The critical driving force for martensitic transformation fcc ( gamma ) yields hcp ( epsilon ) in ternary Fe-Mn-Si alloys increases with the content of Mn and decreases with that of Si. Thermodynamical prediction of ...The critical driving force for martensitic transformation fcc ( gamma ) yields hcp ( epsilon ) in ternary Fe-Mn-Si alloys increases with the content of Mn and decreases with that of Si. Thermodynamical prediction of M//s in ternary Fe-Mn-Si alloys was established. The fcc ( gamma ) yields hcp ( epsilon ) martensitic transformation in Fe-Mn-Si is a semi-thermoelastic and the nucleation process does not strongly depend on soft mode. Nucleation occurs directly through an overlapping of stacking fault rather than pole mechanism, and it is suggested that stacking fault energy (SFE) is the main factor controlling nucleation. Based on the phenomenological theory of martensite crystallography, a shuffle on (0001)//h//c//p plane is required when d//1//1//1 does not equal d//0//0//0//2. The derived principal strain in Bain distortion is smaller, i, e., more reasonable than the values given by Christian. Alloying elements strengthening the austenite, lowering SFE of gamma phase and reducing T//N** gamma temperature may be beneficial to shape memory effect of Fe-Mn-Si based alloys. Accordingly, Fe-Mn-Si-RE and Fe-Mn-Si-Cr-N (or Fe-Mn-Si-Ni-Cr-N) are worthy to be recommended as shape memory materials with improved shape memory effect. (Edited author abstract) 48 Refs.展开更多
Let M f be the Kakeya maximal function in d-dimensional Euclidean space, with same base consisting of cylinders of eccentricity N. The inequality shoum for a base satisfying a direction condition, where ?and c are con...Let M f be the Kakeya maximal function in d-dimensional Euclidean space, with same base consisting of cylinders of eccentricity N. The inequality shoum for a base satisfying a direction condition, where ?and c are constants depending only on d.展开更多
We investigate the memory properties of the ITO/graphene oxide/Al diodes. It is found that the devices show different memory behaviors with the diverse geometry and thickness of Al. When the thickness of the Al electr...We investigate the memory properties of the ITO/graphene oxide/Al diodes. It is found that the devices show different memory behaviors with the diverse geometry and thickness of Al. When the thickness of the Al electrode is relatively thick, the device of the cross-point Al electrode shows a three-level memory effect, and the counterpart device of the cross-bar Al electrode exhibits a volatile static random access memory effect. When the thickness of the AI electrode is thinner, the above devices demonstrate a flash memory effect. The different memory behaviors of ITO/GO/AI diodes are ascribed to the mode and degree of reduction and oxidation of GO.展开更多
Impact of band-engineering to the performance of charge trapping memory with HfO2/Ta2O5/HfO2 （HTH） as the charge trapping layer is investigated. Compared with devices with the same total HfO2 thickness, structures w...Impact of band-engineering to the performance of charge trapping memory with HfO2/Ta2O5/HfO2 （HTH） as the charge trapping layer is investigated. Compared with devices with the same total HfO2 thickness, structures with Ta2O5 closer to substrates show larger program/erase window, because the 2nd HfO2 （next to blocking oxide） serving as part of blocking oxide reduces the current tunneling out of/in the charge trapping layer during program and erase. Moreover, trapped charge centroid is modulated and contributed more to the fiat-band voltage shift. Further experiments prove that devices with a thicker 2nd HfO2 layer exhibit larger saturate fiat-band shift in both program and erase operation. The optimized device achieves a 7 V memory window and good reliability characteristics.展开更多
Uncertainty principle is one of the most fascinating features of the quantum world. It asserts a fundamental limit on the precision with which certain pairs of physical properties of a particle, such as position and m...Uncertainty principle is one of the most fascinating features of the quantum world. It asserts a fundamental limit on the precision with which certain pairs of physical properties of a particle, such as position and momentum, can not be si- multaneously known. The uncertainty principle has attracted considerable attention since the innovation of quantum me- chanics and has been investigated in terms of various types of uncertainty inequalities： in terms of the noise and dis- turbance, according to successive measurements, as informa- tional recourses in entropic terms, by means of majorization technique and based on sum of variances and standard devia- tions.展开更多
Anomaly detection is crucial to the flight safety and maintenance of unmanned aerial vehicles(UAVs)and has attracted extensive attention from scholars.Knowledge-based approaches rely on prior knowledge,while model-bas...Anomaly detection is crucial to the flight safety and maintenance of unmanned aerial vehicles(UAVs)and has attracted extensive attention from scholars.Knowledge-based approaches rely on prior knowledge,while model-based approaches are challenging for constructing accurate and complex physical models of unmanned aerial systems(UASs).Although data-driven methods do not require extensive prior knowledge and accurate physical UAS models,they often lack parameter selection and are limited by the cost of labeling anomalous data.Furthermore,flight data with random noise pose a significant challenge for anomaly detection.This work proposes a spatiotemporal correlation based on long short-term memory and autoencoder(STCLSTM-AE)neural network data-driven method for unsupervised anomaly detection and recovery of UAV flight data.First,UAV flight data are preprocessed by combining the Savitzky-Golay filter data processing technique to mitigate the effect of noise in the original historical flight data on the model.Correlation-based feature subset selection is subsequently performed to reduce the reliance on expert knowledge.Then,the extracted features are used as the input of the designed LSTM-AE model to achieve the anomaly detection and recovery of UAV flight data in an unsupervised manner.Finally,the method's effectiveness is validated on real UAV flight data.展开更多
文摘The critical driving force for martensitic transformation fcc ( gamma ) yields hcp ( epsilon ) in ternary Fe-Mn-Si alloys increases with the content of Mn and decreases with that of Si. Thermodynamical prediction of M//s in ternary Fe-Mn-Si alloys was established. The fcc ( gamma ) yields hcp ( epsilon ) martensitic transformation in Fe-Mn-Si is a semi-thermoelastic and the nucleation process does not strongly depend on soft mode. Nucleation occurs directly through an overlapping of stacking fault rather than pole mechanism, and it is suggested that stacking fault energy (SFE) is the main factor controlling nucleation. Based on the phenomenological theory of martensite crystallography, a shuffle on (0001)//h//c//p plane is required when d//1//1//1 does not equal d//0//0//0//2. The derived principal strain in Bain distortion is smaller, i, e., more reasonable than the values given by Christian. Alloying elements strengthening the austenite, lowering SFE of gamma phase and reducing T//N** gamma temperature may be beneficial to shape memory effect of Fe-Mn-Si based alloys. Accordingly, Fe-Mn-Si-RE and Fe-Mn-Si-Cr-N (or Fe-Mn-Si-Ni-Cr-N) are worthy to be recommended as shape memory materials with improved shape memory effect. (Edited author abstract) 48 Refs.
基金The author is partly supported by the Grants-in-Aid for Scientific Reseach,The Ministry of Educa-ion,Science and Culture,Japan.
文摘Let M f be the Kakeya maximal function in d-dimensional Euclidean space, with same base consisting of cylinders of eccentricity N. The inequality shoum for a base satisfying a direction condition, where ?and c are constants depending only on d.
基金Supported by the National Basic Research Program of China under Grant Nos 2012CB723402 and 2014CB648300the National Natural Science Foundation of China under Grant Nos 61204095 and 61475074+3 种基金the National Science Fund for Excellent Young Scholars under Grant No 21322402the Natural Science Foundation of Jiangsu Province under Grant No BK2012431,the Natural Science Foundation of the Education Committee of Jiangsu Province under Grant No 14KJB510027the Ministry of Education of China under Grant No IRT1148the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘We investigate the memory properties of the ITO/graphene oxide/Al diodes. It is found that the devices show different memory behaviors with the diverse geometry and thickness of Al. When the thickness of the Al electrode is relatively thick, the device of the cross-point Al electrode shows a three-level memory effect, and the counterpart device of the cross-bar Al electrode exhibits a volatile static random access memory effect. When the thickness of the AI electrode is thinner, the above devices demonstrate a flash memory effect. The different memory behaviors of ITO/GO/AI diodes are ascribed to the mode and degree of reduction and oxidation of GO.
基金Supported by the National Basic Research Program of China under Grant No 2011CBA00602the National Key Scientific and Technological Project under Grant No 2013ZX01032001-001-003
文摘Impact of band-engineering to the performance of charge trapping memory with HfO2/Ta2O5/HfO2 （HTH） as the charge trapping layer is investigated. Compared with devices with the same total HfO2 thickness, structures with Ta2O5 closer to substrates show larger program/erase window, because the 2nd HfO2 （next to blocking oxide） serving as part of blocking oxide reduces the current tunneling out of/in the charge trapping layer during program and erase. Moreover, trapped charge centroid is modulated and contributed more to the fiat-band voltage shift. Further experiments prove that devices with a thicker 2nd HfO2 layer exhibit larger saturate fiat-band shift in both program and erase operation. The optimized device achieves a 7 V memory window and good reliability characteristics.
基金supported by the National Natural Science Foundation of China (Grant Nos. 11275131, 11371247, 11571313, and 11675113)
文摘Uncertainty principle is one of the most fascinating features of the quantum world. It asserts a fundamental limit on the precision with which certain pairs of physical properties of a particle, such as position and momentum, can not be si- multaneously known. The uncertainty principle has attracted considerable attention since the innovation of quantum me- chanics and has been investigated in terms of various types of uncertainty inequalities： in terms of the noise and dis- turbance, according to successive measurements, as informa- tional recourses in entropic terms, by means of majorization technique and based on sum of variances and standard devia- tions.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFB1713300)the Guizhou Provincial Colleges and Universities Talent Training Base Project(Grant No.[2020]009)+3 种基金the Guizhou Province Science and Technology Plan Project(Grant Nos.[2015]4011,[2017]5788)the Guizhou Provincial Department of Education Youth Science and Technology Talent Growth Project(Grant No.[2022]142)the Scientific Research Project for Introducing Talents from Guizhou University(Grant No.(2021)74)the Guizhou Province Higher Education Integrated Research Platform Project(Grant No.[2020]005)。
文摘Anomaly detection is crucial to the flight safety and maintenance of unmanned aerial vehicles(UAVs)and has attracted extensive attention from scholars.Knowledge-based approaches rely on prior knowledge,while model-based approaches are challenging for constructing accurate and complex physical models of unmanned aerial systems(UASs).Although data-driven methods do not require extensive prior knowledge and accurate physical UAS models,they often lack parameter selection and are limited by the cost of labeling anomalous data.Furthermore,flight data with random noise pose a significant challenge for anomaly detection.This work proposes a spatiotemporal correlation based on long short-term memory and autoencoder(STCLSTM-AE)neural network data-driven method for unsupervised anomaly detection and recovery of UAV flight data.First,UAV flight data are preprocessed by combining the Savitzky-Golay filter data processing technique to mitigate the effect of noise in the original historical flight data on the model.Correlation-based feature subset selection is subsequently performed to reduce the reliance on expert knowledge.Then,the extracted features are used as the input of the designed LSTM-AE model to achieve the anomaly detection and recovery of UAV flight data in an unsupervised manner.Finally,the method's effectiveness is validated on real UAV flight data.
