For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to p...For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.展开更多
There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because the...There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.展开更多
The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick resp...The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.展开更多
A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,a...A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.展开更多
The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key ...The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.展开更多
[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-base...[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.展开更多
Recent advancements have led to the synthesis of various new metal-containing explosives,particularly energetic metal-organic frameworks(EMOFs),which feature high-energy ligands within well-ordered crystalline structu...Recent advancements have led to the synthesis of various new metal-containing explosives,particularly energetic metal-organic frameworks(EMOFs),which feature high-energy ligands within well-ordered crystalline structures.These explosives exhibit significant advantages over traditional compounds,including higher density,greater heats of detonation,improved mechanical hardness,and excellent thermal stability.To effectively evaluate their detonation performance,it is crucial to have a reliable method for predicting detonation heat,velocity,and pressure.This study leverages experimental data and outputs from the leading commercial computer code to identify suitable decomposition pathways for different metal oxides,facilitating straightforward calculations for the detonation performance of alkali metal salts,and metal coordination compounds,along with EMOFs.The new model enhances predictive reliability for detonation velocities,aligning more closely with experimental results,as evi-denced by a root mean square error(RMSE)of 0.68 km/s compared to 1.12 km/s for existing methods.Furthermore,it accommodates a broader range of compounds,including those containing Sr,Cd,and Ag,and provides predictions for EMOFs that are more consistent with computer code outputs than previous predictive models.展开更多
The biology safety of genetically modified organisms （GMO） has been a topic of considerable public debate in recent years. Parts of the international research on the safety of GMO focus on its effect on soil ecosyst...The biology safety of genetically modified organisms （GMO） has been a topic of considerable public debate in recent years. Parts of the international research on the safety of GMO focus on its effect on soil ecosystem, especially on microbial communities changing and process in soil that are essential to key terrestrial ecosystem functions. This paper studied the dynamic change of soil microbe after cultivating Roundup Ready soybean （RRS） and the effect on biochemical processing of nitrogen cycle. According to the variance analysis, the ammonifying bacteria and nitrifying bacteria quantities of RRS in the rhizosphere soil were much lower than that of other genotype soybeans. The effects of different genotype soybeans on ammoniation intensity and nitrification intensity were remarkable. The nitrification intensity and the nitrifying bacteria had the great positive correlation and sustainable development.展开更多
Established system equivalences for transition systems, such as trace equivalence and failures equivalence, require the ob- servations to be exactly identical. However, an accurate measure- ment is impossible when int...Established system equivalences for transition systems, such as trace equivalence and failures equivalence, require the ob- servations to be exactly identical. However, an accurate measure- ment is impossible when interacting with the physical world, hence exact equivalence is restrictive and not robust. Using Baire met- ric, a generalized framework of transition system approximation is proposed by developing the notions of approximate language equivalence and approximate singleton failures （SF） equivalence. The framework takes the traditional exact equivalence as a special case. The approximate language equivalence is coarser than the approximate Slc equivalence, just like the hierarchy of the exact ones. The main conclusion is that the two approximate equiva- lences satisfy the transitive property, consequently, they can be successively used in transition system approximation.展开更多
As a main oxidizer in solid composite propellants,ammonium perchlorate(AP)plays an important role because its thermal decomposition behavior has a direct influence on the characteristic of solid composite propellants....As a main oxidizer in solid composite propellants,ammonium perchlorate(AP)plays an important role because its thermal decomposition behavior has a direct influence on the characteristic of solid composite propellants.To improve the performance of solid composite propellant,it is necessary to take measures to modify the thermal decomposition behavior of AP.In recent years,transition metal oxides and carbon-supported transition metal oxides have drawn considerable attention due to their extraordinary catalytic activity.In this review,we highlight strategies to enhance the thermal decomposition of AP by tuning morphology,varying the types of metal ion,and coupling with carbon analogue.The enhanced catalytic performance can be ascribed to synergistic effect,increased surface area,more exposed active sites,and accelerated electron transportation and so on.The mechanism of AP decomposition mixed with catalyst has also been briefly summarized.Finally,a conclusive outlook and possible research directions are suggested to address challenges such as lacking practical application in actual formulation of solid composite propellant and batch manufacturing.展开更多
A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism （IGAE）. In IGAE, the new methods for computing antibody s...A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism （IGAE）. In IGAE, the new methods for computing antibody similarity, expected reproduction probability, and clonal selection probability were given. IGAE has three features. The first is that the similarities of two antibodies in structure and quality are all defined in the form of percentage, which helps to describe the similarity of two antibodies more accurately and to reduce the computational burden effectively. The second is that with the elitist selection and elitist crossover strategy IGAE is able to find the globally optimal solution of a given problem. The third is that the formula of expected reproduction probability of antibody can be adjusted through a parameter r, which helps to balance the population diversity and the convergence speed of IGAE so that IGAE can find the globally optimal solution of a given problem more rapidly. Two different complex multi-modal functions were selected to test the validity of IGAE. The experimental results show that IGAE can find the globally maximum/minimum values of the two functions rapidly. The experimental results also confirm that IGAE is of better performance in convergence speed, solution variation behavior, and computational efficiency compared with the canonical genetic algorithm with the elitism and the immune genetic algorithm with the information entropy and elitism.展开更多
The method of Zeng et al. (1991) employed diameter growth to estimate the transition probability of the matrix model in uneven-aged forest stands. In this paper the Weibull distribution for even-aged forest stands ins...The method of Zeng et al. (1991) employed diameter growth to estimate the transition probability of the matrix model in uneven-aged forest stands. In this paper the Weibull distribution for even-aged forest stands instead of uniform distribution chosen by Zeng is used. By comparing the results of the improved method with those of the original method of Zeng, it turns out that the improved method of Zeng given in this paper is more efficient.展开更多
The novel method to analyze metallic structure corrosion status was proposed in the presence of stray current in DC mass transit systems. Firstly, the characteristic parameter and the influence parameters for the corr...The novel method to analyze metallic structure corrosion status was proposed in the presence of stray current in DC mass transit systems. Firstly, the characteristic parameter and the influence parameters for the corrosion status were determined. Secondly, an experimental system was established for simulating the corrosion process within the stray current interference. Then, a predictive model for the corrosion status was built, using a support vector machine(SVM) method and experimental data. The data were divided into two sets, including training set and testing set. The training set was used to generate the SVM model and the testing set was used to evaluate the predictive performance of the SVM model. The results show that the relationship between the characteristic parameter and the influence parameters is nonlinear and the SVM model is suitable for predicting the corrosion status.展开更多
基金supported by the National Natural Science Foundation of China(61371172)the International S&T Cooperation Program of China(2015DFR10220)+1 种基金the Ocean Engineering Project of National Key Laboratory Foundation(1213)the Fundamental Research Funds for the Central Universities(HEUCF1608)
文摘For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.
基金Project(61374140)supported by the National Natural Science Foundation of China
文摘There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.
基金Project(LQ12E05008)supported by Natural Science Foundation of Zhejiang Province,ChinaProject(201708330107)supported by China Scholarship Council
文摘The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
基金Supported by the Fundamental Research Funds for the Central Universities(ZYGX2021J008)。
文摘A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.
基金Project(2018XK2301) supported by the Change-Zhu-Tan National Independent Innavation Demonstration Zone Special Program,China。
文摘The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.
文摘[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.
基金the research committee at Malek Ashtar University of Technology (MUT) for their invaluable support of this project
文摘Recent advancements have led to the synthesis of various new metal-containing explosives,particularly energetic metal-organic frameworks(EMOFs),which feature high-energy ligands within well-ordered crystalline structures.These explosives exhibit significant advantages over traditional compounds,including higher density,greater heats of detonation,improved mechanical hardness,and excellent thermal stability.To effectively evaluate their detonation performance,it is crucial to have a reliable method for predicting detonation heat,velocity,and pressure.This study leverages experimental data and outputs from the leading commercial computer code to identify suitable decomposition pathways for different metal oxides,facilitating straightforward calculations for the detonation performance of alkali metal salts,and metal coordination compounds,along with EMOFs.The new model enhances predictive reliability for detonation velocities,aligning more closely with experimental results,as evi-denced by a root mean square error(RMSE)of 0.68 km/s compared to 1.12 km/s for existing methods.Furthermore,it accommodates a broader range of compounds,including those containing Sr,Cd,and Ag,and provides predictions for EMOFs that are more consistent with computer code outputs than previous predictive models.
基金Supported by Natural Science Foundation of Heilongjiang Province(04-0402:ZJN)
文摘The biology safety of genetically modified organisms （GMO） has been a topic of considerable public debate in recent years. Parts of the international research on the safety of GMO focus on its effect on soil ecosystem, especially on microbial communities changing and process in soil that are essential to key terrestrial ecosystem functions. This paper studied the dynamic change of soil microbe after cultivating Roundup Ready soybean （RRS） and the effect on biochemical processing of nitrogen cycle. According to the variance analysis, the ammonifying bacteria and nitrifying bacteria quantities of RRS in the rhizosphere soil were much lower than that of other genotype soybeans. The effects of different genotype soybeans on ammoniation intensity and nitrification intensity were remarkable. The nitrification intensity and the nitrifying bacteria had the great positive correlation and sustainable development.
基金supported by the National Natural Science Foundation of China(1137100311461006)+4 种基金the Natural Science Foundation of Guangxi(2011GXNSFA0181542012GXNSFGA060003)the Science and Technology Foundation of Guangxi(10169-1)the Scientific Research Project from Guangxi Education Department(201012MS274)Open Research Fund Program of Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis(HCIC201301)
文摘Established system equivalences for transition systems, such as trace equivalence and failures equivalence, require the ob- servations to be exactly identical. However, an accurate measure- ment is impossible when interacting with the physical world, hence exact equivalence is restrictive and not robust. Using Baire met- ric, a generalized framework of transition system approximation is proposed by developing the notions of approximate language equivalence and approximate singleton failures （SF） equivalence. The framework takes the traditional exact equivalence as a special case. The approximate language equivalence is coarser than the approximate Slc equivalence, just like the hierarchy of the exact ones. The main conclusion is that the two approximate equiva- lences satisfy the transitive property, consequently, they can be successively used in transition system approximation.
基金This work was financially supported by the Science and Technology project of Jiangsu province(BN2015021,XZ-SZ201819).
文摘As a main oxidizer in solid composite propellants,ammonium perchlorate(AP)plays an important role because its thermal decomposition behavior has a direct influence on the characteristic of solid composite propellants.To improve the performance of solid composite propellant,it is necessary to take measures to modify the thermal decomposition behavior of AP.In recent years,transition metal oxides and carbon-supported transition metal oxides have drawn considerable attention due to their extraordinary catalytic activity.In this review,we highlight strategies to enhance the thermal decomposition of AP by tuning morphology,varying the types of metal ion,and coupling with carbon analogue.The enhanced catalytic performance can be ascribed to synergistic effect,increased surface area,more exposed active sites,and accelerated electron transportation and so on.The mechanism of AP decomposition mixed with catalyst has also been briefly summarized.Finally,a conclusive outlook and possible research directions are suggested to address challenges such as lacking practical application in actual formulation of solid composite propellant and batch manufacturing.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProjects(20040533035, 20070533131) supported by the National Research Foundation for the Doctoral Program of Higher Education of China
文摘A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism （IGAE）. In IGAE, the new methods for computing antibody similarity, expected reproduction probability, and clonal selection probability were given. IGAE has three features. The first is that the similarities of two antibodies in structure and quality are all defined in the form of percentage, which helps to describe the similarity of two antibodies more accurately and to reduce the computational burden effectively. The second is that with the elitist selection and elitist crossover strategy IGAE is able to find the globally optimal solution of a given problem. The third is that the formula of expected reproduction probability of antibody can be adjusted through a parameter r, which helps to balance the population diversity and the convergence speed of IGAE so that IGAE can find the globally optimal solution of a given problem more rapidly. Two different complex multi-modal functions were selected to test the validity of IGAE. The experimental results show that IGAE can find the globally maximum/minimum values of the two functions rapidly. The experimental results also confirm that IGAE is of better performance in convergence speed, solution variation behavior, and computational efficiency compared with the canonical genetic algorithm with the elitism and the immune genetic algorithm with the information entropy and elitism.
基金This paper was supported by the National Natural Science Foundation of China
文摘The method of Zeng et al. (1991) employed diameter growth to estimate the transition probability of the matrix model in uneven-aged forest stands. In this paper the Weibull distribution for even-aged forest stands instead of uniform distribution chosen by Zeng is used. By comparing the results of the improved method with those of the original method of Zeng, it turns out that the improved method of Zeng given in this paper is more efficient.
基金Project(BE2010043) supported by the Technology Support Program of Jiangsu Province,ChinaProject(CXZZ13_0928) supported by the Graduate Education Innovation Project of Jiangsu Province,China
文摘The novel method to analyze metallic structure corrosion status was proposed in the presence of stray current in DC mass transit systems. Firstly, the characteristic parameter and the influence parameters for the corrosion status were determined. Secondly, an experimental system was established for simulating the corrosion process within the stray current interference. Then, a predictive model for the corrosion status was built, using a support vector machine(SVM) method and experimental data. The data were divided into two sets, including training set and testing set. The training set was used to generate the SVM model and the testing set was used to evaluate the predictive performance of the SVM model. The results show that the relationship between the characteristic parameter and the influence parameters is nonlinear and the SVM model is suitable for predicting the corrosion status.
