Research on panicle detection is one of the most important aspects of paddy phenotypic analysis.A phenotyping method that uses unmanned aerial vehicles can be an excellent alternative to field-based methods.Neverthele...Research on panicle detection is one of the most important aspects of paddy phenotypic analysis.A phenotyping method that uses unmanned aerial vehicles can be an excellent alternative to field-based methods.Nevertheless,it entails many other challenges,including different illuminations,panicle sizes,shape distortions,partial occlusions,and complex backgrounds.Object detection algorithms are directly affected by these factors.This work proposes a model for detecting panicles called Border Sensitive Knowledge Distillation(BSKD).It is designed to prioritize the preservation of knowledge in border areas through the use of feature distillation.Our feature-based knowledge distillation method allows us to compress the model without sacrificing its effectiveness.An imitation mask is used to distinguish panicle-related foreground features from irrelevant background features.A significant improvement in Unmanned Aerial Vehicle(UAV)images is achieved when students imitate the teacher’s features.On the UAV rice imagery dataset,the proposed BSKD model shows superior performance with 76.3%mAP,88.3%precision,90.1%recall and 92.6%F1 score.展开更多
Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequenc...Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.展开更多
An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are mad...An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are made for the various large-scale problems of varying size. The comparison results between ASTNA and the subspace limited memory quasi-Newton algorithm and between the modified augmented Lagrange multiplier methods combined with ASTNA and the modified barrier function method show the stability and effectiveness of ASTNA for simultaneous optimization of distillation column.展开更多
Bismuth-doped tin dioxide （BTO） nanometer powders were prepared by the wet chemical method using tin tetrachloride （SnCl4）, bismuth nitrate [Bi（NO3） 3 ] and ammonia as raw materials. Non-bridge hydroxides and ca...Bismuth-doped tin dioxide （BTO） nanometer powders were prepared by the wet chemical method using tin tetrachloride （SnCl4）, bismuth nitrate [Bi（NO3） 3 ] and ammonia as raw materials. Non-bridge hydroxides and capillary force between particles were found to be key factors causing hard aggregation of BTO through analyzing the formation mechanism of hard aggregation. The hard aggregation of BTO was eliminated effectively when the Bi-Sn precursor （BSP） was treated with post processing including dispersing with ultrasonic wave, refluxing and distilling with addition of n-butanol and benzene （DRD） and drying by microwave. Characterized with X-ray diffraction （XRD） and transmission electron microscopy （TEM）, BTO spherical particles with tetragonal phase structure are well crystallized, dispersed easily and the average size was less than 10 nm.展开更多
In this paper,a generalized model of the reactive distillation processes was developed via rate-based approach. The homotopy-continuation method was employed to solve the complicated nonlinear model equations efficien...In this paper,a generalized model of the reactive distillation processes was developed via rate-based approach. The homotopy-continuation method was employed to solve the complicated nonlinear model equations efficiently. The simulation on the reactive distillation processes was carried out with the profiles of stage temperature,composition and flow rate for both vapor and liquid phases obtained. Based on careful analysis of the simulation results, the pitfalls in experimental design were detected. Finally, a software package for the simulation of reactive distillation processes was developed.展开更多
Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data predic...Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data prediction systems represented by machine learning,it has become possible for real-time prediction systems of petroleum fraction molecular information to replace analyses such as gas chromatography and mass spectrometry.However,the biggest difficulty lies in acquiring the data required for training the neural network.To address these issues,this work proposes an innovative method that utilizes the Aspen HYSYS and full two-dimensional gas chromatography-time-of-flight mass spectrometry to establish a comprehensive training database.Subsequently,a deep neural network prediction model is developed for heavy distillate oil to predict its composition in terms of molecular structure.After training,the model accurately predicts the molecular composition of catalytically cracked raw oil in a refinery.The validation and test sets exhibit R2 values of 0.99769 and 0.99807,respectively,and the average relative error of molecular composition prediction for raw materials of the catalytic cracking unit is less than 7%.Finally,the SHAP(SHapley Additive ExPlanation)interpretation method is used to disclose the relationship among different variables by performing global and local weight comparisons and correlation analyses.展开更多
文摘Research on panicle detection is one of the most important aspects of paddy phenotypic analysis.A phenotyping method that uses unmanned aerial vehicles can be an excellent alternative to field-based methods.Nevertheless,it entails many other challenges,including different illuminations,panicle sizes,shape distortions,partial occlusions,and complex backgrounds.Object detection algorithms are directly affected by these factors.This work proposes a model for detecting panicles called Border Sensitive Knowledge Distillation(BSKD).It is designed to prioritize the preservation of knowledge in border areas through the use of feature distillation.Our feature-based knowledge distillation method allows us to compress the model without sacrificing its effectiveness.An imitation mask is used to distinguish panicle-related foreground features from irrelevant background features.A significant improvement in Unmanned Aerial Vehicle(UAV)images is achieved when students imitate the teacher’s features.On the UAV rice imagery dataset,the proposed BSKD model shows superior performance with 76.3%mAP,88.3%precision,90.1%recall and 92.6%F1 score.
文摘Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.
基金Project (2002CB312200) supported by the National Key Basic Research and Development Program of China Project(03JJY3109) supported by the Natural Science Foundation of Hunan Province
文摘An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are made for the various large-scale problems of varying size. The comparison results between ASTNA and the subspace limited memory quasi-Newton algorithm and between the modified augmented Lagrange multiplier methods combined with ASTNA and the modified barrier function method show the stability and effectiveness of ASTNA for simultaneous optimization of distillation column.
文摘Bismuth-doped tin dioxide （BTO） nanometer powders were prepared by the wet chemical method using tin tetrachloride （SnCl4）, bismuth nitrate [Bi（NO3） 3 ] and ammonia as raw materials. Non-bridge hydroxides and capillary force between particles were found to be key factors causing hard aggregation of BTO through analyzing the formation mechanism of hard aggregation. The hard aggregation of BTO was eliminated effectively when the Bi-Sn precursor （BSP） was treated with post processing including dispersing with ultrasonic wave, refluxing and distilling with addition of n-butanol and benzene （DRD） and drying by microwave. Characterized with X-ray diffraction （XRD） and transmission electron microscopy （TEM）, BTO spherical particles with tetragonal phase structure are well crystallized, dispersed easily and the average size was less than 10 nm.
基金Supported by the State Key Project of the National Natural Science Foundation of China (No.2929054)
文摘In this paper,a generalized model of the reactive distillation processes was developed via rate-based approach. The homotopy-continuation method was employed to solve the complicated nonlinear model equations efficiently. The simulation on the reactive distillation processes was carried out with the profiles of stage temperature,composition and flow rate for both vapor and liquid phases obtained. Based on careful analysis of the simulation results, the pitfalls in experimental design were detected. Finally, a software package for the simulation of reactive distillation processes was developed.
基金the National Natural Science Foundation of China(22108307)the Natural Science Foundation of Shandong Province(ZR2020KB006)the Outstanding Youth Fund of Shandong Provincial Natural Science Foundation(ZR2020YQ17).
文摘Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data prediction systems represented by machine learning,it has become possible for real-time prediction systems of petroleum fraction molecular information to replace analyses such as gas chromatography and mass spectrometry.However,the biggest difficulty lies in acquiring the data required for training the neural network.To address these issues,this work proposes an innovative method that utilizes the Aspen HYSYS and full two-dimensional gas chromatography-time-of-flight mass spectrometry to establish a comprehensive training database.Subsequently,a deep neural network prediction model is developed for heavy distillate oil to predict its composition in terms of molecular structure.After training,the model accurately predicts the molecular composition of catalytically cracked raw oil in a refinery.The validation and test sets exhibit R2 values of 0.99769 and 0.99807,respectively,and the average relative error of molecular composition prediction for raw materials of the catalytic cracking unit is less than 7%.Finally,the SHAP(SHapley Additive ExPlanation)interpretation method is used to disclose the relationship among different variables by performing global and local weight comparisons and correlation analyses.
