance of anomaly detection with higher data anomaly resolution.
Despite the possible benefits of implementing healthcare information technologies, successful implementation of effective healthcare information technology is constrained by cultural and regulatory concerns and technical obstacles encountered when establishing or upgrading an organisation's enterprise infrastructure. In this paper, we advance Ross' four‐stage model of enterprise architecture maturity as a valuable IT resource for helping healthcare organisations sustain a competitive advantage. We use partial least squares (PLS) structural equation modelling to analyse survey data from 164 US hospitals at different stages of EA maturity. Our results provide evidence that enterprise architecture maturity directly influences the effectiveness of hospitals' IT resources for achieving strategic goals. Further, enterprise architecture maturity indirectly influences the effectiveness of IT resources when IT alignment is incorporated as a mediating variable. We discuss the implications of our findings for research and practice and suggest opportunities for future research. 相似文献
Adaptive anisotropic refinement of finite element meshes allows one to reduce the computational effort required to achieve a specified accuracy of the solution of a PDE problem. We present a new approach to adaptive refinement and demonstrate that this allows one to construct algorithms which generate very flexible and efficient anisotropically refined meshes, even improving the convergence order compared to adaptive isotropic refinement if the problem permits. 相似文献
Catalysis Letters - Porous materials with heterogeneous nature occupy a pivotal position in the chemical industry. This work described a facile pre- and post-synthetic approach to modify porous... 相似文献