Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,maki...Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.展开更多
Semiconductor optical amplifiers (SOA) are optical amplifying devices and key parts in optical switches and optical buffers.They are largely used in communication system.Linewidth enhancement factor is an important pa...Semiconductor optical amplifiers (SOA) are optical amplifying devices and key parts in optical switches and optical buffers.They are largely used in communication system.Linewidth enhancement factor is an important parameter for SOA.A method is proposed to measure the linewidth enhancement factor with Sagnac interferometer.Cross phase modulation (XPM) and cross gain modulation (XGM) coexist in SOA.The quantitative relation of linewidth enhancement factor to XGM and the interference extinction ratio is given.The experimental results indicate that the value of linewidth enhancement factor changes from 5.13 to 6.24 when the electric current varies from 130 mA to 240 mA.展开更多
The ring-polymer molecular dynamics(RPMD)was used to calculate the thermal rate coefficients of the multi-channel roaming reaction H+MgH→Mg+H_(2).Two reaction channels,tight and roaming,are explicitly considered.This...The ring-polymer molecular dynamics(RPMD)was used to calculate the thermal rate coefficients of the multi-channel roaming reaction H+MgH→Mg+H_(2).Two reaction channels,tight and roaming,are explicitly considered.This is a pioneering attempt of exerting RPMD method to multichannel reactions.With the help of a newly developed optimization-interpolation protocol for preparing the initial structures and adaptive protocol for choosing the force constants,we have successfully obtained the thermal rate coefficients.The results are consistent with those from other theoretical methods,such as variational transition state theory and quantum dynamics.Especially,RPMD results exhibit negative temperature dependence,which is similar to the results from variational transition state theory but different from the ones from ground state quantum dynamics calculations.展开更多
Intelligent seismic facies identification based on deep learning can alleviate the time-consuming and labor-intensive problem of manual interpretation,which has been widely applied.Supervised learning can realize faci...Intelligent seismic facies identification based on deep learning can alleviate the time-consuming and labor-intensive problem of manual interpretation,which has been widely applied.Supervised learning can realize facies identification with high efficiency and accuracy;however,it depends on the usage of a large amount of well-labeled data.To solve this issue,we propose herein an incremental semi-supervised method for intelligent facies identification.Our method considers the continuity of the lateral variation of strata and uses cosine similarity to quantify the similarity of the seismic data feature domain.The maximum-diff erence sample in the neighborhood of the currently used training data is then found to reasonably expand the training sets.This process continuously increases the amount of training data and learns its distribution.We integrate old knowledge while absorbing new ones to realize incremental semi-supervised learning and achieve the purpose of evolving the network models.In this work,accuracy and confusion matrix are employed to jointly control the predicted results of the model from both overall and partial aspects.The obtained values are then applied to a three-dimensional(3D)real dataset and used to quantitatively evaluate the results.Using unlabeled data,our proposed method acquires more accurate and stable testing results compared to conventional supervised learning algorithms that only use well-labeled data.A considerable improvement for small-sample categories is also observed.Using less than 1%of the training data,the proposed method can achieve an average accuracy of over 95%on the 3D dataset.In contrast,the conventional supervised learning algorithm achieved only approximately 85%.展开更多
The optical noninvasive diagnostic of characteristic of silicon semiconductor devices by using a InGaAsP/InP semiconductor laser as an optical probe is reported. The principle of experimental method is based on the de...The optical noninvasive diagnostic of characteristic of silicon semiconductor devices by using a InGaAsP/InP semiconductor laser as an optical probe is reported. The principle of experimental method is based on the dependence of the optical refractive index on the carrier charge density in the active region of devices and detection of variation of refractive index by two laser beam interferometric techniques.展开更多
Multi-label data with high dimensionality often occurs,which will produce large time and energy overheads when directly used in classification tasks.To solve this problem,a novel algorithm called multi-label dimension...Multi-label data with high dimensionality often occurs,which will produce large time and energy overheads when directly used in classification tasks.To solve this problem,a novel algorithm called multi-label dimensionality reduction via semi-supervised discriminant analysis(MSDA) was proposed.It was expected to derive an objective discriminant function as smooth as possible on the data manifold by multi-label learning and semi-supervised learning.By virtue of the latent imformation,which was provided by the graph weighted matrix of sample attributes and the similarity correlation matrix of partial sample labels,MSDA readily made the separability between different classes achieve maximization and estimated the intrinsic geometric structure in the lower manifold space by employing unlabeled data.Extensive experimental results on several real multi-label datasets show that after dimensionality reduction using MSDA,the average classification accuracy is about 9.71% higher than that of other algorithms,and several evaluation metrices like Hamming-loss are also superior to those of other dimensionality reduction methods.展开更多
Background Patient autonomy is a leading principle in bioethics and a basis for shared decision making. This study explores conditions for an autonomous choice experienced by older adults who recently underwent trans-...Background Patient autonomy is a leading principle in bioethics and a basis for shared decision making. This study explores conditions for an autonomous choice experienced by older adults who recently underwent trans-catheter aortic valve replacement （TAVR）. Methods Qualitative study entailing semi-structured interviews of a purposive sample often older （range 73-89, median 83.5 years） adults after TAVR （median 23 days）. The study setting was a cardiac department at a university hospital performing TAVR since 2010. Analysis was by systematic text condensation. Results Even when choice seemed hard or absent, TAVR-patients deliberately took the chance offered them by processing risk assessment, ambivalence and fate. They regarded declining the treatment to be worse than accepting the risk related to the procedure. The experience of being thoroughly advised by their physician formed the basis of an autonomous trust. The trust they felt for the physicians＇ recommendations mitigated ambivalence about the procedure and risks. TAVR patients expressed feelings consistent with self-empowerment and claimed that it had to be their decision. Even so, choosing the intervention as an obligation to their family or passively accepting it was also reported. Conclusions Older TAVR patients＇ experience of an autonomous decision may encompass frank tradeoff; deliberate physician dependency as well as a resilient self-view. Physicians should be especially aware of how older adults＇ subtle cognitive declines and inclinations to preserve their identities which can influence their medical decision making when obtaining in- formed consent. Cardiologists and other providers may also use these insights to develop new strategies that better respond to such inherent complexities.展开更多
This article is based on research on pre-service teachers＇ perspectives on their mathematics knowledge of proof in geometry. The study was framed using tile mathematical knowledge for teaching framework. This qualita...This article is based on research on pre-service teachers＇ perspectives on their mathematics knowledge of proof in geometry. The study was framed using tile mathematical knowledge for teaching framework. This qualitative study employed the use of a task-based worksheet, focus group sessions and semi-structured individual interviews. The task-based worksheet was completed by 180 pre-service mathematics teachers （second, third and fourth year mathematics education students）. Pre-service mathematics teachers are student teachers who have not yet completed their training to become teachers. After the analysis of the task-based worksheet, 20 participants were invited to participate in focus group sessions and individual interviews. The findings of the study reveal that the participants possess peripheral mathematics knowledge of proof in geometry. The study aims at assisting pre-service teachers and interested educationists to explore innovative methods of acquiring and imparting mathematics knowledge of proof in geometry. The study proposes possible changes in curriculum at school and university level.展开更多
The purpose of this article is to investigate visual literacy from the perspective of the VTS （Visual Thinking Strategies） method. The authors examine the viewpoints of seven American elementary school teachers on v...The purpose of this article is to investigate visual literacy from the perspective of the VTS （Visual Thinking Strategies） method. The authors examine the viewpoints of seven American elementary school teachers on visual literacy and its meanings in the context of the VTS method. Data collection was done using a semi-structured questionnaire, which was followed by theory-driven content analysis. The authors emphasize that when supporting holistic development in a teaching context, it is the interconnected nature of aesthetics, growth and the learner＇s learning which is more important than developing special skills, like visual literacy. In the teaching context visual literacy and language development should be acknowledged in pedagogy and research.展开更多
By making use of the direct integration method,an exact analysis of the general three-dimensional thermoelasticity problem is performed for the case of a transversely isotropic homogeneous half-space subject to local ...By making use of the direct integration method,an exact analysis of the general three-dimensional thermoelasticity problem is performed for the case of a transversely isotropic homogeneous half-space subject to local thermal and force loadings.The material plane of isotropy is assumed to be parallel to the limiting surface of the halfspace.By reducing the original thermoelasticity equations to the governing ones for individual stress-tensor components,the effect of material anisotropy in the stress field is analyzed with regard to the feasibility requirement,i.e.,the finiteness of the stress field at a distance from the disturbed area.As a result,the solution is constructed in the form of explicit analytical dependencies on the force and thermal loadings for various kinds of transversely isotropic materials and agrees with the basic principles of the continua mechanics.The solution can be efficiently used as a benchmark one for the direct computation of temperature and thermal stresses in transversely isotropic semi-infinite domains,as well as for the verification of solutions constructed by different means.展开更多
The progressive stacking of chalcogenide single layers gives rise to two- dimensional semiconducting materials with tunable properties that can be exploited for new field-effect transistors and photonic devices. Yet t...The progressive stacking of chalcogenide single layers gives rise to two- dimensional semiconducting materials with tunable properties that can be exploited for new field-effect transistors and photonic devices. Yet the properties of some members of the chalcogenide family remain unexplored. Indium selenide （InSe） is attractive for applications due to its direct bandgap in the near infrared, controllable p- and n-type doping and high chemical stability. Here, we reveal the lattice dynamics, optical and electronic properties of atomically thin InSe flakes prepared by micromechanical cleavage. Raman active modes stiffen or soften in the flakes depending on which electronic bonds are excited. A progressive blue-shift of the photoluminescence peaks is observed for decreasing flake thickness （as large as 0.2 eV for three single layers）. First-principles calculations predict an even larger increase in the bandgap, 0.40 eV, for three single layers, and as much as 1.1 eV for a single layer. These results are promising from the point of view of the versatility of this material for optoelectronic applications at the nanometer scale and compatible with Si and III-V technologies.展开更多
Semi-supervised learning is an emerging computational paradigm for machine learning,that aims to make better use of large amounts of inexpensive unlabeled data to improve the learning performance.While various methods...Semi-supervised learning is an emerging computational paradigm for machine learning,that aims to make better use of large amounts of inexpensive unlabeled data to improve the learning performance.While various methods have been proposed based on different intuitions,the crucial issue of generalization performance is still poorly understood.In this paper,we investigate the convergence property of the Laplacian regularized least squares regression,a semi-supervised learning algorithm based on manifold regularization.Moreover,the improvement of error bounds in terms of the number of labeled and unlabeled data is presented for the first time as far as we know.The convergence rate depends on the approximation property and the capacity of the reproducing kernel Hilbert space measured by covering numbers.Some new techniques are exploited for the analysis since an extra regularizer is introduced.展开更多
基金National Key Research and Development Program of China(Nos.2022YFB4700600 and 2022YFB4700605)National Natural Science Foundation of China(Nos.61771123 and 62171116)+1 种基金Fundamental Research Funds for the Central UniversitiesGraduate Student Innovation Fund of Donghua University,China(No.CUSF-DH-D-2022044)。
文摘Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.
文摘Semiconductor optical amplifiers (SOA) are optical amplifying devices and key parts in optical switches and optical buffers.They are largely used in communication system.Linewidth enhancement factor is an important parameter for SOA.A method is proposed to measure the linewidth enhancement factor with Sagnac interferometer.Cross phase modulation (XPM) and cross gain modulation (XGM) coexist in SOA.The quantitative relation of linewidth enhancement factor to XGM and the interference extinction ratio is given.The experimental results indicate that the value of linewidth enhancement factor changes from 5.13 to 6.24 when the electric current varies from 130 mA to 240 mA.
基金supported by the National Natural Science Foundation of China(No.21503130 and No.11674212,and No.21603144)supported by the Young Eastern Scholar Program of the Shanghai Municipal Education Commission(QD2016021)+1 种基金the Shanghai Key Laboratory of High Temperature Superconductors(No.14DZ2260700)supported by Shanghai Sailing Program(No.2016YF1408400).
文摘The ring-polymer molecular dynamics(RPMD)was used to calculate the thermal rate coefficients of the multi-channel roaming reaction H+MgH→Mg+H_(2).Two reaction channels,tight and roaming,are explicitly considered.This is a pioneering attempt of exerting RPMD method to multichannel reactions.With the help of a newly developed optimization-interpolation protocol for preparing the initial structures and adaptive protocol for choosing the force constants,we have successfully obtained the thermal rate coefficients.The results are consistent with those from other theoretical methods,such as variational transition state theory and quantum dynamics.Especially,RPMD results exhibit negative temperature dependence,which is similar to the results from variational transition state theory but different from the ones from ground state quantum dynamics calculations.
基金financially supported by the National Key R&D Program of China(No.2018YFA0702504)the National Natural Science Foundation of China(No.42174152 and No.41974140)+1 种基金the Science Foundation of China University of Petroleum,Beijing(No.2462020YXZZ008 and No.2462020QZDX003)the Strategic Cooperation Technology Projects of CNPC and CUPB(No.ZLZX2020-03).
文摘Intelligent seismic facies identification based on deep learning can alleviate the time-consuming and labor-intensive problem of manual interpretation,which has been widely applied.Supervised learning can realize facies identification with high efficiency and accuracy;however,it depends on the usage of a large amount of well-labeled data.To solve this issue,we propose herein an incremental semi-supervised method for intelligent facies identification.Our method considers the continuity of the lateral variation of strata and uses cosine similarity to quantify the similarity of the seismic data feature domain.The maximum-diff erence sample in the neighborhood of the currently used training data is then found to reasonably expand the training sets.This process continuously increases the amount of training data and learns its distribution.We integrate old knowledge while absorbing new ones to realize incremental semi-supervised learning and achieve the purpose of evolving the network models.In this work,accuracy and confusion matrix are employed to jointly control the predicted results of the model from both overall and partial aspects.The obtained values are then applied to a three-dimensional(3D)real dataset and used to quantitatively evaluate the results.Using unlabeled data,our proposed method acquires more accurate and stable testing results compared to conventional supervised learning algorithms that only use well-labeled data.A considerable improvement for small-sample categories is also observed.Using less than 1%of the training data,the proposed method can achieve an average accuracy of over 95%on the 3D dataset.In contrast,the conventional supervised learning algorithm achieved only approximately 85%.
文摘The optical noninvasive diagnostic of characteristic of silicon semiconductor devices by using a InGaAsP/InP semiconductor laser as an optical probe is reported. The principle of experimental method is based on the dependence of the optical refractive index on the carrier charge density in the active region of devices and detection of variation of refractive index by two laser beam interferometric techniques.
基金Project(60425310) supported by the National Science Fund for Distinguished Young ScholarsProject(10JJ6094) supported by the Hunan Provincial Natural Foundation of China
文摘Multi-label data with high dimensionality often occurs,which will produce large time and energy overheads when directly used in classification tasks.To solve this problem,a novel algorithm called multi-label dimensionality reduction via semi-supervised discriminant analysis(MSDA) was proposed.It was expected to derive an objective discriminant function as smooth as possible on the data manifold by multi-label learning and semi-supervised learning.By virtue of the latent imformation,which was provided by the graph weighted matrix of sample attributes and the similarity correlation matrix of partial sample labels,MSDA readily made the separability between different classes achieve maximization and estimated the intrinsic geometric structure in the lower manifold space by employing unlabeled data.Extensive experimental results on several real multi-label datasets show that after dimensionality reduction using MSDA,the average classification accuracy is about 9.71% higher than that of other algorithms,and several evaluation metrices like Hamming-loss are also superior to those of other dimensionality reduction methods.
文摘Background Patient autonomy is a leading principle in bioethics and a basis for shared decision making. This study explores conditions for an autonomous choice experienced by older adults who recently underwent trans-catheter aortic valve replacement （TAVR）. Methods Qualitative study entailing semi-structured interviews of a purposive sample often older （range 73-89, median 83.5 years） adults after TAVR （median 23 days）. The study setting was a cardiac department at a university hospital performing TAVR since 2010. Analysis was by systematic text condensation. Results Even when choice seemed hard or absent, TAVR-patients deliberately took the chance offered them by processing risk assessment, ambivalence and fate. They regarded declining the treatment to be worse than accepting the risk related to the procedure. The experience of being thoroughly advised by their physician formed the basis of an autonomous trust. The trust they felt for the physicians＇ recommendations mitigated ambivalence about the procedure and risks. TAVR patients expressed feelings consistent with self-empowerment and claimed that it had to be their decision. Even so, choosing the intervention as an obligation to their family or passively accepting it was also reported. Conclusions Older TAVR patients＇ experience of an autonomous decision may encompass frank tradeoff; deliberate physician dependency as well as a resilient self-view. Physicians should be especially aware of how older adults＇ subtle cognitive declines and inclinations to preserve their identities which can influence their medical decision making when obtaining in- formed consent. Cardiologists and other providers may also use these insights to develop new strategies that better respond to such inherent complexities.
文摘This article is based on research on pre-service teachers＇ perspectives on their mathematics knowledge of proof in geometry. The study was framed using tile mathematical knowledge for teaching framework. This qualitative study employed the use of a task-based worksheet, focus group sessions and semi-structured individual interviews. The task-based worksheet was completed by 180 pre-service mathematics teachers （second, third and fourth year mathematics education students）. Pre-service mathematics teachers are student teachers who have not yet completed their training to become teachers. After the analysis of the task-based worksheet, 20 participants were invited to participate in focus group sessions and individual interviews. The findings of the study reveal that the participants possess peripheral mathematics knowledge of proof in geometry. The study aims at assisting pre-service teachers and interested educationists to explore innovative methods of acquiring and imparting mathematics knowledge of proof in geometry. The study proposes possible changes in curriculum at school and university level.
文摘The purpose of this article is to investigate visual literacy from the perspective of the VTS （Visual Thinking Strategies） method. The authors examine the viewpoints of seven American elementary school teachers on visual literacy and its meanings in the context of the VTS method. Data collection was done using a semi-structured questionnaire, which was followed by theory-driven content analysis. The authors emphasize that when supporting holistic development in a teaching context, it is the interconnected nature of aesthetics, growth and the learner＇s learning which is more important than developing special skills, like visual literacy. In the teaching context visual literacy and language development should be acknowledged in pedagogy and research.
基金supported by Joint Fund of Advanced Aerospace Manufacturing Technology Research(No. U1937601)the partial financial support of this research by the budget program of Ukraine“Support for the Development of Priority Research Areas”(No.CPCEC 6451230)。
文摘By making use of the direct integration method,an exact analysis of the general three-dimensional thermoelasticity problem is performed for the case of a transversely isotropic homogeneous half-space subject to local thermal and force loadings.The material plane of isotropy is assumed to be parallel to the limiting surface of the halfspace.By reducing the original thermoelasticity equations to the governing ones for individual stress-tensor components,the effect of material anisotropy in the stress field is analyzed with regard to the feasibility requirement,i.e.,the finiteness of the stress field at a distance from the disturbed area.As a result,the solution is constructed in the form of explicit analytical dependencies on the force and thermal loadings for various kinds of transversely isotropic materials and agrees with the basic principles of the continua mechanics.The solution can be efficiently used as a benchmark one for the direct computation of temperature and thermal stresses in transversely isotropic semi-infinite domains,as well as for the verification of solutions constructed by different means.
文摘The progressive stacking of chalcogenide single layers gives rise to two- dimensional semiconducting materials with tunable properties that can be exploited for new field-effect transistors and photonic devices. Yet the properties of some members of the chalcogenide family remain unexplored. Indium selenide （InSe） is attractive for applications due to its direct bandgap in the near infrared, controllable p- and n-type doping and high chemical stability. Here, we reveal the lattice dynamics, optical and electronic properties of atomically thin InSe flakes prepared by micromechanical cleavage. Raman active modes stiffen or soften in the flakes depending on which electronic bonds are excited. A progressive blue-shift of the photoluminescence peaks is observed for decreasing flake thickness （as large as 0.2 eV for three single layers）. First-principles calculations predict an even larger increase in the bandgap, 0.40 eV, for three single layers, and as much as 1.1 eV for a single layer. These results are promising from the point of view of the versatility of this material for optoelectronic applications at the nanometer scale and compatible with Si and III-V technologies.
基金supported by National Natural Science Foundation of China (Grant Nos.11171014 and 11101024)National Basic Research Program of China (973 Project) (Grant No. 2010CB731900)
文摘Semi-supervised learning is an emerging computational paradigm for machine learning,that aims to make better use of large amounts of inexpensive unlabeled data to improve the learning performance.While various methods have been proposed based on different intuitions,the crucial issue of generalization performance is still poorly understood.In this paper,we investigate the convergence property of the Laplacian regularized least squares regression,a semi-supervised learning algorithm based on manifold regularization.Moreover,the improvement of error bounds in terms of the number of labeled and unlabeled data is presented for the first time as far as we know.The convergence rate depends on the approximation property and the capacity of the reproducing kernel Hilbert space measured by covering numbers.Some new techniques are exploited for the analysis since an extra regularizer is introduced.
