In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytic...In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.展开更多
Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has bee...Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has been extensively studied,there is still no consensus on the correlation between acoustic attenuation coefficient and sediment physical properties.Predicting the acoustic attenuation coefficient remains a challenging issue in sedimentary acoustic research.In this study,we propose a prediction method for the acoustic attenuation coefficient using machine learning algorithms,specifically the random forest(RF),support vector machine(SVR),and convolutional neural network(CNN)algorithms.We utilized the acoustic attenuation coefficient and sediment particle size data from 52 stations as training parameters,with the particle size parameters as the input feature matrix,and measured acoustic attenuation as the training label to validate the attenuation prediction model.Our results indicate that the error of the attenuation prediction model is small.Among the three models,the RF model exhibited the lowest prediction error,with a mean squared error of 0.8232,mean absolute error of 0.6613,and root mean squared error of 0.9073.Additionally,when we applied the models to predict the data collected at different times in the same region,we found that the models developed in this study also demonstrated a certain level of reliability in real prediction scenarios.Our approach demonstrates that constructing a sediment acoustic characteristics model based on machine learning is feasible to a certain extent and offers a novel perspective for studying sediment acoustic properties.展开更多
Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial i...Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial intelligence technology,especially the breakthrough of deep learning technology,it provides a new idea for bearing fault diagnosis.Deep learning can automatically learn features from a large amount of data,has a strong nonlinear modeling ability,and can effectively solve the problems existing in traditional methods.Aiming at the key problems in bearing fault diagnosis,this paper studies the fault diagnosis method based on deep learning,which not only provides a new solution for bearing fault diagnosis but also provides a reference for the application of deep learning in other mechanical fault diagnosis fields.展开更多
This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by cons...This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by constructing multi-layer neural networks to simulate the learning process of the human brain.The article explores the application of deep learning in solving partial differential equations,optimizing problems,and data-driven modeling,and analyzes its advantages in computational efficiency,accuracy,and adaptability.At the same time,this article also points out the challenges faced by deep learning numerical computation methods in terms of computational efficiency,interpretability,and generalization ability,and proposes strategies and future development directions for integrating with traditional numerical methods.展开更多
Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our ho...Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.展开更多
Objective: Given the unique cultural background, way of life, and physical environment of the Tibetan Plateau, this study aims to investigate the effects of health education using problem-based learning (PBL) approach...Objective: Given the unique cultural background, way of life, and physical environment of the Tibetan Plateau, this study aims to investigate the effects of health education using problem-based learning (PBL) approaches on the knowledge, attitude, practice, and coping skills of women with high-risk pregnancies in this region. Methods: 76 high-risk pregnancy cases were enrolled at Tibet’s Linzhi People’s Hospital between September 2023 and April 2024. 30 patients admitted between September 2023 and December 2023 were selected as the control group and were performed with regular patient education. 46 patients admitted between January 2024 and April 2024 were selected as the observation group and were performed regular patient education with problem-based learning approaches. Two groups’ performance on their health knowledge, attitude, practice and coping skills before and after interventions were evaluated, and patient satisfaction were measured at the end of the study. Results: There was no statistical significance (P P P Conclusions: Health education with problem-based learning approaches is worth promoting as it can help high-risk pregnant women in plateau areas develop better health knowledge, attitude and practice and healthier coping skills. Also, it can improve patient sanctification.展开更多
This study focuses on the application of the“PBL(problem-based learning)+Flipped Classroom”teaching model in bilingual education,aiming to explore its potential to enhance the quality and effectiveness of bilingual ...This study focuses on the application of the“PBL(problem-based learning)+Flipped Classroom”teaching model in bilingual education,aiming to explore its potential to enhance the quality and effectiveness of bilingual teaching.PBL emphasizes learning through the resolution of real-world problems,while the Flipped Classroom advocates that students acquire basic knowledge through self-study before class,dedicating class time to in-depth discussions and practical activities.The integration of these two teaching models in bilingual education aims to stimulate students’interest in learning,improve their autonomous learning abilities,enhance critical thinking,and foster cross-cultural communication skills.Through literature review,case analysis,and empirical research,this study first examines the current applications and challenges of PBL and the Flipped Classroom in bilingual education.Subsequently,it elaborates on the specific implementation steps of the“PBL+Flipped Classroom”teaching model in bilingual education,including problem design,preview material provision,cooperative learning,classroom activities,and language support.A comparative experiment is then conducted to analyze the impact of this teaching model on students’learning motivation,academic performance,and cross-cultural communication skills.The results indicate that the“PBL+Flipped Classroom”teaching model significantly improves students’learning motivation and participation,enhances academic performance,and effectively boosts their cross-cultural communication skills.Furthermore,this model aids in cultivating students’autonomous learning abilities and critical thinking,providing an innovative and effective approach to bilingual education.This study offers new ideas and insights for the field of bilingual education,which is of great significance for promoting the innovation and development of bilingual teaching models.展开更多
The Veterinary Microbiology course is centered around the diagnosis and testing of pathogenic microorganisms,with the core value of“moral education and character development.”It reconstructs multidimensional teachin...The Veterinary Microbiology course is centered around the diagnosis and testing of pathogenic microorganisms,with the core value of“moral education and character development.”It reconstructs multidimensional teaching resources by integrating disciplinary achievements with clinical cases and implements a hybrid teaching approach combining virtual simulation and problem-based learning(PBL)through the“three stages+four models+three reflections”framework.Dual-qualification teachers employ various teaching methods,create a“six-in-one”model for ideological and political education,and conduct formative assessments based on the principles of diversified objectives and process emphasis.The hybrid teaching reform addresses issues such as fragmented knowledge,insufficient class hours,weak animal disease diagnostic abilities among students,limited application and expansion of knowledge points,and students’lack of proactive critical thinking skills.The application of hybrid teaching has shown significant advantages and effectiveness,providing a reference for teaching reform in similar microbiology courses.展开更多
Objective: To explore the application effect of flipped classroom combined with problem-based learning teaching method in clinical skills teaching of standardized training for resident doctors of traditional Chinese M...Objective: To explore the application effect of flipped classroom combined with problem-based learning teaching method in clinical skills teaching of standardized training for resident doctors of traditional Chinese Medicine. Methods: The study used the experimental control method. The study lasted from September to November 2022. The subjects of this study were 49 students of standardized training for resident doctors of traditional Chinese Medicine from grades 2020, 2021 and 2022 of Dazhou integrated TCM & Western Medicine Hospital. They were randomly divided into experiment group (25) and control group (24). The experiment group adopted flipped classroom combined with problem-based learning teaching method, and the control group adopted traditional teaching method. The teaching content was 4 basic clinical skill projects, including four diagnoses of traditional Chinese Medicine, cardiopulmonary resuscitation, dressing change procedure, acupuncture and massage. The evaluation method was carried out by comparing the students’ performance and a self-designed questionnaire was used to investigate the students’ evaluation of the teaching method. Results: The test scores of total scores in the experimental group (90.12 ± 5.89) were all higher than those in the control group (81.47 ± 7.96) (t = 4.53, P P Conclusions: The teaching process of the flipped classroom combined with problem-based learning teaching method is conducive to improving the efficiency of classroom teaching, cultivating students’ self-learning ability, and enhancing students’ willingness to learn.展开更多
Mathematical modeling course has been one of the fast development courses in China since 1992,which mainly trains students’innovation ability.However,the teaching of mathematical modeling course is quite difficult si...Mathematical modeling course has been one of the fast development courses in China since 1992,which mainly trains students’innovation ability.However,the teaching of mathematical modeling course is quite difficult since it requires students to have a strong mathematical foundation,good ability to design algorithms,and programming skills.Besides,limited class hours and lack of interest in learning are the other reasons.To address these problems,according to the outcome-based education,we adopt the problem-based learning combined with a seminar mode in teaching.We customize cases related to computer and software engineering,start from simple problems in daily life,step by step deepen the difficulty,and finally refer to the professional application in computer and software engineering.Also,we focus on ability training rather than mathematical theory or programming language learning.Initially,we prepare the problem,related mathematic theory,and core code for students.Furtherly,we train them how to find the problem,and how to search the related mathematic theory and software tools by references for modeling and analysis.Moreover,we solve the problem of limited class hours by constructing an online resource learning library.After a semester of practical teaching,it has been shown that the interest and learning effectiveness of students have been increased and our reform plan has achieved good results.展开更多
Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recogn...Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recognition System(TSRS)is one of themost important components ofADAS.Among the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time.Accordingly,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules.Firstly,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured frames.Secondly,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise recognition.In addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting technique.Through rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,respectively.Furthermore,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.展开更多
As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst ...As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.展开更多
As an important material for manufacturing resonant components of musical instruments,Paulownia has an important influence on the sound quality of Ruan.In this paper,a model for evaluating the sound quality of Ruan ba...As an important material for manufacturing resonant components of musical instruments,Paulownia has an important influence on the sound quality of Ruan.In this paper,a model for evaluating the sound quality of Ruan based on the vibration characteristics of wood is developed using machine learning methods.Generally,the selection of materials for Ruan manufacturing relies primarily on manually weighing,observing,striking,and listening by the instrument technician.Deficiencies in scientific theory have hindered the quality of the finished Ruan.In this study,nine Ruans were manufactured,and a prediction model of Ruan sound quality was proposed based on the raw material information of Ruans.Out of a total of 180 data sets,145 and 45 sets were chosen for training and validation,respec-tively.In this paper,typical correlation analysis was used to determine the correlation between two single indicators in two adjacent pairwise combinations of the measured objects in each stage of the production process in Ruan.The vibra-tion characteristics of the wood were tested,and a model for predicting the evaluation of Ruan’s acoustic qualities was developed by measuring the vibration characteristics of the resonating plate material.The acoustic quality of the Ruan sound board wood was evaluated and predicted using machine learning model generalized regression neural net-work.The results show that the prediction of Ruan sound quality can be achieved using Matlab simulation based on the vibration characteristics of the soundboard wood.When the model-predicted values were compared with the tradi-tional predicted results,it was found that the generalized regression neural network had good performance,achieving an accuracy of 93.8%which was highly consistent with the experimental results.It was concluded that the model can accurately predict the acoustic quality of the Ruan based on the vibration performance of the soundboards.展开更多
A new approach for flexoelectricmaterial shape optimization is proposed in this study.In this work,a proxymodel based on artificial neural network(ANN)is used to solve the parameter optimization and shape optimization...A new approach for flexoelectricmaterial shape optimization is proposed in this study.In this work,a proxymodel based on artificial neural network(ANN)is used to solve the parameter optimization and shape optimization problems.To improve the fitting ability of the neural network,we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training.The isogeometric analysis-finite element method(IGA-FEM)is used to discretize the flexural theoretical formulas and obtain samples,which helps ANN to build a proxy model from the model shape to the target value.The effectiveness of the proposed method is verified through two numerical examples of parameter optimization and one numerical example of shape optimization.展开更多
The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinea...The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinear in nature,pose challenges for accurate description through physical models.While field data provides insights into real-world effects,its limited volume and quality restrict its utility.Complementing this,numerical simulation models offer effective support.To harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination model.Leveraging fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil reservoirs.Through the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well conditions.The results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.展开更多
English is a key subject in high school that troubles many students,especially in the aspect of vocabulary learning.Only by laying a good vocabulary foundation can students better complete the learning tasks such as r...English is a key subject in high school that troubles many students,especially in the aspect of vocabulary learning.Only by laying a good vocabulary foundation can students better complete the learning tasks such as reading,writing,listening,and speaking training.This paper aims to explain the importance of improving the efficiency of English vocabulary learning and discuss the effective methods of English vocabulary learning in high school,in order to help more students find their own learning methods,improve vocabulary memory and application skills,and lay a solid foundation for follow-up learning,examination,and even work.展开更多
In college badminton teaching,teachers utilize the group cooperative learning method,which not only helps to improve students’badminton skill level but also cultivates their teamwork spirit,communication skills,and s...In college badminton teaching,teachers utilize the group cooperative learning method,which not only helps to improve students’badminton skill level but also cultivates their teamwork spirit,communication skills,and self-management ability unconsciously.In view of this,this paper mainly describes the significance of applying the group cooperative learning method in college badminton teaching,analyzes the current problems in college badminton teaching,and aims to discover effective development strategies for group cooperative learning method in college badminton teaching in order to improve the effectiveness of college badminton teaching.展开更多
Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 vali...Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 valid questionnaires were returned,for an effective return rate of 86.4%.Some 54.4%of the students learned that PBL was a pedagogical method from teachers,and 27.8%of the students had participated in PBL courses.Almost all of students(97.6%)were interested in PBL,and 66.7%of survey participants believed that students who were not good at solving problems would have difficulty in PBL courses.Conclusion:Nursing educators should guide students to adapt to new learning approaches,and encourage students to participate in the teaching reform to promote students’autonomous learning ability,innovation ability,and comprehensive ability.展开更多
Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known e...Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known education methods that can be integrated into ophthalmology education to improve students' competence level and promote active learning. Methods: We used a mixed teaching methodology that integrated a FC and PBL into a 1-week ophthalmology clerkship for 72 fourth-year medical students. The course includes two major sessions: FC session and PBL session, relying on clinical and real-patient cases. Written examinations were set up to assess students' academic performance and questionnaires were designed to evaluate their perceptions. Results: The post-course examination results were higher than the pre-course results, and many students gained ophthalmic knowledge and learning skills to varying levels. Comparison of pre-and post-course questionnaires indicated that interests in ophthalmology increased and more students expressed desires to be eye doctors. Most students were satisfied with the new method, while some suggested the process should be slower and the communication with their teacher needed to strengthen.Conclusions: FC and PBL are complementary methodologies. Utilizing the mixed teaching meth of FC and PBL was successful in enhancing academic performance, student satisfactions and promoting active learning.展开更多
Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effectiv...Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effective PBL problems.The purpose of this paper is to provide a possible solution to the formulation of PBL problems for computer science courses,which is to reimplement open-source projects(ROSP).A case is demonstrated by showing how ROSP was adopted in a practical intercourse-level PBL course module.This paper contributes to a new PBL problem formulation method for promoting PBL in a practical way for Chinese universities.展开更多
文摘In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.
基金funded by the Basic Scientific Fund for National Public Research Institutes of China(No.2022 S01)the National Natural Science Foundation of China(Nos.42176191,42049902,and U22A2012)+5 种基金the Shandong Provincial Natural Science Foundation,China(No.ZR2022YQ40)the National Key R&D Program of China(No.2021YFF0501202)the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2023 SP232)the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.241gqb006)Data acquisition and sample collections were supported by the National Natural Science Foundation of China Open Research Cruise(Cruise No.NORC2021-02+NORC2021301)funded by the Shiptime Sharing Project of the National Natural Science Foundation of China。
文摘Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has been extensively studied,there is still no consensus on the correlation between acoustic attenuation coefficient and sediment physical properties.Predicting the acoustic attenuation coefficient remains a challenging issue in sedimentary acoustic research.In this study,we propose a prediction method for the acoustic attenuation coefficient using machine learning algorithms,specifically the random forest(RF),support vector machine(SVR),and convolutional neural network(CNN)algorithms.We utilized the acoustic attenuation coefficient and sediment particle size data from 52 stations as training parameters,with the particle size parameters as the input feature matrix,and measured acoustic attenuation as the training label to validate the attenuation prediction model.Our results indicate that the error of the attenuation prediction model is small.Among the three models,the RF model exhibited the lowest prediction error,with a mean squared error of 0.8232,mean absolute error of 0.6613,and root mean squared error of 0.9073.Additionally,when we applied the models to predict the data collected at different times in the same region,we found that the models developed in this study also demonstrated a certain level of reliability in real prediction scenarios.Our approach demonstrates that constructing a sediment acoustic characteristics model based on machine learning is feasible to a certain extent and offers a novel perspective for studying sediment acoustic properties.
文摘Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial intelligence technology,especially the breakthrough of deep learning technology,it provides a new idea for bearing fault diagnosis.Deep learning can automatically learn features from a large amount of data,has a strong nonlinear modeling ability,and can effectively solve the problems existing in traditional methods.Aiming at the key problems in bearing fault diagnosis,this paper studies the fault diagnosis method based on deep learning,which not only provides a new solution for bearing fault diagnosis but also provides a reference for the application of deep learning in other mechanical fault diagnosis fields.
文摘This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by constructing multi-layer neural networks to simulate the learning process of the human brain.The article explores the application of deep learning in solving partial differential equations,optimizing problems,and data-driven modeling,and analyzes its advantages in computational efficiency,accuracy,and adaptability.At the same time,this article also points out the challenges faced by deep learning numerical computation methods in terms of computational efficiency,interpretability,and generalization ability,and proposes strategies and future development directions for integrating with traditional numerical methods.
文摘Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.
文摘Objective: Given the unique cultural background, way of life, and physical environment of the Tibetan Plateau, this study aims to investigate the effects of health education using problem-based learning (PBL) approaches on the knowledge, attitude, practice, and coping skills of women with high-risk pregnancies in this region. Methods: 76 high-risk pregnancy cases were enrolled at Tibet’s Linzhi People’s Hospital between September 2023 and April 2024. 30 patients admitted between September 2023 and December 2023 were selected as the control group and were performed with regular patient education. 46 patients admitted between January 2024 and April 2024 were selected as the observation group and were performed regular patient education with problem-based learning approaches. Two groups’ performance on their health knowledge, attitude, practice and coping skills before and after interventions were evaluated, and patient satisfaction were measured at the end of the study. Results: There was no statistical significance (P P P Conclusions: Health education with problem-based learning approaches is worth promoting as it can help high-risk pregnant women in plateau areas develop better health knowledge, attitude and practice and healthier coping skills. Also, it can improve patient sanctification.
基金Quality Engineering Project of Chuzhou University“A Study on the Application of the‘PBL+Flipped Classroom’Teaching Mode Integrated with Rain Classroom in Bilingual Teaching of International Enterprise Management”(2022jyc047)Scientific Research Projects of Higher Education Institutions in Anhui Province“Research on the Mechanism of Enabling the Dual-Chain Integration of‘Industry Chain–Talent Chain’in Anhui through New Quality Productivity”(2024AH052932)+1 种基金Education Science Planning Project of Jiangsu Province“Research on the Reform of Practical Teaching in Open Universities under Digital Transformation”(C/2023/01/126)Project of Social Science Foundation of Jiangsu Province“Research on the Path and Mechanism of Digital Empowerment for the Integration of‘Industry Chain-Talent Chain’in Jiangsu”(23GLD002)。
文摘This study focuses on the application of the“PBL(problem-based learning)+Flipped Classroom”teaching model in bilingual education,aiming to explore its potential to enhance the quality and effectiveness of bilingual teaching.PBL emphasizes learning through the resolution of real-world problems,while the Flipped Classroom advocates that students acquire basic knowledge through self-study before class,dedicating class time to in-depth discussions and practical activities.The integration of these two teaching models in bilingual education aims to stimulate students’interest in learning,improve their autonomous learning abilities,enhance critical thinking,and foster cross-cultural communication skills.Through literature review,case analysis,and empirical research,this study first examines the current applications and challenges of PBL and the Flipped Classroom in bilingual education.Subsequently,it elaborates on the specific implementation steps of the“PBL+Flipped Classroom”teaching model in bilingual education,including problem design,preview material provision,cooperative learning,classroom activities,and language support.A comparative experiment is then conducted to analyze the impact of this teaching model on students’learning motivation,academic performance,and cross-cultural communication skills.The results indicate that the“PBL+Flipped Classroom”teaching model significantly improves students’learning motivation and participation,enhances academic performance,and effectively boosts their cross-cultural communication skills.Furthermore,this model aids in cultivating students’autonomous learning abilities and critical thinking,providing an innovative and effective approach to bilingual education.This study offers new ideas and insights for the field of bilingual education,which is of great significance for promoting the innovation and development of bilingual teaching models.
基金Education Research and Reform Project of the Online Open Course Alliance in the Guangdong-Hong Kong-Macao Greater Bay Area in 2023(WGKM2023158)Research Topic of the Online Open Curriculum Steering Committee of Guangdong Province in 2022(2022ZXKC462)+3 种基金Foshan Philosophy and Social Science Planning Project in 2024(2024-GJ037)Innovation Project of Guangdong Graduate Education(2022JGXM129,2022JGXM128,2023ANLK-080)Demonstration Project of Ideological and Political Reform of Guangdong Education Department(Guangdong Higher Education Letter[2021]No.21)Guangdong Provincial Department of Education,Provincial First-Class Undergraduate Courses(Guangdong Higher Education Letter[2023]No.33)。
文摘The Veterinary Microbiology course is centered around the diagnosis and testing of pathogenic microorganisms,with the core value of“moral education and character development.”It reconstructs multidimensional teaching resources by integrating disciplinary achievements with clinical cases and implements a hybrid teaching approach combining virtual simulation and problem-based learning(PBL)through the“three stages+four models+three reflections”framework.Dual-qualification teachers employ various teaching methods,create a“six-in-one”model for ideological and political education,and conduct formative assessments based on the principles of diversified objectives and process emphasis.The hybrid teaching reform addresses issues such as fragmented knowledge,insufficient class hours,weak animal disease diagnostic abilities among students,limited application and expansion of knowledge points,and students’lack of proactive critical thinking skills.The application of hybrid teaching has shown significant advantages and effectiveness,providing a reference for teaching reform in similar microbiology courses.
文摘Objective: To explore the application effect of flipped classroom combined with problem-based learning teaching method in clinical skills teaching of standardized training for resident doctors of traditional Chinese Medicine. Methods: The study used the experimental control method. The study lasted from September to November 2022. The subjects of this study were 49 students of standardized training for resident doctors of traditional Chinese Medicine from grades 2020, 2021 and 2022 of Dazhou integrated TCM & Western Medicine Hospital. They were randomly divided into experiment group (25) and control group (24). The experiment group adopted flipped classroom combined with problem-based learning teaching method, and the control group adopted traditional teaching method. The teaching content was 4 basic clinical skill projects, including four diagnoses of traditional Chinese Medicine, cardiopulmonary resuscitation, dressing change procedure, acupuncture and massage. The evaluation method was carried out by comparing the students’ performance and a self-designed questionnaire was used to investigate the students’ evaluation of the teaching method. Results: The test scores of total scores in the experimental group (90.12 ± 5.89) were all higher than those in the control group (81.47 ± 7.96) (t = 4.53, P P Conclusions: The teaching process of the flipped classroom combined with problem-based learning teaching method is conducive to improving the efficiency of classroom teaching, cultivating students’ self-learning ability, and enhancing students’ willingness to learn.
基金supported in part by the 2023 Schoollevel Education and Teaching Reform Project of Guangdong Ocean University。
文摘Mathematical modeling course has been one of the fast development courses in China since 1992,which mainly trains students’innovation ability.However,the teaching of mathematical modeling course is quite difficult since it requires students to have a strong mathematical foundation,good ability to design algorithms,and programming skills.Besides,limited class hours and lack of interest in learning are the other reasons.To address these problems,according to the outcome-based education,we adopt the problem-based learning combined with a seminar mode in teaching.We customize cases related to computer and software engineering,start from simple problems in daily life,step by step deepen the difficulty,and finally refer to the professional application in computer and software engineering.Also,we focus on ability training rather than mathematical theory or programming language learning.Initially,we prepare the problem,related mathematic theory,and core code for students.Furtherly,we train them how to find the problem,and how to search the related mathematic theory and software tools by references for modeling and analysis.Moreover,we solve the problem of limited class hours by constructing an online resource learning library.After a semester of practical teaching,it has been shown that the interest and learning effectiveness of students have been increased and our reform plan has achieved good results.
文摘Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recognition System(TSRS)is one of themost important components ofADAS.Among the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time.Accordingly,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules.Firstly,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured frames.Secondly,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise recognition.In addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting technique.Through rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,respectively.Furthermore,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.
基金funded by National Natural Science Foundation of China(Grants Nos.41825018 and 42141009)the Second Tibetan Plateau Scientific Expedition and Research Program(Grants No.2019QZKK0904)。
文摘As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.
基金supported by China Postdoctoral Science Foundation(2019M651240)National Natural Science Foundation of China(31670559).
文摘As an important material for manufacturing resonant components of musical instruments,Paulownia has an important influence on the sound quality of Ruan.In this paper,a model for evaluating the sound quality of Ruan based on the vibration characteristics of wood is developed using machine learning methods.Generally,the selection of materials for Ruan manufacturing relies primarily on manually weighing,observing,striking,and listening by the instrument technician.Deficiencies in scientific theory have hindered the quality of the finished Ruan.In this study,nine Ruans were manufactured,and a prediction model of Ruan sound quality was proposed based on the raw material information of Ruans.Out of a total of 180 data sets,145 and 45 sets were chosen for training and validation,respec-tively.In this paper,typical correlation analysis was used to determine the correlation between two single indicators in two adjacent pairwise combinations of the measured objects in each stage of the production process in Ruan.The vibra-tion characteristics of the wood were tested,and a model for predicting the evaluation of Ruan’s acoustic qualities was developed by measuring the vibration characteristics of the resonating plate material.The acoustic quality of the Ruan sound board wood was evaluated and predicted using machine learning model generalized regression neural net-work.The results show that the prediction of Ruan sound quality can be achieved using Matlab simulation based on the vibration characteristics of the soundboard wood.When the model-predicted values were compared with the tradi-tional predicted results,it was found that the generalized regression neural network had good performance,achieving an accuracy of 93.8%which was highly consistent with the experimental results.It was concluded that the model can accurately predict the acoustic quality of the Ruan based on the vibration performance of the soundboards.
基金supported by a Major Research Project in Higher Education Institutions in Henan Province,with Project Number 23A560015.
文摘A new approach for flexoelectricmaterial shape optimization is proposed in this study.In this work,a proxymodel based on artificial neural network(ANN)is used to solve the parameter optimization and shape optimization problems.To improve the fitting ability of the neural network,we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training.The isogeometric analysis-finite element method(IGA-FEM)is used to discretize the flexural theoretical formulas and obtain samples,which helps ANN to build a proxy model from the model shape to the target value.The effectiveness of the proposed method is verified through two numerical examples of parameter optimization and one numerical example of shape optimization.
基金supported by the China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR20210E260).
文摘The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinear in nature,pose challenges for accurate description through physical models.While field data provides insights into real-world effects,its limited volume and quality restrict its utility.Complementing this,numerical simulation models offer effective support.To harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination model.Leveraging fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil reservoirs.Through the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well conditions.The results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.
文摘English is a key subject in high school that troubles many students,especially in the aspect of vocabulary learning.Only by laying a good vocabulary foundation can students better complete the learning tasks such as reading,writing,listening,and speaking training.This paper aims to explain the importance of improving the efficiency of English vocabulary learning and discuss the effective methods of English vocabulary learning in high school,in order to help more students find their own learning methods,improve vocabulary memory and application skills,and lay a solid foundation for follow-up learning,examination,and even work.
文摘In college badminton teaching,teachers utilize the group cooperative learning method,which not only helps to improve students’badminton skill level but also cultivates their teamwork spirit,communication skills,and self-management ability unconsciously.In view of this,this paper mainly describes the significance of applying the group cooperative learning method in college badminton teaching,analyzes the current problems in college badminton teaching,and aims to discover effective development strategies for group cooperative learning method in college badminton teaching in order to improve the effectiveness of college badminton teaching.
文摘Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 valid questionnaires were returned,for an effective return rate of 86.4%.Some 54.4%of the students learned that PBL was a pedagogical method from teachers,and 27.8%of the students had participated in PBL courses.Almost all of students(97.6%)were interested in PBL,and 66.7%of survey participants believed that students who were not good at solving problems would have difficulty in PBL courses.Conclusion:Nursing educators should guide students to adapt to new learning approaches,and encourage students to participate in the teaching reform to promote students’autonomous learning ability,innovation ability,and comprehensive ability.
基金supported by National Natural Science Foundation of China for Young Scientist (81200686, 81400426)Research Fund for the Doctoral Program of Higher Education of China (20120171120108)+1 种基金Natural Science Foundation of Guangdong Province, China(S2011040005378)Fundamental Research Funds for the Central Universities (11ykpy65, 15ykpy31)
文摘Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known education methods that can be integrated into ophthalmology education to improve students' competence level and promote active learning. Methods: We used a mixed teaching methodology that integrated a FC and PBL into a 1-week ophthalmology clerkship for 72 fourth-year medical students. The course includes two major sessions: FC session and PBL session, relying on clinical and real-patient cases. Written examinations were set up to assess students' academic performance and questionnaires were designed to evaluate their perceptions. Results: The post-course examination results were higher than the pre-course results, and many students gained ophthalmic knowledge and learning skills to varying levels. Comparison of pre-and post-course questionnaires indicated that interests in ophthalmology increased and more students expressed desires to be eye doctors. Most students were satisfied with the new method, while some suggested the process should be slower and the communication with their teacher needed to strengthen.Conclusions: FC and PBL are complementary methodologies. Utilizing the mixed teaching meth of FC and PBL was successful in enhancing academic performance, student satisfactions and promoting active learning.
基金This research was financially supported by the PBL Research and Application Project of Northeastern University(Grant No.PBL-JX2021yb029,PBL-JX2021yb027).
文摘Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effective PBL problems.The purpose of this paper is to provide a possible solution to the formulation of PBL problems for computer science courses,which is to reimplement open-source projects(ROSP).A case is demonstrated by showing how ROSP was adopted in a practical intercourse-level PBL course module.This paper contributes to a new PBL problem formulation method for promoting PBL in a practical way for Chinese universities.
