In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturban...In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.展开更多
INTRODUCTION Pangolin is the common name for animals in the Family Pholidota,Mammalia,which consists of eight extant species.All pangolin species have been listed as critically endangered(CR),endangered(EN),or vulnera...INTRODUCTION Pangolin is the common name for animals in the Family Pholidota,Mammalia,which consists of eight extant species.All pangolin species have been listed as critically endangered(CR),endangered(EN),or vulnerable(VU)species in the International Union for Conservation of Nature(IUCN)Red List of Threatened Species(Challender et al.2020).In June 2020,the Chinese government upgraded the Chinese pangolin(Manis pentadactyla Linnaeus,1758)from a national second-class protected animal to a national first-class protected animal.In February 2021,the Sunda pangolin(Manis javanica Desmarest,1822)and the Indian pangolin(Manis crassicaudata Geoffroy,1803)were added to the list of national first-class protected animals.However,the number of species of pangolins naturally distributed in China varies in the literature:Some sources have recorded only one species,namely the Chinese pangolin(Nowak&Paradiso 1983;Sheng 1999),while most have recorded two species,namely the Chinese pangolin and Indian pangolin(Allen 1938;Zhang 1997;Wang 2003;Wu et al.2005a;Hu&Hu 2017).展开更多
With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and live...With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and lives.To identify and classify new malware variants,different types of deep learning models have been widely explored recently.Generally,sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ability.However,in current practical applications,an ample supply of data is absent in most specific industrial malware detection scenarios.Transfer learning as an effective approach can be used to alleviate the influence of the small sample size problem.In addition,it can also reuse the knowledge from pretrained models,which is beneficial to the real-time requirement in industrial malware detection.In this paper,we investigate the transferable features learned by a 1D-convolutional network and evaluate our proposed methods on 6 transfer learning tasks.The experiment results show that 1D-convolutional architecture is effective to learn transferable features for malware classification,and indicate that transferring the first 2 layers of our proposed 1D-convolutional network is the most efficient way to reuse the learned features.展开更多
As the large single-crystalline silicon wafers have revolutionized many industries including electronics and solar cells, it is envisioned that the availability of large single-crystalline perovskite crystals and wafe...As the large single-crystalline silicon wafers have revolutionized many industries including electronics and solar cells, it is envisioned that the availability of large single-crystalline perovskite crystals and wafers will revolutionize its broad applications in photovoltaics, optoelectronics, lasers, photodetectors, light emitting diodes(LEDs), etc. Here we report a method to grow large single-crystalline perovskites including single-halide crystals: CH3NH3PbX3(X=I, Br, Cl), and dual-halide ones:CH3NH3Pb(ClxBr1.x)3 and CH3NH3Pb(BrxI1.x)3, with the largest crystal being 120 mm in length. Meanwhile, we have advanced a process to slice the large perovskite crystals into thin wafers. It is found that the wafers exhibit remarkable features:(1)its trap-state density is a million times smaller than that in the microcrystalline perovskite thin films(MPTF);(2) its carrier mobility is 410 times higher than its most popular organic counterpart P3HT;(3) its optical absorption is expanded to as high as910 nm comparing to 797 nm for the MPTF;(4) while MPTF decomposes at 150 °C, the wafer is stable at high temperature up to270 °C;(5) when exposed to high humidity(75% RH), MPTF decomposes in 5 h while the wafer shows no change for overnight;(6) its photocurrent response is 250 times higher than its MPTF counterpart. A few electronic devices have been fabricated using the crystalline wafers. Among them, the Hall test gives low carrier concentration with high mobility. The trap-state density is measured much lower than common semiconductors. Moreover, the large SC-wafer is found particularly useful for mass production of integrated circuits. By adjusting the halide composition, both the optical absorption and the light emission can be fine-tuned across the entire visible spectrum from 400 nm to 800 nm. It is envisioned that a range of visible lasers and LEDs may be developed using the dual-halide perovskites. With fewer trap states, high mobility, broader absorption, and humidity resistance, it is expected that solar cells with high stable efficiency maybe attainable using the crystalline wafers.展开更多
基金supported in part by the National Natural Science Foundation of China(61473080,61573099,61973080,61750110525,61633003)。
文摘In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.
基金funded by the National Key Program of Research and Development,Ministry of Science and Technology(No.2022YFF1301500)the National Nature Science Foundation of China(No.32070522)。
文摘INTRODUCTION Pangolin is the common name for animals in the Family Pholidota,Mammalia,which consists of eight extant species.All pangolin species have been listed as critically endangered(CR),endangered(EN),or vulnerable(VU)species in the International Union for Conservation of Nature(IUCN)Red List of Threatened Species(Challender et al.2020).In June 2020,the Chinese government upgraded the Chinese pangolin(Manis pentadactyla Linnaeus,1758)from a national second-class protected animal to a national first-class protected animal.In February 2021,the Sunda pangolin(Manis javanica Desmarest,1822)and the Indian pangolin(Manis crassicaudata Geoffroy,1803)were added to the list of national first-class protected animals.However,the number of species of pangolins naturally distributed in China varies in the literature:Some sources have recorded only one species,namely the Chinese pangolin(Nowak&Paradiso 1983;Sheng 1999),while most have recorded two species,namely the Chinese pangolin and Indian pangolin(Allen 1938;Zhang 1997;Wang 2003;Wu et al.2005a;Hu&Hu 2017).
基金the National Natural Science Foundation of China under Grants U1836106 and 81961138010the Beijing Natural Science Foundation under Grants 19L2029 and M21032+2 种基金the Scientific and Technological Innovation Foundation of Foshan under Grants BK20BF010 and BK21BF001the Scientific and Technological Innovation Foundation of Shunde Graduate School,USTB,under Grant BK19BF006by the Fundamental Research Funds for the University of Science and Technology Beijing under Grant FRF-BD-19-012A.
文摘With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and lives.To identify and classify new malware variants,different types of deep learning models have been widely explored recently.Generally,sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ability.However,in current practical applications,an ample supply of data is absent in most specific industrial malware detection scenarios.Transfer learning as an effective approach can be used to alleviate the influence of the small sample size problem.In addition,it can also reuse the knowledge from pretrained models,which is beneficial to the real-time requirement in industrial malware detection.In this paper,we investigate the transferable features learned by a 1D-convolutional network and evaluate our proposed methods on 6 transfer learning tasks.The experiment results show that 1D-convolutional architecture is effective to learn transferable features for malware classification,and indicate that transferring the first 2 layers of our proposed 1D-convolutional network is the most efficient way to reuse the learned features.
基金supported by the National Key Research Project MOST (2016YFA0202400)the National Natural Science Foundation of China (61604090, 61604091, 61674098)+4 种基金National University Research Fund (GK261001009, GK201603107)the Changjiang Scholar and Innovative Research Team (IRT_14R33)the 111 Project (B14041)the Chinese National 1000-talent-plan Program (1110010341)the Innovation Funds of Graduate Programs, SNNU (2015CXS047)
文摘As the large single-crystalline silicon wafers have revolutionized many industries including electronics and solar cells, it is envisioned that the availability of large single-crystalline perovskite crystals and wafers will revolutionize its broad applications in photovoltaics, optoelectronics, lasers, photodetectors, light emitting diodes(LEDs), etc. Here we report a method to grow large single-crystalline perovskites including single-halide crystals: CH3NH3PbX3(X=I, Br, Cl), and dual-halide ones:CH3NH3Pb(ClxBr1.x)3 and CH3NH3Pb(BrxI1.x)3, with the largest crystal being 120 mm in length. Meanwhile, we have advanced a process to slice the large perovskite crystals into thin wafers. It is found that the wafers exhibit remarkable features:(1)its trap-state density is a million times smaller than that in the microcrystalline perovskite thin films(MPTF);(2) its carrier mobility is 410 times higher than its most popular organic counterpart P3HT;(3) its optical absorption is expanded to as high as910 nm comparing to 797 nm for the MPTF;(4) while MPTF decomposes at 150 °C, the wafer is stable at high temperature up to270 °C;(5) when exposed to high humidity(75% RH), MPTF decomposes in 5 h while the wafer shows no change for overnight;(6) its photocurrent response is 250 times higher than its MPTF counterpart. A few electronic devices have been fabricated using the crystalline wafers. Among them, the Hall test gives low carrier concentration with high mobility. The trap-state density is measured much lower than common semiconductors. Moreover, the large SC-wafer is found particularly useful for mass production of integrated circuits. By adjusting the halide composition, both the optical absorption and the light emission can be fine-tuned across the entire visible spectrum from 400 nm to 800 nm. It is envisioned that a range of visible lasers and LEDs may be developed using the dual-halide perovskites. With fewer trap states, high mobility, broader absorption, and humidity resistance, it is expected that solar cells with high stable efficiency maybe attainable using the crystalline wafers.