Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since...Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.展开更多
Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been c...Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.展开更多
We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc...We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc-ing control methods,the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control.Besides,the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking.A cost function was con-structed to achieve the high-precision grid-connected control of the CHB inverter.Finally,the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules.展开更多
The membrane fouling phenomenon,reflected with various fouling characterization in the membrane bioreactor(MBR)process,is so complicated to distinguish.This paper proposes a multivariable identification model(MIM)base...The membrane fouling phenomenon,reflected with various fouling characterization in the membrane bioreactor(MBR)process,is so complicated to distinguish.This paper proposes a multivariable identification model(MIM)based on a compacted cascade neural network to identify membrane fouling accurately.Firstly,a multivariable model is proposed to calculate multiple indicators of membrane fouling using a cascade neural network,which could avoid the interference of the overlap inputs.Secondly,an unsupervised pretraining algorithm was developed with periodic information of membrane fouling to obtain the compact structure of MIM.Thirdly,a hierarchical learning algorithm was proposed to update the parameters of MIM for improving the identification accuracy online.Finally,the proposed model was tested in real plants to evaluate its efficiency and effectiveness.Experimental results have verified the benefits of the proposed method.展开更多
The thermal diffusion column represents one method of separating stable isotopes.This method is advantageous for smallscale operations because of the simplicity of the apparatus and small inventory,especially in gas-p...The thermal diffusion column represents one method of separating stable isotopes.This method is advantageous for smallscale operations because of the simplicity of the apparatus and small inventory,especially in gas-phase operations.Consequently,it has attracted attention for its applicability in tritium and noble gas separation systems.In this study,the R cascade was used to design and determine the number of columns.A square cascade was adopted for the final design because of its flexibility,and calculations were performed to separate 20Ne and 22Ne isotopes.All the R cascades that enriched the Ne isotopes by more than 99%were investigated,the number of columns was determined,and the square cascade parameters were optimized using the specified columns.Additionally,a calculation code“RSQ_CASCADE”was developed.A unit separation factor of three was considered,and the number of studied stages ranged from 10 to 20.The results showed that the column separation power,relative total flow rate,and required number of columns were linearly related to the number of stages.The separation power and relative total flow decreased and the number of columns increased as the stage number increased.Therefore,a cascade of 85 columns is recommended to separate the stable Ne isotopes.These calculations yielded a 17-stage square cascade with five columns in each stage.By changing the stage cut,feed point,and cascade feed flow rate,the best parameters for the square cascade were determined according to the cascade and column separation powers.As the column separation power had a maximum value in cascade feed 50,it was selected for separating Ne isotopes.展开更多
For mode selection in a quantum cascade laser(QCL),we demonstrate an anti-symmetric sampled grating(ASG).The wavelength of the-1-th mode of this laser has been blue-shifted more than 75 nm(~10 cm^(-1))compared with th...For mode selection in a quantum cascade laser(QCL),we demonstrate an anti-symmetric sampled grating(ASG).The wavelength of the-1-th mode of this laser has been blue-shifted more than 75 nm(~10 cm^(-1))compared with that of an ordinary sampled grating laser with an emission wavelength of approximately 8.6μm,when the periodicities within both the base grating and the sample grating are kept constant.Under this condition,an improvement in the continuous tuning capability of the QCL array is ensured.The ASG structure is fabricated in holographic exposure and optical photolithography,thereby enhancing its flexibility,repeatability,and cost-effectiveness.The wavelength modulation capability of the two channels of the grating is insensitive to the variations in channel size,assuming that the overall waveguide width remains constant.The output wavelength can be tailored freely within a certain range by adjusting the width of the ridge and the material of the cladding layer.展开更多
Sharing the advantages of high optical power,high efficiency and design flexibility in a compact size,quantum cascade lasers(QCLs)are excellent mid-to-far infrared laser sources for gas sensing,infrared spectroscopic,...Sharing the advantages of high optical power,high efficiency and design flexibility in a compact size,quantum cascade lasers(QCLs)are excellent mid-to-far infrared laser sources for gas sensing,infrared spectroscopic,medical diagnosis,and defense applications.Metalorganic chemical vapor deposition(MOCVD)is an important technology for growing high quality semiconductor materials,and has achieved great success in the semiconductor industry due to its advantages of high efficiency,short maintenance cycles,and high stability and repeatability.The utilization of MOCVD for the growth of QCL materials holds a significant meaning for promoting the large batch production and industrial application of QCL devices.This review summarizes the recent progress of QCLs grown by MOCVD.Material quality and the structure design together determine the device performance.Research progress on the performance improvement of MOCVD-grown QCLs based on the optimization of material quality and active region structure are mainly reviewed.展开更多
This paper proposes a cascade deep convolutional neural network to address the loosening detection problem of bolts on axlebox covers.Firstly,an SSD network based on ResNet50 and CBAM module by improving bolt image fe...This paper proposes a cascade deep convolutional neural network to address the loosening detection problem of bolts on axlebox covers.Firstly,an SSD network based on ResNet50 and CBAM module by improving bolt image features is proposed for locating bolts on axlebox covers.And then,theA2-PFN is proposed according to the slender features of the marker lines for extracting more accurate marker lines regions of the bolts.Finally,a rectangular approximationmethod is proposed to regularize themarker line regions asaway tocalculate the angle of themarker line and plot all the angle values into an angle table,according to which the criteria of the angle table can determine whether the bolt with the marker line is in danger of loosening.Meanwhile,our improved algorithm is compared with the pre-improved algorithmin the object localization stage.The results show that our proposed method has a significant improvement in both detection accuracy and detection speed,where ourmAP(IoU=0.75)reaches 0.77 and fps reaches 16.6.And in the saliency detection stage,after qualitative comparison and quantitative comparison,our method significantly outperforms other state-of-the-art methods,where our MAE reaches 0.092,F-measure reaches 0.948 and AUC reaches 0.943.Ultimately,according to the angle table,out of 676 bolt samples,a total of 60 bolts are loose,69 bolts are at risk of loosening,and 547 bolts are tightened.展开更多
基金support from the National Natural Science Foundation of China (No.62005164,62222507,62175101,and 62005166)the Shanghai Natural Science Foundation (23ZR1443700)+3 种基金Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission (23SG41)the Young Elite Scientist Sponsorship Program by CAST (No.20220042)Science and Technology Commission of Shanghai Municipality (Grant No.21DZ1100500)the Shanghai Municipal Science and Technology Major Project,and the Shanghai Frontiers Science Center Program (2021-2025 No.20).
文摘Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.
基金The authors acknowledge the funding provided by the National Key R&D Program of China(2021YFA1401200)Beijing Outstanding Young Scientist Program(BJJWZYJH01201910007022)+2 种基金National Natural Science Foundation of China(No.U21A20140,No.92050117,No.62005017)programBeijing Municipal Science&Technology Commission,Administrative Commission of Zhongguancun Science Park(No.Z211100004821009)This work was supported by the Synergetic Extreme Condition User Facility(SECUF).
文摘Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.
基金Research on Control Methods and Fault Tolerance of Multilevel Electronic Transformers for PV Access(Project number:042300034204)Research on Open-Circuit Fault Diagnosis and Seamless Fault-Tolerant Control of Multiple Devices in Modular Multilevel Digital Power Amplifiers(Project number:202203021212210)Research on Key Technologies and Demonstrations of Low-Voltage DC Power Electronic Converters Based on SiC Devices Access(Project number:202102060301012)。
文摘We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc-ing control methods,the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control.Besides,the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking.A cost function was con-structed to achieve the high-precision grid-connected control of the CHB inverter.Finally,the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules.
基金supports by National Key Research and Development Project(2018YFC1900800-5)National Natural Science Foundation of China(61890930-5,62021003,61903010 and 62103012)+1 种基金Beijing Outstanding Young Scientist Program(BJJWZYJH01201910005020)Beijing Natural Science Foundation(KZ202110005009 and 4214068).
文摘The membrane fouling phenomenon,reflected with various fouling characterization in the membrane bioreactor(MBR)process,is so complicated to distinguish.This paper proposes a multivariable identification model(MIM)based on a compacted cascade neural network to identify membrane fouling accurately.Firstly,a multivariable model is proposed to calculate multiple indicators of membrane fouling using a cascade neural network,which could avoid the interference of the overlap inputs.Secondly,an unsupervised pretraining algorithm was developed with periodic information of membrane fouling to obtain the compact structure of MIM.Thirdly,a hierarchical learning algorithm was proposed to update the parameters of MIM for improving the identification accuracy online.Finally,the proposed model was tested in real plants to evaluate its efficiency and effectiveness.Experimental results have verified the benefits of the proposed method.
文摘The thermal diffusion column represents one method of separating stable isotopes.This method is advantageous for smallscale operations because of the simplicity of the apparatus and small inventory,especially in gas-phase operations.Consequently,it has attracted attention for its applicability in tritium and noble gas separation systems.In this study,the R cascade was used to design and determine the number of columns.A square cascade was adopted for the final design because of its flexibility,and calculations were performed to separate 20Ne and 22Ne isotopes.All the R cascades that enriched the Ne isotopes by more than 99%were investigated,the number of columns was determined,and the square cascade parameters were optimized using the specified columns.Additionally,a calculation code“RSQ_CASCADE”was developed.A unit separation factor of three was considered,and the number of studied stages ranged from 10 to 20.The results showed that the column separation power,relative total flow rate,and required number of columns were linearly related to the number of stages.The separation power and relative total flow decreased and the number of columns increased as the stage number increased.Therefore,a cascade of 85 columns is recommended to separate the stable Ne isotopes.These calculations yielded a 17-stage square cascade with five columns in each stage.By changing the stage cut,feed point,and cascade feed flow rate,the best parameters for the square cascade were determined according to the cascade and column separation powers.As the column separation power had a maximum value in cascade feed 50,it was selected for separating Ne isotopes.
基金Project supported by the National Basic Research Program of China (Grant No. 2021YFB3201900)in part by the National Natural Science Foundation of China (Grant Nos. 61991430, 61774146, 61790583,61627822, and 61774150)in part by the Key Projects of the Chinese Academy of Sciences (Grant Nos. 2018147, YJKYYQ20190002, QYZDJ-SSW-JSC027,XDB43000000)
文摘For mode selection in a quantum cascade laser(QCL),we demonstrate an anti-symmetric sampled grating(ASG).The wavelength of the-1-th mode of this laser has been blue-shifted more than 75 nm(~10 cm^(-1))compared with that of an ordinary sampled grating laser with an emission wavelength of approximately 8.6μm,when the periodicities within both the base grating and the sample grating are kept constant.Under this condition,an improvement in the continuous tuning capability of the QCL array is ensured.The ASG structure is fabricated in holographic exposure and optical photolithography,thereby enhancing its flexibility,repeatability,and cost-effectiveness.The wavelength modulation capability of the two channels of the grating is insensitive to the variations in channel size,assuming that the overall waveguide width remains constant.The output wavelength can be tailored freely within a certain range by adjusting the width of the ridge and the material of the cladding layer.
基金supported by National Key Research and Development Program of China (Grant No.2021YFB3201900)National Natural Science Foundation of China (Grant Nos.61991430,62235016)+1 种基金Youth Innovation Promotion Association of CAS (Grant Nos.2022112,Y2022046)Key projects of the Chinese Academy of Sciences (Grant No.XDB43000000)。
文摘Sharing the advantages of high optical power,high efficiency and design flexibility in a compact size,quantum cascade lasers(QCLs)are excellent mid-to-far infrared laser sources for gas sensing,infrared spectroscopic,medical diagnosis,and defense applications.Metalorganic chemical vapor deposition(MOCVD)is an important technology for growing high quality semiconductor materials,and has achieved great success in the semiconductor industry due to its advantages of high efficiency,short maintenance cycles,and high stability and repeatability.The utilization of MOCVD for the growth of QCL materials holds a significant meaning for promoting the large batch production and industrial application of QCL devices.This review summarizes the recent progress of QCLs grown by MOCVD.Material quality and the structure design together determine the device performance.Research progress on the performance improvement of MOCVD-grown QCLs based on the optimization of material quality and active region structure are mainly reviewed.
文摘This paper proposes a cascade deep convolutional neural network to address the loosening detection problem of bolts on axlebox covers.Firstly,an SSD network based on ResNet50 and CBAM module by improving bolt image features is proposed for locating bolts on axlebox covers.And then,theA2-PFN is proposed according to the slender features of the marker lines for extracting more accurate marker lines regions of the bolts.Finally,a rectangular approximationmethod is proposed to regularize themarker line regions asaway tocalculate the angle of themarker line and plot all the angle values into an angle table,according to which the criteria of the angle table can determine whether the bolt with the marker line is in danger of loosening.Meanwhile,our improved algorithm is compared with the pre-improved algorithmin the object localization stage.The results show that our proposed method has a significant improvement in both detection accuracy and detection speed,where ourmAP(IoU=0.75)reaches 0.77 and fps reaches 16.6.And in the saliency detection stage,after qualitative comparison and quantitative comparison,our method significantly outperforms other state-of-the-art methods,where our MAE reaches 0.092,F-measure reaches 0.948 and AUC reaches 0.943.Ultimately,according to the angle table,out of 676 bolt samples,a total of 60 bolts are loose,69 bolts are at risk of loosening,and 547 bolts are tightened.