Dual-frequency multi-constellation(DFMC) satellitebased augmentation system(SBAS) does not broadcast fast correction, which is important in reducing range error in L1-only SBAS.Meanwhile, the integrity bound of a sate...Dual-frequency multi-constellation(DFMC) satellitebased augmentation system(SBAS) does not broadcast fast correction, which is important in reducing range error in L1-only SBAS.Meanwhile, the integrity bound of a satellite at low elevation is so loose that the service availability is decreased near the boundary of the service area. Therefore, the computation of satellite clockephemeris(SCE) augmentation parameters needs improvement.We propose a method introducing SCE prediction to eliminate most of the SCE error resulting from global navigation satellite system GNSS broadcast message. Compared with the signal-inspace(SIS) after applying augmentation parameters broadcast by the wide area augmentation system(WAAS), SIS accuracy after applying augmentation parameters computed by the proposed algorithm is improved and SIS integrity is ensured. With global positioning system(GPS) only, the availability of category-I(CAT-I)with a vertical alert level of 15 m in continental United States is about 90%, while the availability in the other part of the WAAS service area is markedly improved. With measurements made by the stations from the crustal movement observation network of China,users in some part of China can obtain CAT-I(vertical alert limit is 15 m) service with GPS and global navigation satellite system(GLONASS).展开更多
Automatically recognizing radar emitters from com-plex electromagnetic environments is important but non-trivial.Moreover,the changing electromagnetic environment results in inconsistent signal distribution in the rea...Automatically recognizing radar emitters from com-plex electromagnetic environments is important but non-trivial.Moreover,the changing electromagnetic environment results in inconsistent signal distribution in the real world,which makes the existing approaches perform poorly for recognition tasks in different scenes.In this paper,we propose a domain generaliza-tion framework is proposed to improve the adaptability of radar emitter signal recognition in changing environments.Specifically,we propose an end-to-end denoising based domain-invariant radar emitter recognition network(DDIRNet)consisting of a denoising model and a domain invariant representation learning model(IRLM),which mutually benefit from each other.For the signal denoising model,a loss function is proposed to match the feature of the radar signals and guarantee the effectiveness of the model.For the domain invariant representation learning model,contrastive learning is introduced to learn the cross-domain feature by aligning the source and unseen domain distri-bution.Moreover,we design a data augmentation method that improves the diversity of signal data for training.Extensive experiments on classification have shown that DDIRNet achieves up to 6.4%improvement compared with the state-of-the-art radar emitter recognition methods.The proposed method pro-vides a promising direction to solve the radar emitter signal recognition problem.展开更多
A design and verification of linear state observers which estimate state information such as angular velocity and load torque for retraction control of the motorized seat belt (MSB) system were described. The motorize...A design and verification of linear state observers which estimate state information such as angular velocity and load torque for retraction control of the motorized seat belt (MSB) system were described. The motorized seat belt system provides functions to protect passengers and improve passenger's convenience. Each MSB function has its own required belt tension which is determined by the function's purpose. To realize the MSB functions, state information, such as seat belt winding velocity and seat belt tension are required. Using a linear state observer, the state information for MSB operations can be estimated without sensors. To design the linear state observer, the motorized seat belt system is analyzed and represented as a state space model which contains load torque as an augmented state. Based on the state space model, a linear state observer was designed and verified by experiments. Also, the retraction control of the MSB algorithm using linear state observer was designed and verified on the test bench. With the designed retraction control algorithm using the linear state observer, it is possible to realize various types of MSB functions.展开更多
In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A...In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.展开更多
Convolutional neural networks(CNNs)are well suited to bearing fault classification due to their ability to learn discriminative spectro-temporal patterns.However,gathering sufficient cases of faulty conditions in real...Convolutional neural networks(CNNs)are well suited to bearing fault classification due to their ability to learn discriminative spectro-temporal patterns.However,gathering sufficient cases of faulty conditions in real-world engineering scenarios to train an intelligent diagnosis system is challenging.This paper proposes a fault diagnosis method combining several augmentation schemes to alleviate the problem of limited fault data.We begin by identifying relevant parameters that influence the construction of a spectrogram.We leverage the uncertainty principle in processing time-frequency domain signals,making it impossible to simultaneously achieve good time and frequency resolutions.A key determinant of this phenomenon is the window function's choice and length used in implementing the shorttime Fourier transform.The Gaussian,Kaiser,and rectangular windows are selected in the experimentation due to their diverse characteristics.The overlap parameter's size also influences the outcome and resolution of the spectrogram.A 50%overlap is used in the original data transformation,and±25%is used in implementing an effective augmentation policy to which two-stage regular CNN can be applied to achieve improved performance.The best model reaches an accuracy of 99.98%and a cross-domain accuracy of 92.54%.When combined with data augmentation,the proposed model yields cutting-edge results.展开更多
A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential...A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.展开更多
Objective:Augmented renal clearance(ARC),in contrast to renal dysfunction,refers to enhanced renal elimination of circulating solutes compared to the expected baseline.Although patients may present with normal serum c...Objective:Augmented renal clearance(ARC),in contrast to renal dysfunction,refers to enhanced renal elimination of circulating solutes compared to the expected baseline.Although patients may present with normal serum creatinine(Scr)levels,the incidence of ARC is high in intensive care unit(ICU)settings.ARC is associated with subtherapeutic exposure and treatment failure of renally cleared antibiotics.However,limited research exists on the incidence and risk factors of ARC in the ICU,and even fewer data are available specifically for neurological ICU(NICU).This study aims to determine the incidence and risk factors of ARC in neurocritically ill patients.Methods:We retrospectively analyzed all available Scr data of neurocritical care patients admitted to the NICU of the Second Xiangya Hospital of Central South University between December 2020 and January 2023.Creatinine clearance(CrCl)was calculated using the Cockcroft-Gault equation.ARC was defined as a CrCl≥130 mL/(min·1.73 m^(2))sustained for more than 50%of the duration of the NICU stay.A total of 208 neurocritically ill patients were assigned into an ARC group(n=52)and a non-ARC(N-ARC)group(n=156).Clinical characteristics were compared between the 2 groups.Variables with P<0.05 in univariate analysis were included in binary Logistic regression to identify independent risk factors for ARC.Results:The incidence of ARC among neurocritically ill patients was 25.00%.Of the 74 patients with normal CrCl,20(27.03%)gradually developed ARC during hospitalization.Compared with the N-ARC group,the patients of the ARC group were younger(P<0.001),with a higher proportion of females(P=0.048)and a lower admission mean arterial pressure(MAP)(P=0.034).Moreover,patients of the ARC group were commonly complicated with severe bacterial infections compared with the patients of the N-ARC group(P<0.001).In binary Logistic regression analysis,younger age(OR=0.903,95%CI 0.872 to 0.935)and severe bacterial infections(OR=6.270,95%CI 2.568 to 15.310)were significant predictors of ARC.Conclusion:ARC is relatively common in the NICU.A considerable number of patients with initially normal renal function developed ARC during hospitalization.Younger age and concurrent severe bacterial infection are important risk factors of ARC in neurocritically ill patients.展开更多
It has been proven that carrier smoothing and differential global positioning system （DGPS） are effective to improve the accuracy of pseudorange by reducing the noise in it and eliminating almost all the common mode...It has been proven that carrier smoothing and differential global positioning system （DGPS） are effective to improve the accuracy of pseudorange by reducing the noise in it and eliminating almost all the common mode errors between the ground station and user. However, another issue coming with local area augmentation system （LAAS） is how to find an adaptive smoothing window width to minimize the error on account of ionosphere delay and multipath. Based on the errors analysis in carrier smoothing process, a novel algorithm is formulated to design adaptive Hatch filter whose smoothing window width flexibly varies with the characteristic of ionosphere delay and multipath in the differential carrier smoothing process. By conducting the simulation in LAAS and after compared with traditional Hatch filers, it reveals that not only the accuracy of differential correction, but also the accuracy and the robustness of positioning results are significantly improved by using the designed adaptive Hatch filter.展开更多
In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight tech...In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.展开更多
The contact resistance between the armature and rails is an important indicator of the contact characteristics in electromagnetic launches.As the contact resistance depends not only on the contact state but also on th...The contact resistance between the armature and rails is an important indicator of the contact characteristics in electromagnetic launches.As the contact resistance depends not only on the contact state but also on the contact stress and temperature,there are some limitations in analyzing the contact characteristics using only the contact resistance.In this paper,the contact characteristics of the augmented railgun are analyzed by the combination of contact resistance and sliding friction coefficient.Firstly,the theoretical calculation model of the contact resistance and friction coefficient of the augmented electromagnetic railgun is established.Then the contact resistance and friction coefficient are calculated by the measured values of the muzzle voltage,rail current and armature displacement.Finally,the contact characteristics are analyzed according to the features of the waveforms of the contact resistance and the friction coefficient,and the analysis conclusions are verified by experimental rail images.The results showed that:the aluminum melt film gradually formed on the contact surface reduces the contact resistance and the friction coefficient;the wear and erosion of the armature cause deterioration of the contact state;after the transition,the reliability of the sliding contact between the armature and rails decreases,resulting in an increase in contact resistance.展开更多
develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining...develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.展开更多
文摘Dual-frequency multi-constellation(DFMC) satellitebased augmentation system(SBAS) does not broadcast fast correction, which is important in reducing range error in L1-only SBAS.Meanwhile, the integrity bound of a satellite at low elevation is so loose that the service availability is decreased near the boundary of the service area. Therefore, the computation of satellite clockephemeris(SCE) augmentation parameters needs improvement.We propose a method introducing SCE prediction to eliminate most of the SCE error resulting from global navigation satellite system GNSS broadcast message. Compared with the signal-inspace(SIS) after applying augmentation parameters broadcast by the wide area augmentation system(WAAS), SIS accuracy after applying augmentation parameters computed by the proposed algorithm is improved and SIS integrity is ensured. With global positioning system(GPS) only, the availability of category-I(CAT-I)with a vertical alert level of 15 m in continental United States is about 90%, while the availability in the other part of the WAAS service area is markedly improved. With measurements made by the stations from the crustal movement observation network of China,users in some part of China can obtain CAT-I(vertical alert limit is 15 m) service with GPS and global navigation satellite system(GLONASS).
基金supported by the National Natural Science Foundation of China(62101575)the Research Project of NUDT(ZK22-57)the Self-directed Project of State Key Laboratory of High Performance Computing(202101-16).
文摘Automatically recognizing radar emitters from com-plex electromagnetic environments is important but non-trivial.Moreover,the changing electromagnetic environment results in inconsistent signal distribution in the real world,which makes the existing approaches perform poorly for recognition tasks in different scenes.In this paper,we propose a domain generaliza-tion framework is proposed to improve the adaptability of radar emitter signal recognition in changing environments.Specifically,we propose an end-to-end denoising based domain-invariant radar emitter recognition network(DDIRNet)consisting of a denoising model and a domain invariant representation learning model(IRLM),which mutually benefit from each other.For the signal denoising model,a loss function is proposed to match the feature of the radar signals and guarantee the effectiveness of the model.For the domain invariant representation learning model,contrastive learning is introduced to learn the cross-domain feature by aligning the source and unseen domain distri-bution.Moreover,we design a data augmentation method that improves the diversity of signal data for training.Extensive experiments on classification have shown that DDIRNet achieves up to 6.4%improvement compared with the state-of-the-art radar emitter recognition methods.The proposed method pro-vides a promising direction to solve the radar emitter signal recognition problem.
基金Project supported by the Second Stage of Brain Korea 21 Projects and Changwon National University in 2011-2012
文摘A design and verification of linear state observers which estimate state information such as angular velocity and load torque for retraction control of the motorized seat belt (MSB) system were described. The motorized seat belt system provides functions to protect passengers and improve passenger's convenience. Each MSB function has its own required belt tension which is determined by the function's purpose. To realize the MSB functions, state information, such as seat belt winding velocity and seat belt tension are required. Using a linear state observer, the state information for MSB operations can be estimated without sensors. To design the linear state observer, the motorized seat belt system is analyzed and represented as a state space model which contains load torque as an augmented state. Based on the state space model, a linear state observer was designed and verified by experiments. Also, the retraction control of the MSB algorithm using linear state observer was designed and verified on the test bench. With the designed retraction control algorithm using the linear state observer, it is possible to realize various types of MSB functions.
基金supported by the National Natural Science Foundation of China(91538201)
文摘In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.
基金supported by the National Natural Science Foundation of China(42027805)the National Aeronautical Fund(ASFC-20172080005)。
文摘Convolutional neural networks(CNNs)are well suited to bearing fault classification due to their ability to learn discriminative spectro-temporal patterns.However,gathering sufficient cases of faulty conditions in real-world engineering scenarios to train an intelligent diagnosis system is challenging.This paper proposes a fault diagnosis method combining several augmentation schemes to alleviate the problem of limited fault data.We begin by identifying relevant parameters that influence the construction of a spectrogram.We leverage the uncertainty principle in processing time-frequency domain signals,making it impossible to simultaneously achieve good time and frequency resolutions.A key determinant of this phenomenon is the window function's choice and length used in implementing the shorttime Fourier transform.The Gaussian,Kaiser,and rectangular windows are selected in the experimentation due to their diverse characteristics.The overlap parameter's size also influences the outcome and resolution of the spectrogram.A 50%overlap is used in the original data transformation,and±25%is used in implementing an effective augmentation policy to which two-stage regular CNN can be applied to achieve improved performance.The best model reaches an accuracy of 99.98%and a cross-domain accuracy of 92.54%.When combined with data augmentation,the proposed model yields cutting-edge results.
基金Project supported by the Changwon National University(2013-2014),Korea
文摘A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.
基金supported by the Natural Science Foundation of Hunan Province(2023JJ60087)the Clinical Medical Technology Innovation Guidance Project of Hunan Province(2021SK53501),China。
文摘Objective:Augmented renal clearance(ARC),in contrast to renal dysfunction,refers to enhanced renal elimination of circulating solutes compared to the expected baseline.Although patients may present with normal serum creatinine(Scr)levels,the incidence of ARC is high in intensive care unit(ICU)settings.ARC is associated with subtherapeutic exposure and treatment failure of renally cleared antibiotics.However,limited research exists on the incidence and risk factors of ARC in the ICU,and even fewer data are available specifically for neurological ICU(NICU).This study aims to determine the incidence and risk factors of ARC in neurocritically ill patients.Methods:We retrospectively analyzed all available Scr data of neurocritical care patients admitted to the NICU of the Second Xiangya Hospital of Central South University between December 2020 and January 2023.Creatinine clearance(CrCl)was calculated using the Cockcroft-Gault equation.ARC was defined as a CrCl≥130 mL/(min·1.73 m^(2))sustained for more than 50%of the duration of the NICU stay.A total of 208 neurocritically ill patients were assigned into an ARC group(n=52)and a non-ARC(N-ARC)group(n=156).Clinical characteristics were compared between the 2 groups.Variables with P<0.05 in univariate analysis were included in binary Logistic regression to identify independent risk factors for ARC.Results:The incidence of ARC among neurocritically ill patients was 25.00%.Of the 74 patients with normal CrCl,20(27.03%)gradually developed ARC during hospitalization.Compared with the N-ARC group,the patients of the ARC group were younger(P<0.001),with a higher proportion of females(P=0.048)and a lower admission mean arterial pressure(MAP)(P=0.034).Moreover,patients of the ARC group were commonly complicated with severe bacterial infections compared with the patients of the N-ARC group(P<0.001).In binary Logistic regression analysis,younger age(OR=0.903,95%CI 0.872 to 0.935)and severe bacterial infections(OR=6.270,95%CI 2.568 to 15.310)were significant predictors of ARC.Conclusion:ARC is relatively common in the NICU.A considerable number of patients with initially normal renal function developed ARC during hospitalization.Younger age and concurrent severe bacterial infection are important risk factors of ARC in neurocritically ill patients.
基金supported by the National Natural Science Foundationof China (60974104)the National Defense Technical Foundation of Shipbuilding Industry (08J3.8.8)
文摘It has been proven that carrier smoothing and differential global positioning system （DGPS） are effective to improve the accuracy of pseudorange by reducing the noise in it and eliminating almost all the common mode errors between the ground station and user. However, another issue coming with local area augmentation system （LAAS） is how to find an adaptive smoothing window width to minimize the error on account of ionosphere delay and multipath. Based on the errors analysis in carrier smoothing process, a novel algorithm is formulated to design adaptive Hatch filter whose smoothing window width flexibly varies with the characteristic of ionosphere delay and multipath in the differential carrier smoothing process. By conducting the simulation in LAAS and after compared with traditional Hatch filers, it reveals that not only the accuracy of differential correction, but also the accuracy and the robustness of positioning results are significantly improved by using the designed adaptive Hatch filter.
基金supported by the Foundation of Shanghai Aerospace Science and Technology(SAST2016077)。
文摘In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.
文摘The contact resistance between the armature and rails is an important indicator of the contact characteristics in electromagnetic launches.As the contact resistance depends not only on the contact state but also on the contact stress and temperature,there are some limitations in analyzing the contact characteristics using only the contact resistance.In this paper,the contact characteristics of the augmented railgun are analyzed by the combination of contact resistance and sliding friction coefficient.Firstly,the theoretical calculation model of the contact resistance and friction coefficient of the augmented electromagnetic railgun is established.Then the contact resistance and friction coefficient are calculated by the measured values of the muzzle voltage,rail current and armature displacement.Finally,the contact characteristics are analyzed according to the features of the waveforms of the contact resistance and the friction coefficient,and the analysis conclusions are verified by experimental rail images.The results showed that:the aluminum melt film gradually formed on the contact surface reduces the contact resistance and the friction coefficient;the wear and erosion of the armature cause deterioration of the contact state;after the transition,the reliability of the sliding contact between the armature and rails decreases,resulting in an increase in contact resistance.
基金supported by the National Natural Science Foundation of China under Grant No.11371001
文摘develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.
