Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth sta...Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.展开更多
Sleep and well-being have been intricately linked,and sleep hygiene is paramount for developing mental well-being and resilience.Although widespread,sleep disorders require elaborate polysomnography laboratory and pat...Sleep and well-being have been intricately linked,and sleep hygiene is paramount for developing mental well-being and resilience.Although widespread,sleep disorders require elaborate polysomnography laboratory and patient-stay with sleep in unfamiliar environments.Current technologies have allowed various devices to diagnose sleep disorders at home.However,these devices are in various validation stages,with many already receiving approvals from competent authorities.This has captured vast patient-related physiologic data for advanced analytics using artificial intelligence through machine and deep learning applications.This is expected to be integrated with patients’Electronic Health Records and provide individualized prescriptive therapy for sleep disorders in the future.展开更多
The“counterpart aid to Xinjiang”is one of the important measures to implement the country’s western development strategy.It aims to shorten the gap between higher education in Xinjiang and the eastern region and to...The“counterpart aid to Xinjiang”is one of the important measures to implement the country’s western development strategy.It aims to shorten the gap between higher education in Xinjiang and the eastern region and to maintain the coordinated development of education,economy and society in the eastern and western regions.This article takes the counterpart support of Xinjiang students from the School of Foreign Languages of Jilin Engineering Normal University as an example to explore the problem of the initiative training of Xinjiang students in English learning in our school,mainly from the aspects of the students themselves,the teachers and the entire education and training environment of our school.The angle explains how to help them improve their learning initiative.This article is divided into three parts.The first is the analysis of the connotation of learning initiative;the second is its meaning;the last is how to build the learning initiative of Xinjiang students.展开更多
With the deepening of exchanges between China and other countries,especially the proposal of the Belt and Road Initiative,more and more foreign students come to China to study,putting forward higher requirements for t...With the deepening of exchanges between China and other countries,especially the proposal of the Belt and Road Initiative,more and more foreign students come to China to study,putting forward higher requirements for the education and management of colleges and universities in China.In the process of implementing the strategy of"one belt and one road",language interaction is the basic prerequisite for achieving exchanges and cooperation among different countries.In the face of this situation,by analyzing the existing problems in the training of overseas students in higher vocational colleges in China under the background of"One Belt and One Road"strategy,in this paper,the construction of the Chinese learning mode for overseas students in higher vocational colleges was put forward,hoping to provide help for the training of overseas students and solve the problem of foreign students'language learning.展开更多
This paper deals with the problem of iterative learning control for a class of linear continuous-time switched systems in the presence of a fixed initial shift. Here, the considered switched systems are operated durin...This paper deals with the problem of iterative learning control for a class of linear continuous-time switched systems in the presence of a fixed initial shift. Here, the considered switched systems are operated during a finite time interval repetitively. According to the characteristics of the systems, a PD-type learning scheme is proposed for such switched systems with arbitrary switching rules, and the corresponding output limiting trajectories under the action of the PD-type learning scheme are given. Based on the contraction mapping method, it is shown that this scheme can guarantee the outputs of the systems converge uniformly to the output limiting trajectories of the systems over the whole time interval. Furthermore, the initial rectifying strategies are applied to the systems for eliminating the effect of the fixed initial shift. When the learning scheme is applied to the systems, the outputs of the systems can converge to the desired reference trajectories over a pre-specified interval. Finally, simulation examples illustrate the effectiveness of the proposed method.展开更多
Selecting a proper initial input for Iterative Learning Control (ILC) algorithms has been shown to offer faster learning speed compared to the same theories if a system starts from blind. Iterative Learning Control is...Selecting a proper initial input for Iterative Learning Control (ILC) algorithms has been shown to offer faster learning speed compared to the same theories if a system starts from blind. Iterative Learning Control is a control technique that uses previous successive projections to update the following execution/trial input such that a reference is followed to a high precision. In ILC, convergence of the error is generally highly dependent on the initial choice of input applied to the plant, thus a good choice of initial start would make learning faster and as a consequence the error tends to zero faster as well. Here in this paper, an upper limit to the initial choice construction for the input signal for trial 1 is set such that the system would not tend to respond aggressively due to the uncertainty that lies in high frequencies. The provided limit is found in term of singular values and simulation results obtained illustrate the theory behind.展开更多
Although seemingly disparate,high-energy nuclear physics(HENP)and machine learning(ML)have begun to merge in the last few years,yielding interesting results.It is worthy to raise the profile of utilizing this novel mi...Although seemingly disparate,high-energy nuclear physics(HENP)and machine learning(ML)have begun to merge in the last few years,yielding interesting results.It is worthy to raise the profile of utilizing this novel mindset from ML in HENP,to help interested readers see the breadth of activities around this intersection.The aim of this mini-review is to inform the community of the current status and present an overview of the application of ML to HENP.From different aspects and using examples,we examine how scientific questions involving HENP can be answered using ML.展开更多
Considering the same initial state error in each repetitive operation in the iterative learning system, a method of arranging the transient process is given. During the current iteration, the system will track the tra...Considering the same initial state error in each repetitive operation in the iterative learning system, a method of arranging the transient process is given. During the current iteration, the system will track the transient function firstly, and then the expected trajectory. After several iterations, the learning system output will trend to the arranged curve, which has avoided the effect of the initial error on the controller. Also the transient time can be changed as you need, which makes the designing simple and the operation easy. Then the detailed designing steps are given via the robot system. At last the simulation of the robot system is given, which shows the validity of the method.展开更多
Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, ...Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, have been used to control this kind of system, but there are some deficiencie s in those methods: some need accurate and some need complicated operation and e tc. In recent years, in need of controlling the industrial robots, aiming at com pletely tracking the ideal input for the controlled subject with repetitive character, a new research area, ILC (iterative learning control), has been devel oped in the control technology and theory. The iterative learning control method can make the controlled subject operate as desired in a definite time span, merely making use of the prior control experie nce of the system and searching for the desired control signal according to the practical and desired output signal. The process of searching is equal to that o f learning, during which we only need to measure the output signal to amend the control signal, not like the adaptive control strategy, which on line assesses t he complex parameters of the system. Besides, since the iterative learning contr ol relies little on the prior message of the subject, it has been well used in a lot of areas, especially the dynamic systems with strong non-linear coupling a nd high repetitive position precision and the control system with batch producti on. Since robot manipulator has the above-mentioned character, ILC can be very well used in robot manipulator. In the ILC, since the operation always begins with a certain initial state, init ial condition has been required in almost all convergence verification. Therefor e, in designing the controller, the initial state has to be restricted with some condition to guarantee the convergence of the algorithm. The settle of initial condition problem has long been pursued in the ILC. There are commonly two kinds of initial condition problems: one is zero initial error problem, another is non-zero initial error problem. In practice, the repe titive operation will invariably produce excursion of the iterative initial stat e from the desired initial state. As a result, the research on the second in itial problem has more practical meaning. In this paper, for the non-zero initial error problem, one novel robust ILC alg orithms, respectively combining PD type iterative learning control algorithm wit h the robust feedback control algorithm, has been presented. This novel robust ILC algorithm contain two parts: feedforward ILC algorithm and robust feedback algorithm, which can be used to restrain disturbance from param eter variation, mechanical nonlinearities and unmodeled dynamics and to achieve good performance as well. The feedforward ILC algorithm can be used to improve the tracking error and perf ormance of the system through iteratively learning from the previous operation, thus performing the tracking task very fast. The robust feedback algorithm could mainly be applied to make the real output of the system not deviate too much fr om the desired tracking trajectory, and guarantee the system’s robustness w hen there are exterior noises and variations of the system parameter. In this paper, in order to analyze the convergence of the algorithm, Lyapunov st ability theory has been used through properly selecting the Lyapunov function. T he result of the verification shows the feasibility of the novel robust iterativ e learning control in theory. Finally, aiming at the two-freedom rate robot, simulation has been made with th e MATLAB software. Furthermore, two groups of parameters are selected to validat e the robustness of the algorithm.展开更多
To encourage learner to gain knowledge by individual learning outside classroom is concerned very much in modern English teaching.A study on the characteristics of individual English learning shows some new looks from...To encourage learner to gain knowledge by individual learning outside classroom is concerned very much in modern English teaching.A study on the characteristics of individual English learning shows some new looks from five aspects:self-consciousness,initiative,openness,research and process that involved in fostering learners learn language by themselves rather than learn language inside the classroom.展开更多
基金supported by the National Key Research and Development Program of China(2022YFD2300700)the Open Project Program of State Key Laboratory of Rice Biology,China National Rice Research Institute(20210403)the Zhejiang“Ten Thousand Talents”Plan Science and Technology Innovation Leading Talent Project,China(2020R52035)。
文摘Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.
文摘Sleep and well-being have been intricately linked,and sleep hygiene is paramount for developing mental well-being and resilience.Although widespread,sleep disorders require elaborate polysomnography laboratory and patient-stay with sleep in unfamiliar environments.Current technologies have allowed various devices to diagnose sleep disorders at home.However,these devices are in various validation stages,with many already receiving approvals from competent authorities.This has captured vast patient-related physiologic data for advanced analytics using artificial intelligence through machine and deep learning applications.This is expected to be integrated with patients’Electronic Health Records and provide individualized prescriptive therapy for sleep disorders in the future.
基金financially supported by the"13th Five-Year Plan"of Education Science in Jilin Province in 2017 as one of the research results of"Study of the initiative in English learning of the Xinjiang students assisted by other universities"(GHI 170652).
文摘The“counterpart aid to Xinjiang”is one of the important measures to implement the country’s western development strategy.It aims to shorten the gap between higher education in Xinjiang and the eastern region and to maintain the coordinated development of education,economy and society in the eastern and western regions.This article takes the counterpart support of Xinjiang students from the School of Foreign Languages of Jilin Engineering Normal University as an example to explore the problem of the initiative training of Xinjiang students in English learning in our school,mainly from the aspects of the students themselves,the teachers and the entire education and training environment of our school.The angle explains how to help them improve their learning initiative.This article is divided into three parts.The first is the analysis of the connotation of learning initiative;the second is its meaning;the last is how to build the learning initiative of Xinjiang students.
文摘With the deepening of exchanges between China and other countries,especially the proposal of the Belt and Road Initiative,more and more foreign students come to China to study,putting forward higher requirements for the education and management of colleges and universities in China.In the process of implementing the strategy of"one belt and one road",language interaction is the basic prerequisite for achieving exchanges and cooperation among different countries.In the face of this situation,by analyzing the existing problems in the training of overseas students in higher vocational colleges in China under the background of"One Belt and One Road"strategy,in this paper,the construction of the Chinese learning mode for overseas students in higher vocational colleges was put forward,hoping to provide help for the training of overseas students and solve the problem of foreign students'language learning.
基金The NSF(11371013)of Chinathe Research Innovation Program(SKCX17 032)for Graduate Students
文摘This paper deals with the problem of iterative learning control for a class of linear continuous-time switched systems in the presence of a fixed initial shift. Here, the considered switched systems are operated during a finite time interval repetitively. According to the characteristics of the systems, a PD-type learning scheme is proposed for such switched systems with arbitrary switching rules, and the corresponding output limiting trajectories under the action of the PD-type learning scheme are given. Based on the contraction mapping method, it is shown that this scheme can guarantee the outputs of the systems converge uniformly to the output limiting trajectories of the systems over the whole time interval. Furthermore, the initial rectifying strategies are applied to the systems for eliminating the effect of the fixed initial shift. When the learning scheme is applied to the systems, the outputs of the systems can converge to the desired reference trajectories over a pre-specified interval. Finally, simulation examples illustrate the effectiveness of the proposed method.
文摘Selecting a proper initial input for Iterative Learning Control (ILC) algorithms has been shown to offer faster learning speed compared to the same theories if a system starts from blind. Iterative Learning Control is a control technique that uses previous successive projections to update the following execution/trial input such that a reference is followed to a high precision. In ILC, convergence of the error is generally highly dependent on the initial choice of input applied to the plant, thus a good choice of initial start would make learning faster and as a consequence the error tends to zero faster as well. Here in this paper, an upper limit to the initial choice construction for the input signal for trial 1 is set such that the system would not tend to respond aggressively due to the uncertainty that lies in high frequencies. The provided limit is found in term of singular values and simulation results obtained illustrate the theory behind.
基金supported in part by the National Natural Science Foundation of China under contract Nos.11890714,12147101(Ma),12075098(Pang),12247107,12075007(Song)the Germany BMBF under the ErUM-Data project(Zhou)the Guangdong Major Project of Basic and Applied Basic Research No.2020B0301030008(Ma).
文摘Although seemingly disparate,high-energy nuclear physics(HENP)and machine learning(ML)have begun to merge in the last few years,yielding interesting results.It is worthy to raise the profile of utilizing this novel mindset from ML in HENP,to help interested readers see the breadth of activities around this intersection.The aim of this mini-review is to inform the community of the current status and present an overview of the application of ML to HENP.From different aspects and using examples,we examine how scientific questions involving HENP can be answered using ML.
文摘Considering the same initial state error in each repetitive operation in the iterative learning system, a method of arranging the transient process is given. During the current iteration, the system will track the transient function firstly, and then the expected trajectory. After several iterations, the learning system output will trend to the arranged curve, which has avoided the effect of the initial error on the controller. Also the transient time can be changed as you need, which makes the designing simple and the operation easy. Then the detailed designing steps are given via the robot system. At last the simulation of the robot system is given, which shows the validity of the method.
文摘Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, have been used to control this kind of system, but there are some deficiencie s in those methods: some need accurate and some need complicated operation and e tc. In recent years, in need of controlling the industrial robots, aiming at com pletely tracking the ideal input for the controlled subject with repetitive character, a new research area, ILC (iterative learning control), has been devel oped in the control technology and theory. The iterative learning control method can make the controlled subject operate as desired in a definite time span, merely making use of the prior control experie nce of the system and searching for the desired control signal according to the practical and desired output signal. The process of searching is equal to that o f learning, during which we only need to measure the output signal to amend the control signal, not like the adaptive control strategy, which on line assesses t he complex parameters of the system. Besides, since the iterative learning contr ol relies little on the prior message of the subject, it has been well used in a lot of areas, especially the dynamic systems with strong non-linear coupling a nd high repetitive position precision and the control system with batch producti on. Since robot manipulator has the above-mentioned character, ILC can be very well used in robot manipulator. In the ILC, since the operation always begins with a certain initial state, init ial condition has been required in almost all convergence verification. Therefor e, in designing the controller, the initial state has to be restricted with some condition to guarantee the convergence of the algorithm. The settle of initial condition problem has long been pursued in the ILC. There are commonly two kinds of initial condition problems: one is zero initial error problem, another is non-zero initial error problem. In practice, the repe titive operation will invariably produce excursion of the iterative initial stat e from the desired initial state. As a result, the research on the second in itial problem has more practical meaning. In this paper, for the non-zero initial error problem, one novel robust ILC alg orithms, respectively combining PD type iterative learning control algorithm wit h the robust feedback control algorithm, has been presented. This novel robust ILC algorithm contain two parts: feedforward ILC algorithm and robust feedback algorithm, which can be used to restrain disturbance from param eter variation, mechanical nonlinearities and unmodeled dynamics and to achieve good performance as well. The feedforward ILC algorithm can be used to improve the tracking error and perf ormance of the system through iteratively learning from the previous operation, thus performing the tracking task very fast. The robust feedback algorithm could mainly be applied to make the real output of the system not deviate too much fr om the desired tracking trajectory, and guarantee the system’s robustness w hen there are exterior noises and variations of the system parameter. In this paper, in order to analyze the convergence of the algorithm, Lyapunov st ability theory has been used through properly selecting the Lyapunov function. T he result of the verification shows the feasibility of the novel robust iterativ e learning control in theory. Finally, aiming at the two-freedom rate robot, simulation has been made with th e MATLAB software. Furthermore, two groups of parameters are selected to validat e the robustness of the algorithm.
基金a part of the project,"The Research of the New Type of College English Teaching Group"(No.Y-B/2011/04)supported by 2011"12.5"Program of Jiansu Education Science Research~~
文摘To encourage learner to gain knowledge by individual learning outside classroom is concerned very much in modern English teaching.A study on the characteristics of individual English learning shows some new looks from five aspects:self-consciousness,initiative,openness,research and process that involved in fostering learners learn language by themselves rather than learn language inside the classroom.
