Time series analysis is widely used in the fields of finance, medical, and climate monitoring. However, the high dimension characteristic of time series brings a lot of inconvenience to its application. In order to so...Time series analysis is widely used in the fields of finance, medical, and climate monitoring. However, the high dimension characteristic of time series brings a lot of inconvenience to its application. In order to solve the high dimensionality problem of time series, symbolic representation, a method of time series feature representation is proposed, which plays an important role in time series classification and clustering, pattern matching, anomaly detection and others. In this paper, existing symbolization representation methods of time series were reviewed and compared. Firstly, the classical symbolic aggregate approximation (SAX) principle and its deficiencies were analyzed. Then, several SAX improvement methods, including aSAX, SMSAX, ESAX and some others, were introduced and classified;Meanwhile, an experiment evaluation of the existing SAX methods was given. Finally, some unresolved issues of existing SAX methods were summed up for future work.展开更多
Due to their excellent physical and chemical properties,boron nitride nanosheets(BNNSs)have shown great application potential in many fields.However,the difficulty in scalable preparation of large-size BNNSs is still ...Due to their excellent physical and chemical properties,boron nitride nanosheets(BNNSs)have shown great application potential in many fields.However,the difficulty in scalable preparation of large-size BNNSs is still the current factor that limits this.Herein,a simple yet efficient microwave-assisted chemical exfoliation strategy is proposed to realize scalable preparation of BNNSs by using perchloric acid as the edge modifier and intercalation agent of h-BN.The as-obtained BNNSs behave a thin-layered structure(average thickness of 3.9 nm)with a high yield of~16%.Noteworthy,the size of BNNSs is maintained to the greatest extent so as to realize the preparation of BNNSs with ultra-large size(up to 7.1μm),which is the largest so far obtained for the top-down exfoliated BNNSs.Benefiting from the large size,it can significantly improve the thermal diffusion coefficient and the thermal conductivity of polyvinyl alcohol by 51 and 62 times respectively,both showing a higher value than the one previously reported.This demonstrates that the prepared BNNSs have great promise in enhancing the thermal conductivity of polymer materials.展开更多
基金the National Natural Science Foundation of China [grant numbers 61602279, 61472229]Shandong Province Postdoctoral Innovation Project [grant number 201603056]+2 种基金the Sci.& Tech. Development Fund of Shandong Province of China [grant number 2016ZDJS02A11 and Grant ZR2017MF027]the SDUST Research Fund [grant number 2015TDJH102]and the Fund of Oceanic telemetry Engineering and Technology Research Center, State Oceanic Administration (grant number 2018002).
文摘Time series analysis is widely used in the fields of finance, medical, and climate monitoring. However, the high dimension characteristic of time series brings a lot of inconvenience to its application. In order to solve the high dimensionality problem of time series, symbolic representation, a method of time series feature representation is proposed, which plays an important role in time series classification and clustering, pattern matching, anomaly detection and others. In this paper, existing symbolization representation methods of time series were reviewed and compared. Firstly, the classical symbolic aggregate approximation (SAX) principle and its deficiencies were analyzed. Then, several SAX improvement methods, including aSAX, SMSAX, ESAX and some others, were introduced and classified;Meanwhile, an experiment evaluation of the existing SAX methods was given. Finally, some unresolved issues of existing SAX methods were summed up for future work.
基金Projects 52172052 and 51872253 supported by the National Natural Science Foundation of ChinaProject E2019203480 supported by the Hebei Natural Science Foundation of China.
文摘Due to their excellent physical and chemical properties,boron nitride nanosheets(BNNSs)have shown great application potential in many fields.However,the difficulty in scalable preparation of large-size BNNSs is still the current factor that limits this.Herein,a simple yet efficient microwave-assisted chemical exfoliation strategy is proposed to realize scalable preparation of BNNSs by using perchloric acid as the edge modifier and intercalation agent of h-BN.The as-obtained BNNSs behave a thin-layered structure(average thickness of 3.9 nm)with a high yield of~16%.Noteworthy,the size of BNNSs is maintained to the greatest extent so as to realize the preparation of BNNSs with ultra-large size(up to 7.1μm),which is the largest so far obtained for the top-down exfoliated BNNSs.Benefiting from the large size,it can significantly improve the thermal diffusion coefficient and the thermal conductivity of polyvinyl alcohol by 51 and 62 times respectively,both showing a higher value than the one previously reported.This demonstrates that the prepared BNNSs have great promise in enhancing the thermal conductivity of polymer materials.
