To validate the design rationality of the power coupler for the RFQ cavity and minimize cavity contamination,we designed a low-loss offline conditioning cavity and conducted high-power testing.This offline cavity feat...To validate the design rationality of the power coupler for the RFQ cavity and minimize cavity contamination,we designed a low-loss offline conditioning cavity and conducted high-power testing.This offline cavity features two coupling ports and two tuners,operating at a frequency of 162.5 MHz with a tuning range of 3.2 MHz.Adjusting the installation angle of the coupling ring and the insertion depth of the tuner helps minimize cavity losses.We performed electromagnetic structural and multiphysics simulations,revealing a minimal theoretical power loss of 4.3%.However,when the cavity frequency varied by110 kHz,theoretical power losses increased to10%,necessitating constant tuner adjustments during conditioning.Multiphysics simulations indicated that increased cavity temperature did not affect frequency variation.Upon completion of the offline high-power conditioning platform,we measured the transmission performance,revealing a power loss of 6.3%,exceeding the theoretical calculation.Conditioning utilized efficient automatic range scanning and standing wave resonant methods.To fully condition the power coupler,a 15°phase difference between two standing wave points in the condition-ing system was necessary.Notably,the maximum continuous wave power surpassed 20 kW,exceeding the expected target.展开更多
The purpose of this paper is to explore the application of online and offline blended teaching in local anatomy courses of acupuncture specialty.It introduces the concept and characteristics of blended teaching mode a...The purpose of this paper is to explore the application of online and offline blended teaching in local anatomy courses of acupuncture specialty.It introduces the concept and characteristics of blended teaching mode and analyzes the respective advantages of online and offline teaching as well as the advantages and application prospects of blended teaching mode.The teaching status quo of local anatomy courses in acupuncture and moxibustion is analyzed,pointing out the problems of the traditional teaching mode and the application prospect of the blended teaching mode.In the practical part,the preparation and design of online teaching resources,the design of offline practical teaching sessions,and the evaluation methods of teaching effect are introduced in detail.This study aims to provide new teaching modes and ideas for teaching acupuncture and moxibustion and promote the improvement of teaching quality.展开更多
With the development of information technology,the blended online and offline teaching mode has gradually become a new trend in the teaching of ideological and political theory courses in universities.This article ana...With the development of information technology,the blended online and offline teaching mode has gradually become a new trend in the teaching of ideological and political theory courses in universities.This article analyzes the current situation and existing problems of blended online and offline teaching of ideological and political courses in universities,and explores how to effectively combine online and offline teaching resources to improve the teaching effectiveness of ideological and political courses in universities.展开更多
Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited n...Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited number of signature samples are available to train these models in a real-world scenario.Several researchers have proposed models to augment new signature images by applying various transformations.Others,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature samples.Hence,augmenting a sufficient number of signatures with variations is still a challenging task.This study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature verification.The proposed model is capable of augmenting better quality signatures with diversity from a single signature image only.It is empirically evaluated on widely used public datasets;GPDSsyntheticSignature.The quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIM),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy rate.Experiment results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation methods.The improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.展开更多
Since flight accidents due to aircraft icing occur from time to time,this paper proposes an array of impact rod-type plasma synthetic jet de-icing methods for aircraft icing problems.The impact rod-type plasma synthet...Since flight accidents due to aircraft icing occur from time to time,this paper proposes an array of impact rod-type plasma synthetic jet de-icing methods for aircraft icing problems.The impact rod-type plasma synthetic jet actuator(PSJA)is based on the traditional PSJA with an additional impact rod structure for better de-icing in the flight environment.In this work,we first optimize the ice-breaking performance of a single-impact rod-type PSJA,and then conduct an array of impact rod-type plasma synthetic jet ice-breaking experiments to investigate the relationship between crack expansion and discharge energy,ice thickness and group spacing.The results show that the impact force and impulse of a single-impact rod-type PSJA are proportional to the discharge energy,and there exists a threshold energy Qmin for a single actuator to break the ice,which is proportional to the ice thickness.Only when the discharge energy reaches above Qmin can the ice layer produce cracks,and at the same time,the maximum radial crack length produced during the ice-breaking process is proportional to the discharge energy.When the ice is broken by an array of impact rod PSJAs,the discharge energy and group spacing together determine whether the crack can be extended to the middle region of the actuator.When the group spacing is certain,increasing the energy can increase the intersection of cracks in the middle region,and the ice-fragmentation degree is increased and the ice-breaking effect is better.At the same time,the energy estimation method of ice breaking by an array of impact rod-type PSJAs is proposed according to the law when a single actuator is breaking ice.展开更多
Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other...Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business envir-onments.However,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective information.Second,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass differences.These challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective information.To solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature images.Moreover,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature images.In addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of strokes.We respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification methods.This is more helpful to the task of signature authentication in justice and finance.展开更多
In order to combine the advantages of online teaching and traditional offline classroom teaching,this paper optimizes the teaching design by taking Musculoskeletal Rehabilitation for undergraduates as the carrier,and ...In order to combine the advantages of online teaching and traditional offline classroom teaching,this paper optimizes the teaching design by taking Musculoskeletal Rehabilitation for undergraduates as the carrier,and reconstructs the course according to five parts:basic theory course,practical training course,standardized patient,case report,and course evaluation.Through analyzing the classroom quality and teaching effect,the innovation and practical effect of course reconstruction are explored.With students as the main body and goals as the guide,this model gives full play to the initiative and creativity of students,meets the individual needs of students at different levels,and provides reference ideas for improving the advanced,innovative and challenging creation of the course.展开更多
Taking construction of the online and offline integrated first-class undergraduate curriculum teaching modes of Histology and Embryology in Guangxi as an opportunity,under the guidance of student-centered teaching con...Taking construction of the online and offline integrated first-class undergraduate curriculum teaching modes of Histology and Embryology in Guangxi as an opportunity,under the guidance of student-centered teaching concept,efforts were made to innovate online and offline integrated teaching mode to overcome the shortcomings and dilemma of traditional Histology and Embryology teaching,with attention paid to the competence education in students including schematic knowledge,professional techniques,analytical thinking,and ideological and political theories,which would be of great significance for the cultivation of high-quality professionals specialized in traditional Chinese medicine.展开更多
Offline reinforcement learning(ORL)aims to learn a rational agent purely from behavior data without any online interaction.One of the major challenges encountered in ORL is the problem of distribution shift,i.e.,the m...Offline reinforcement learning(ORL)aims to learn a rational agent purely from behavior data without any online interaction.One of the major challenges encountered in ORL is the problem of distribution shift,i.e.,the mismatch between the knowledge of the learned policy and the reality of the underlying environment.Recent works usually handle this in a too pessimistic manner to avoid out-of-distribution(OOD)queries as much as possible,but this can influence the robustness of the agents at unseen states.In this paper,we propose a simple but effective method to address this issue.The key idea of our method is to enhance the robustness of the new policy learned offline by weakening its confidence in highly uncertain regions,and we propose to find those regions by simulating them with modified Generative Adversarial Nets(GAN)such that the generated data not only follow the same distribution with the old experience but are very difficult to deal with by themselves,with regard to the behavior policy or some other reference policy.We then use this information to regularize the ORL algorithm to penalize the overconfidence behavior in these regions.Extensive experiments on several publicly available offline RL benchmarks demonstrate the feasibility and effectiveness of the proposed method.展开更多
With the deepening development of educational informatization, online and offline blended teaching, as a new teaching mode, is increasingly receiving widespread attention from educators [1]. At present, the reform of ...With the deepening development of educational informatization, online and offline blended teaching, as a new teaching mode, is increasingly receiving widespread attention from educators [1]. At present, the reform of the “online and offline blended teaching” of ideological and political education courses directly affects the quality of talent cultivation in universities. The article takes the course “Introduction to Basic Principles of Marxism” as an example to explore the reform mode of “online and offline blended teaching” in ideological and political theory courses in universities from the aspects of reasonable allocation of class hours, design of online teaching activities, how to deepen classroom teaching offline, and diversified assessment modes. Furthermore, the article summarizes the experience of mode reform and promotes the deep development of the people-oriented education concept in ideological and political courses in universities, so as to achieve the ultimate goal of moral education in ideological and political education in universities.展开更多
以高职航海技术专业为例,分析现代学徒制培养模式下的瓶颈问题,探究引入O2O(Online to Offline)教学方式,在线上线下形成学生、学校和企业共同参与的工学结合、产教融合的教学生态,提高航海技术专业学徒制学生的自主学习能力、专业技能...以高职航海技术专业为例,分析现代学徒制培养模式下的瓶颈问题,探究引入O2O(Online to Offline)教学方式,在线上线下形成学生、学校和企业共同参与的工学结合、产教融合的教学生态,提高航海技术专业学徒制学生的自主学习能力、专业技能和综合素质,培养满足社会和航运企业需求的航海人才。展开更多
Pavement snow and icing are worldwide problems, but effective countermeasures are just beginning to be developed in China. The two most common snow and ice removal methods are mechanical clearance and chemical melting...Pavement snow and icing are worldwide problems, but effective countermeasures are just beginning to be developed in China. The two most common snow and ice removal methods are mechanical clearance and chemical melting, and the advantages and disadvantages of each approach are discussed here, including environmental and structural damage caused by corrosive snow melting agents. New developments in chemical melting agents and mechanical equipment are discussed, and an overview of alternative thermal melting systems is presented, including the use of geothermy and non-geothermal heating systems utilizing solar energy, electricity, conductive pavement materials, and infrared/microwave applications. Strategic recommendations are made for continued enhancement of public safety in snow and ice conditions.展开更多
Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more...Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more challenge is, afterFukushimacrisis, without the nuclear energy,Japanmay produce about 15 percent more GHG emissions than1990 inthis fiscal year. It still has to struggle to meet the target set by Kyoto Protocol. The demonstration area of “smart community” suggests Japanese exploration for new low carbon strategies. The study proposed a demand side response energy system, a dynamic tree-like hierarchical model for smart community. The model not only conveyed the concept of smart grid, but also built up a smart heat energy supply chain by offline heat transport system. Further, this model promoted a collaborative energy utilization mode between the industrial sector and the civil sector. In addition, the research chose the smart community inKitakyushuas case study and executed the model. The simulation and the analysis of the model not only evaluate the environmental effect of different technologies but also suggest that the smart community inJapanhas the potential but not easy to achieve the target, cut down 50% of the CO2 emission.展开更多
Offline Urdu Nastaleeq text recognition has long been a serious problem due to its very cursive nature. In order to get rid of the character segmentation problems, many researchers are shifting focus towards segmentat...Offline Urdu Nastaleeq text recognition has long been a serious problem due to its very cursive nature. In order to get rid of the character segmentation problems, many researchers are shifting focus towards segmentation free ligature based recognition approaches. Majority of the prevalent ligature based recognition systems heavily rely on hand-engineered feature extraction techniques. However, such techniques are more error prone and may often lead to a loss of useful information that might hardly be captured later by any manual features. Most of the prevalent Urdu Nastaleeq test recognition was trained and tested on small sets. This paper proposes the use of stacked denoising autoencoder for automatic feature extraction directly from raw pixel values of ligature images. Such deep learning networks have not been applied for the recognition of Urdu text thus far. Different stacked denoising autoencoders have been trained on 178573 ligatures with 3732 classes from un-degraded(noise free) UPTI(Urdu Printed Text Image) data set. Subsequently, trained networks are validated and tested on degraded versions of UPTI data set. The experimental results demonstrate accuracies in range of 93% to 96% which are better than the existing Urdu OCR systems for such large dataset of ligatures.展开更多
De-icing technology has become an increasingly important subject in numerous applications in recent years.However,the direct numerical modeling and simulation the physical process of thermomechanical deicing is limite...De-icing technology has become an increasingly important subject in numerous applications in recent years.However,the direct numerical modeling and simulation the physical process of thermomechanical deicing is limited.This work is focusing on developing a numerical model and tool to direct simulate the de-icing process in the framework of the coupled thermo-mechanical peridynamics theory.Here,we adopted the fully coupled thermo-mechanical bond-based peridynamics(TM-BB-PD)method for modeling and simulation of de-icing.Within the framework of TM-BB-PD,the ice constitutive model is established by considering the influence of the temperature difference between two material points,and a modified failure criteria is proposed,which takes into account temperature effect to predict the damage of quasi-brittle ice material.Moreover,thermal boundary condition is used to simulate the thermal load in the de-icing process.By comparing with the experimental results and the previous reported finite element modeling,our numerical model shows good agreement with the previous predictions.Based on the numerical results,we find that the developed method can not only predict crack initiation and propagation in the ice,but also predict the temperature distribution and heat conduction during the de-icing process.Furthermore,the influence of the temperature for the ice crack growth pattern is discussed accordingly.In conclusion,the coupled thermal-mechanical peridynamics formulation with modified failure criterion is capable of providing a modeling tool for engineering applications of de-icing technology.展开更多
An improved generalized predictive control algorithm is presented in thispaper by incorporating offline identification into online identification. Unlike the existinggeneralized predictive control algorithms, the prop...An improved generalized predictive control algorithm is presented in thispaper by incorporating offline identification into online identification. Unlike the existinggeneralized predictive control algorithms, the proposed approach divides parameters of a predictivemodel into the time invariant and time-varying ones, which are treated respectively by offline andonline identification algorithms. Therefore, both the reliability and accuracy of the predictivemodel are improved. Two simulation examples of control of a fixed bed reactor show that this newalgorithm is not only reliable and stable in the case of uncertainties and abnormal disturbances,but also adaptable to slow time varying processes.展开更多
Inherent complexity of plant metabolites necessitates the use of multi-dimensional information to accomplish comprehensive profiling and confirmative identification.A dimension-enhanced strategy,by offline two-dimensi...Inherent complexity of plant metabolites necessitates the use of multi-dimensional information to accomplish comprehensive profiling and confirmative identification.A dimension-enhanced strategy,by offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry(2 D-LC/IM-QTOF-MS)enabling four-dimensional separations(2 D-LC,IM,and MS),is proposed.In combination with in-house database-driven automated peak annotation,this strategy was utilized to characterize ginsenosides simultaneously from white ginseng(WG)and red ginseng(RG).An offline 2 DLC system configuring an Xbridge Amide column and an HSS T3 column showed orthogonality 0.76 in the resolution of ginsenosides.Ginsenoside analysis was performed by data-independent high-definition MSE(HDMSE)in the negative ESI mode on a Vion?IMS-QTOF hybrid high-resolution mass spectrometer,which could better resolve ginsenosides than MSEand directly give the CCS information.An in-house ginsenoside database recording 504 known ginsenosides and 58 reference compounds,was established to assist the identification of ginsenosides.Streamlined workflows,by applying UNIFI?to automatedly annotate the HDMSEdata,were proposed.We could separate and characterize 323 ginsenosides(including 286 from WG and 306 from RG),and 125 thereof may have not been isolated from the Panax genus.The established 2 D-LC/IM-QTOF-HDMSEapproach could also act as a magnifier to probe differentiated components between WG and RG.Compared with conventional approaches,this dimensionenhanced strategy could better resolve coeluting herbal components and more efficiently,more reliably identify the multicomponents,which,we believe,offers more possibilities for the systematic exposure and confirmative identification of plant metabolites.展开更多
基金supported by the Chinese initiative accelerator driven subcritical system and the hundred talents plan of the Chinese Academy of Sciences(No.E129841Y).
文摘To validate the design rationality of the power coupler for the RFQ cavity and minimize cavity contamination,we designed a low-loss offline conditioning cavity and conducted high-power testing.This offline cavity features two coupling ports and two tuners,operating at a frequency of 162.5 MHz with a tuning range of 3.2 MHz.Adjusting the installation angle of the coupling ring and the insertion depth of the tuner helps minimize cavity losses.We performed electromagnetic structural and multiphysics simulations,revealing a minimal theoretical power loss of 4.3%.However,when the cavity frequency varied by110 kHz,theoretical power losses increased to10%,necessitating constant tuner adjustments during conditioning.Multiphysics simulations indicated that increased cavity temperature did not affect frequency variation.Upon completion of the offline high-power conditioning platform,we measured the transmission performance,revealing a power loss of 6.3%,exceeding the theoretical calculation.Conditioning utilized efficient automatic range scanning and standing wave resonant methods.To fully condition the power coupler,a 15°phase difference between two standing wave points in the condition-ing system was necessary.Notably,the maximum continuous wave power surpassed 20 kW,exceeding the expected target.
文摘The purpose of this paper is to explore the application of online and offline blended teaching in local anatomy courses of acupuncture specialty.It introduces the concept and characteristics of blended teaching mode and analyzes the respective advantages of online and offline teaching as well as the advantages and application prospects of blended teaching mode.The teaching status quo of local anatomy courses in acupuncture and moxibustion is analyzed,pointing out the problems of the traditional teaching mode and the application prospect of the blended teaching mode.In the practical part,the preparation and design of online teaching resources,the design of offline practical teaching sessions,and the evaluation methods of teaching effect are introduced in detail.This study aims to provide new teaching modes and ideas for teaching acupuncture and moxibustion and promote the improvement of teaching quality.
文摘With the development of information technology,the blended online and offline teaching mode has gradually become a new trend in the teaching of ideological and political theory courses in universities.This article analyzes the current situation and existing problems of blended online and offline teaching of ideological and political courses in universities,and explores how to effectively combine online and offline teaching resources to improve the teaching effectiveness of ideological and political courses in universities.
文摘Offline signature verification(OfSV)is essential in preventing the falsification of documents.Deep learning(DL)based OfSVs require a high number of signature images to attain acceptable performance.However,a limited number of signature samples are available to train these models in a real-world scenario.Several researchers have proposed models to augment new signature images by applying various transformations.Others,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature samples.Hence,augmenting a sufficient number of signatures with variations is still a challenging task.This study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature verification.The proposed model is capable of augmenting better quality signatures with diversity from a single signature image only.It is empirically evaluated on widely used public datasets;GPDSsyntheticSignature.The quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIM),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy rate.Experiment results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation methods.The improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.
基金financially supported by National Natural Science Foundation of China(No.12002384)National Key Laboratory Foundation of China(No.614220220200107)+1 种基金National Science and Technology Major Project of China(No.J2019-II-0014-0035)Academician Workstation F0undation of the Green Aerotechnics Research Institute of Chongqing Jiaotong University(No.GATRI2020C06003)。
文摘Since flight accidents due to aircraft icing occur from time to time,this paper proposes an array of impact rod-type plasma synthetic jet de-icing methods for aircraft icing problems.The impact rod-type plasma synthetic jet actuator(PSJA)is based on the traditional PSJA with an additional impact rod structure for better de-icing in the flight environment.In this work,we first optimize the ice-breaking performance of a single-impact rod-type PSJA,and then conduct an array of impact rod-type plasma synthetic jet ice-breaking experiments to investigate the relationship between crack expansion and discharge energy,ice thickness and group spacing.The results show that the impact force and impulse of a single-impact rod-type PSJA are proportional to the discharge energy,and there exists a threshold energy Qmin for a single actuator to break the ice,which is proportional to the ice thickness.Only when the discharge energy reaches above Qmin can the ice layer produce cracks,and at the same time,the maximum radial crack length produced during the ice-breaking process is proportional to the discharge energy.When the ice is broken by an array of impact rod PSJAs,the discharge energy and group spacing together determine whether the crack can be extended to the middle region of the actuator.When the group spacing is certain,increasing the energy can increase the intersection of cracks in the middle region,and the ice-fragmentation degree is increased and the ice-breaking effect is better.At the same time,the energy estimation method of ice breaking by an array of impact rod-type PSJAs is proposed according to the law when a single actuator is breaking ice.
基金This work was supported,in part,by the National Nature Science Foundation of China under grant numbers 62272236in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20201136,BK20191401in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business envir-onments.However,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective information.Second,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass differences.These challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective information.To solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature images.Moreover,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature images.In addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of strokes.We respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification methods.This is more helpful to the task of signature authentication in justice and finance.
基金Supported by Guangxi Higher Education Undergraduate Teaching Reform Project(2023JGB238)Hospital Education Teaching Reform and Research Project(2022JG03B)School-level Teaching Reform Project of Guangxi University of Chinese Medicine(2022B029)。
文摘In order to combine the advantages of online teaching and traditional offline classroom teaching,this paper optimizes the teaching design by taking Musculoskeletal Rehabilitation for undergraduates as the carrier,and reconstructs the course according to five parts:basic theory course,practical training course,standardized patient,case report,and course evaluation.Through analyzing the classroom quality and teaching effect,the innovation and practical effect of course reconstruction are explored.With students as the main body and goals as the guide,this model gives full play to the initiative and creativity of students,meets the individual needs of students at different levels,and provides reference ideas for improving the advanced,innovative and challenging creation of the course.
基金Supported by the Project for Undergraduate Education and Teaching Reform and Research at the District Level of Guangxi (2020JGB233)the Key Project for Undergraduate Education and Teaching Reform and Research of Guangxi University of Chinese Medicine (2018B07)。
文摘Taking construction of the online and offline integrated first-class undergraduate curriculum teaching modes of Histology and Embryology in Guangxi as an opportunity,under the guidance of student-centered teaching concept,efforts were made to innovate online and offline integrated teaching mode to overcome the shortcomings and dilemma of traditional Histology and Embryology teaching,with attention paid to the competence education in students including schematic knowledge,professional techniques,analytical thinking,and ideological and political theories,which would be of great significance for the cultivation of high-quality professionals specialized in traditional Chinese medicine.
基金supported by the National Key R&D program of China under Grant No.2021ZD0113203National Science Foundation of China under Grant No.61976115.
文摘Offline reinforcement learning(ORL)aims to learn a rational agent purely from behavior data without any online interaction.One of the major challenges encountered in ORL is the problem of distribution shift,i.e.,the mismatch between the knowledge of the learned policy and the reality of the underlying environment.Recent works usually handle this in a too pessimistic manner to avoid out-of-distribution(OOD)queries as much as possible,but this can influence the robustness of the agents at unseen states.In this paper,we propose a simple but effective method to address this issue.The key idea of our method is to enhance the robustness of the new policy learned offline by weakening its confidence in highly uncertain regions,and we propose to find those regions by simulating them with modified Generative Adversarial Nets(GAN)such that the generated data not only follow the same distribution with the old experience but are very difficult to deal with by themselves,with regard to the behavior policy or some other reference policy.We then use this information to regularize the ORL algorithm to penalize the overconfidence behavior in these regions.Extensive experiments on several publicly available offline RL benchmarks demonstrate the feasibility and effectiveness of the proposed method.
文摘With the deepening development of educational informatization, online and offline blended teaching, as a new teaching mode, is increasingly receiving widespread attention from educators [1]. At present, the reform of the “online and offline blended teaching” of ideological and political education courses directly affects the quality of talent cultivation in universities. The article takes the course “Introduction to Basic Principles of Marxism” as an example to explore the reform mode of “online and offline blended teaching” in ideological and political theory courses in universities from the aspects of reasonable allocation of class hours, design of online teaching activities, how to deepen classroom teaching offline, and diversified assessment modes. Furthermore, the article summarizes the experience of mode reform and promotes the deep development of the people-oriented education concept in ideological and political courses in universities, so as to achieve the ultimate goal of moral education in ideological and political education in universities.
基金supported by the National Natural Science Fund of China(No.41121061)the National Key Basic Research and Development Program(No.2012CB026102)the Fund of the "Hundred People Plan" of CAS(to WenBing Yu)
文摘Pavement snow and icing are worldwide problems, but effective countermeasures are just beginning to be developed in China. The two most common snow and ice removal methods are mechanical clearance and chemical melting, and the advantages and disadvantages of each approach are discussed here, including environmental and structural damage caused by corrosive snow melting agents. New developments in chemical melting agents and mechanical equipment are discussed, and an overview of alternative thermal melting systems is presented, including the use of geothermy and non-geothermal heating systems utilizing solar energy, electricity, conductive pavement materials, and infrared/microwave applications. Strategic recommendations are made for continued enhancement of public safety in snow and ice conditions.
文摘Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more challenge is, afterFukushimacrisis, without the nuclear energy,Japanmay produce about 15 percent more GHG emissions than1990 inthis fiscal year. It still has to struggle to meet the target set by Kyoto Protocol. The demonstration area of “smart community” suggests Japanese exploration for new low carbon strategies. The study proposed a demand side response energy system, a dynamic tree-like hierarchical model for smart community. The model not only conveyed the concept of smart grid, but also built up a smart heat energy supply chain by offline heat transport system. Further, this model promoted a collaborative energy utilization mode between the industrial sector and the civil sector. In addition, the research chose the smart community inKitakyushuas case study and executed the model. The simulation and the analysis of the model not only evaluate the environmental effect of different technologies but also suggest that the smart community inJapanhas the potential but not easy to achieve the target, cut down 50% of the CO2 emission.
基金National Natural Science Foundation of China (Project No. 61273365)111 Project (No. B08004) are gratefully acknowledged
文摘Offline Urdu Nastaleeq text recognition has long been a serious problem due to its very cursive nature. In order to get rid of the character segmentation problems, many researchers are shifting focus towards segmentation free ligature based recognition approaches. Majority of the prevalent ligature based recognition systems heavily rely on hand-engineered feature extraction techniques. However, such techniques are more error prone and may often lead to a loss of useful information that might hardly be captured later by any manual features. Most of the prevalent Urdu Nastaleeq test recognition was trained and tested on small sets. This paper proposes the use of stacked denoising autoencoder for automatic feature extraction directly from raw pixel values of ligature images. Such deep learning networks have not been applied for the recognition of Urdu text thus far. Different stacked denoising autoencoders have been trained on 178573 ligatures with 3732 classes from un-degraded(noise free) UPTI(Urdu Printed Text Image) data set. Subsequently, trained networks are validated and tested on degraded versions of UPTI data set. The experimental results demonstrate accuracies in range of 93% to 96% which are better than the existing Urdu OCR systems for such large dataset of ligatures.
基金the University of California at Berkeley.Ms.Y.Song gratefully acknowledges the financial support from the Chinese Scholar Council(CSC Grant No.201706680094).
文摘De-icing technology has become an increasingly important subject in numerous applications in recent years.However,the direct numerical modeling and simulation the physical process of thermomechanical deicing is limited.This work is focusing on developing a numerical model and tool to direct simulate the de-icing process in the framework of the coupled thermo-mechanical peridynamics theory.Here,we adopted the fully coupled thermo-mechanical bond-based peridynamics(TM-BB-PD)method for modeling and simulation of de-icing.Within the framework of TM-BB-PD,the ice constitutive model is established by considering the influence of the temperature difference between two material points,and a modified failure criteria is proposed,which takes into account temperature effect to predict the damage of quasi-brittle ice material.Moreover,thermal boundary condition is used to simulate the thermal load in the de-icing process.By comparing with the experimental results and the previous reported finite element modeling,our numerical model shows good agreement with the previous predictions.Based on the numerical results,we find that the developed method can not only predict crack initiation and propagation in the ice,but also predict the temperature distribution and heat conduction during the de-icing process.Furthermore,the influence of the temperature for the ice crack growth pattern is discussed accordingly.In conclusion,the coupled thermal-mechanical peridynamics formulation with modified failure criterion is capable of providing a modeling tool for engineering applications of de-icing technology.
基金Supported by the National Natural Science Foundation of China (No. 20206028) and the Qingdao Municipal Major Lab of Industry Information Technology.
文摘An improved generalized predictive control algorithm is presented in thispaper by incorporating offline identification into online identification. Unlike the existinggeneralized predictive control algorithms, the proposed approach divides parameters of a predictivemodel into the time invariant and time-varying ones, which are treated respectively by offline andonline identification algorithms. Therefore, both the reliability and accuracy of the predictivemodel are improved. Two simulation examples of control of a fixed bed reactor show that this newalgorithm is not only reliable and stable in the case of uncertainties and abnormal disturbances,but also adaptable to slow time varying processes.
基金the National Natural Science Foundation of China(Grant No.81872996)the State Key Research and Development Project(Grant No.2017YFC1702104)+1 种基金the State Key Project for the Creation of Major New Drugs(2018ZX09711001-009-010)the Tianjin Municipal Education Commission Research Project(Grant No.2017ZD07)。
文摘Inherent complexity of plant metabolites necessitates the use of multi-dimensional information to accomplish comprehensive profiling and confirmative identification.A dimension-enhanced strategy,by offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry(2 D-LC/IM-QTOF-MS)enabling four-dimensional separations(2 D-LC,IM,and MS),is proposed.In combination with in-house database-driven automated peak annotation,this strategy was utilized to characterize ginsenosides simultaneously from white ginseng(WG)and red ginseng(RG).An offline 2 DLC system configuring an Xbridge Amide column and an HSS T3 column showed orthogonality 0.76 in the resolution of ginsenosides.Ginsenoside analysis was performed by data-independent high-definition MSE(HDMSE)in the negative ESI mode on a Vion?IMS-QTOF hybrid high-resolution mass spectrometer,which could better resolve ginsenosides than MSEand directly give the CCS information.An in-house ginsenoside database recording 504 known ginsenosides and 58 reference compounds,was established to assist the identification of ginsenosides.Streamlined workflows,by applying UNIFI?to automatedly annotate the HDMSEdata,were proposed.We could separate and characterize 323 ginsenosides(including 286 from WG and 306 from RG),and 125 thereof may have not been isolated from the Panax genus.The established 2 D-LC/IM-QTOF-HDMSEapproach could also act as a magnifier to probe differentiated components between WG and RG.Compared with conventional approaches,this dimensionenhanced strategy could better resolve coeluting herbal components and more efficiently,more reliably identify the multicomponents,which,we believe,offers more possibilities for the systematic exposure and confirmative identification of plant metabolites.