Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opac...Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opacity(GGO)nodules.Methods:From October 2023 to April 2024,66 medical imaging students were selected and randomly divided into a control group and an observation group,each with 33 students.The control group received traditional lecture-based teaching,while the observation group was taught using a multi-modal teaching approach based on an online case library.Performance on assessments and teaching quality were analyzed between the two groups.Results:The observation group achieved higher scores in theoretical and practical knowledge compared to the control group(P<0.05).Additionally,the teaching quality scores were significantly higher in the observation group(P<0.05).Conclusion:Implementing multi-modal teaching based on an online case library for pulmonary GGO nodule screening with gene methylation combined with spiral CT can enhance students’knowledge acquisition,improve teaching quality,and have significant clinical application value.展开更多
Taking the teaching practice of agricultural landscape planning for example,this paper uses the multi-modal teaching idea for teaching design based on traditional lecture-style teaching,including multi-modal teaching ...Taking the teaching practice of agricultural landscape planning for example,this paper uses the multi-modal teaching idea for teaching design based on traditional lecture-style teaching,including multi-modal teaching materials,multi-modal teaching methods and multi-modal teaching evaluation. The results show that this method can effectively improve students' interest in learning,reinforce the theoretical basis of agricultural landscape planning theory,and improve agricultural landscape planning practical skills. It is the active exploration of multi-modal teaching model and useful complement to traditional classroom teaching.展开更多
Objective: to observe the application effect of multi-modal teaching method in clinical anesthesiology teaching. Methods: a total of 50 anesthesiology students who practiced in our hospital from September 2020 to Augu...Objective: to observe the application effect of multi-modal teaching method in clinical anesthesiology teaching. Methods: a total of 50 anesthesiology students who practiced in our hospital from September 2020 to August 2021 were selected for research. According to different teaching methods, 25 students in the control group received conventional teaching, and 25 students in the research group received multimodal teaching, comparing students' assessment results, learning excellence rate and teaching quality assessment results. Results: the examination scores of students in the study group in anesthesia preparation, tracheal intubation, general anesthesia and local anesthesia, and anesthesia evaluation were all higher than those in the control group (P<0.05). The teaching quality evaluation results of the research group were better than those of the control group (P<0.05);the student satisfaction rate of the research group was 100.0% higher than that of the control group (84.0%) (P<0.05). Conclusion: the application of multi-mode teaching method in clinical teaching can improve the operation level of anesthesiology students and improve their comprehensive quality. The teaching quality is good, which has been widely recognized by students.展开更多
Listening is the breakthrough for conquering English castle, it is not only the requirement of English test, but also the practical use of English knowledge and the embodiment of English comprehensive ability. Listeni...Listening is the breakthrough for conquering English castle, it is not only the requirement of English test, but also the practical use of English knowledge and the embodiment of English comprehensive ability. Listening teaching plays a crucial role in foreign language teaching. However, the effect of listening teaching is undesirable. In recent years, multi-modality theory has been focused by many researchers. In view of particularity of the listening teaching, it is urgent to apply the multi-modality theory to English listening teaching which will produce very good teaching result.展开更多
Based on the teaching video of middle school English teachers, through observation and analysis, it puts forward the problem of less use, wrong use and abuse in the use of teachers' teaching gestures in middle sch...Based on the teaching video of middle school English teachers, through observation and analysis, it puts forward the problem of less use, wrong use and abuse in the use of teachers' teaching gestures in middle school English teaching. And then it puts forward corresponding solutions from three aspects: concept, theory and practice. Hoping to provide further reference to the complementary role of teaching gesture and teaching discourse.展开更多
With the rapid development of China's education, the citizens of the students' comprehensive quality and aesthetic ability requirements are also gradually improving. It is also an effective way to improve stud...With the rapid development of China's education, the citizens of the students' comprehensive quality and aesthetic ability requirements are also gradually improving. It is also an effective way to improve students' interest in music and educate students. Multi-modal music teaching can effectively improve classroom teaching efficiency and optimize students' classroom experience. Then how should teachers carry out the teaching of multi-modal music evaluation?展开更多
Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocar...Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocardiographic data,traditional Chinese medicine(TCM)tongue manifestations,and facial features were collected from patients who underwent coro-nary computed tomography angiography(CTA)in the Cardiac Care Unit(CCU)of Shanghai Tenth People's Hospital between May 1,2023 and May 1,2024.An adaptive weighted multi-modal data fusion(AWMDF)model based on deep learning was constructed to predict the severity of coronary artery stenosis.The model was evaluated using metrics including accura-cy,precision,recall,F1 score,and the area under the receiver operating characteristic(ROC)curve(AUC).Further performance assessment was conducted through comparisons with six ensemble machine learning methods,data ablation,model component ablation,and various decision-level fusion strategies.Results A total of 158 patients were included in the study.The AWMDF model achieved ex-cellent predictive performance(AUC=0.973,accuracy=0.937,precision=0.937,recall=0.929,and F1 score=0.933).Compared with model ablation,data ablation experiments,and various traditional machine learning models,the AWMDF model demonstrated superior per-formance.Moreover,the adaptive weighting strategy outperformed alternative approaches,including simple weighting,averaging,voting,and fixed-weight schemes.Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.展开更多
Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single ...Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.展开更多
With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths ha...With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.展开更多
With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model...This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.展开更多
A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such...A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.展开更多
The development of a new round of artificial intelligence(AI)science and technology provided good technical support and condition guarantee for college English teaching,but it also brought new challenges.It is necessa...The development of a new round of artificial intelligence(AI)science and technology provided good technical support and condition guarantee for college English teaching,but it also brought new challenges.It is necessary and inevitable for English teaching to experience reform and innovation.China’s AI digital teaching transformation is in the exploratory stage,and AI teaching mode has become the focus of future teaching development.Herein we propose a research method of integrating AI tools in college English teaching to adapt to the personalized learning of the new generation of college students,make the teaching process efficiently integrate the tide of the development of AI,promote the development of education evaluation system more accurately,and provide theoretical and data references for college English teaching reform.展开更多
With the increasingly prominent trend of globalization,English,as the common language of international communication,plays an increasingly important role in university education.As a key link in English teaching,the c...With the increasingly prominent trend of globalization,English,as the common language of international communication,plays an increasingly important role in university education.As a key link in English teaching,the college English audio-visual oral course not only imparts language knowledge and skills,but also shoulders the important task of cultivating students’critical thinking.As one of the essential core qualities of modern talents,critical thinking ability plays an irreplaceable role in students’in-depth understanding of English knowledge,improving intercultural communication ability and cultivating innovative thinking.This paper expounds the significance of cultivating students’critical thinking ability in college English audio-visual and oral teaching,and puts forward a series of innovative teaching strategies to cultivate students’critical thinking ability combined with practical teaching experience and cutting-edge education theory,in order to provide new ideas and practical guidance for the improvement of college English teaching quality and the development of students’comprehensive quality.展开更多
This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers f...This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.展开更多
As new-generation intelligent technologies rapidly evolve,enhancing artificial intelligence(AI)education has become a global consensus,and improving AI literacy is a key focus in higher education.To address the lack o...As new-generation intelligent technologies rapidly evolve,enhancing artificial intelligence(AI)education has become a global consensus,and improving AI literacy is a key focus in higher education.To address the lack of relevant knowledge among non-computer science students,the complexity of the material,which leads to low interest and high difficulty in learning,this paper proposes a three-pronged teaching design model:“BOPPPS model+large language models(LLMs)+mind maps with 3w2h”.This model aims to assist teachers in designing practical teaching cases and engaging,interactive activities,and provides examples of its application to help teachers better teach AI and improve the AI literacy of non-computer science students.展开更多
Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or ...Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or obtaining entity related external knowledge from knowledge bases or Large Language Models(LLMs).However,these approaches ignore the poor semantic correlation between visual and textual modalities in MNER datasets and do not explore different multi-modal fusion approaches.In this paper,we present MMAVK,a multi-modal named entity recognition model with auxiliary visual knowledge and word-level fusion,which aims to leverage the Multi-modal Large Language Model(MLLM)as an implicit knowledge base.It also extracts vision-based auxiliary knowledge from the image formore accurate and effective recognition.Specifically,we propose vision-based auxiliary knowledge generation,which guides the MLLM to extract external knowledge exclusively derived from images to aid entity recognition by designing target-specific prompts,thus avoiding redundant recognition and cognitive confusion caused by the simultaneous processing of image-text pairs.Furthermore,we employ a word-level multi-modal fusion mechanism to fuse the extracted external knowledge with each word-embedding embedded from the transformerbased encoder.Extensive experimental results demonstrate that MMAVK outperforms or equals the state-of-the-art methods on the two classical MNER datasets,even when the largemodels employed have significantly fewer parameters than other baselines.展开更多
Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and ...Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.展开更多
Based on the study of the Mechanical Design and Automation major and its relevance to teaching reform in higher education engineering programs,a project-based teaching model was introduced.This approach integrates tea...Based on the study of the Mechanical Design and Automation major and its relevance to teaching reform in higher education engineering programs,a project-based teaching model was introduced.This approach integrates teaching design,scheme argumentation,and the implementation of teaching activities with the project serving as the central framework.Course knowledge points are derived from the project topics,forming the foundation for a structured knowledge framework.The course content is modularized in alignment with the project design,enabling students to engage with professional courses on a module-by-module basis,guided by the project.Each course utilizes the project topic as a practical case,facilitating project-led teaching.A teaching system tailored to the research project is proposed,establishing a professional course structure closely linked to the project objectives.展开更多
基金supported by the Autonomous Region Industry-Education Integration Project“Application of DNA Methylation Combined with Spiral CT in the Screening of Pulmonary Ground-Glass Nodules and AI Recognition Systems in Teaching Practice”(Project No.2023210016)the“Open Project of the State Key Laboratory of High Incidence Diseases in Central Asia”(Project No.SKL-HIDCA-2021-28).
文摘Objective:To explore the effectiveness of multi-modal teaching based on an online case library in the education of gene methylation combined with spiral computed tomography(CT)screening for pulmonary ground-glass opacity(GGO)nodules.Methods:From October 2023 to April 2024,66 medical imaging students were selected and randomly divided into a control group and an observation group,each with 33 students.The control group received traditional lecture-based teaching,while the observation group was taught using a multi-modal teaching approach based on an online case library.Performance on assessments and teaching quality were analyzed between the two groups.Results:The observation group achieved higher scores in theoretical and practical knowledge compared to the control group(P<0.05).Additionally,the teaching quality scores were significantly higher in the observation group(P<0.05).Conclusion:Implementing multi-modal teaching based on an online case library for pulmonary GGO nodule screening with gene methylation combined with spiral CT can enhance students’knowledge acquisition,improve teaching quality,and have significant clinical application value.
基金Supported by Education and Teaching Reform and Research Project of Xi'an University of Science and Technology(JG14110)Cultivation Fund of Xi'an University of Science and Technology(201640)Science and Technology Innovation Team Fund of College of Architecture and Civil Engineering(17JGCXTD004)
文摘Taking the teaching practice of agricultural landscape planning for example,this paper uses the multi-modal teaching idea for teaching design based on traditional lecture-style teaching,including multi-modal teaching materials,multi-modal teaching methods and multi-modal teaching evaluation. The results show that this method can effectively improve students' interest in learning,reinforce the theoretical basis of agricultural landscape planning theory,and improve agricultural landscape planning practical skills. It is the active exploration of multi-modal teaching model and useful complement to traditional classroom teaching.
文摘Objective: to observe the application effect of multi-modal teaching method in clinical anesthesiology teaching. Methods: a total of 50 anesthesiology students who practiced in our hospital from September 2020 to August 2021 were selected for research. According to different teaching methods, 25 students in the control group received conventional teaching, and 25 students in the research group received multimodal teaching, comparing students' assessment results, learning excellence rate and teaching quality assessment results. Results: the examination scores of students in the study group in anesthesia preparation, tracheal intubation, general anesthesia and local anesthesia, and anesthesia evaluation were all higher than those in the control group (P<0.05). The teaching quality evaluation results of the research group were better than those of the control group (P<0.05);the student satisfaction rate of the research group was 100.0% higher than that of the control group (84.0%) (P<0.05). Conclusion: the application of multi-mode teaching method in clinical teaching can improve the operation level of anesthesiology students and improve their comprehensive quality. The teaching quality is good, which has been widely recognized by students.
文摘Listening is the breakthrough for conquering English castle, it is not only the requirement of English test, but also the practical use of English knowledge and the embodiment of English comprehensive ability. Listening teaching plays a crucial role in foreign language teaching. However, the effect of listening teaching is undesirable. In recent years, multi-modality theory has been focused by many researchers. In view of particularity of the listening teaching, it is urgent to apply the multi-modality theory to English listening teaching which will produce very good teaching result.
文摘Based on the teaching video of middle school English teachers, through observation and analysis, it puts forward the problem of less use, wrong use and abuse in the use of teachers' teaching gestures in middle school English teaching. And then it puts forward corresponding solutions from three aspects: concept, theory and practice. Hoping to provide further reference to the complementary role of teaching gesture and teaching discourse.
文摘With the rapid development of China's education, the citizens of the students' comprehensive quality and aesthetic ability requirements are also gradually improving. It is also an effective way to improve students' interest in music and educate students. Multi-modal music teaching can effectively improve classroom teaching efficiency and optimize students' classroom experience. Then how should teachers carry out the teaching of multi-modal music evaluation?
基金Construction Program of the Key Discipline of State Administration of Traditional Chinese Medicine of China(ZYYZDXK-2023069)Research Project of Shanghai Municipal Health Commission (2024QN018)Shanghai University of Traditional Chinese Medicine Science and Technology Development Program (23KFL005)。
文摘Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocardiographic data,traditional Chinese medicine(TCM)tongue manifestations,and facial features were collected from patients who underwent coro-nary computed tomography angiography(CTA)in the Cardiac Care Unit(CCU)of Shanghai Tenth People's Hospital between May 1,2023 and May 1,2024.An adaptive weighted multi-modal data fusion(AWMDF)model based on deep learning was constructed to predict the severity of coronary artery stenosis.The model was evaluated using metrics including accura-cy,precision,recall,F1 score,and the area under the receiver operating characteristic(ROC)curve(AUC).Further performance assessment was conducted through comparisons with six ensemble machine learning methods,data ablation,model component ablation,and various decision-level fusion strategies.Results A total of 158 patients were included in the study.The AWMDF model achieved ex-cellent predictive performance(AUC=0.973,accuracy=0.937,precision=0.937,recall=0.929,and F1 score=0.933).Compared with model ablation,data ablation experiments,and various traditional machine learning models,the AWMDF model demonstrated superior per-formance.Moreover,the adaptive weighting strategy outperformed alternative approaches,including simple weighting,averaging,voting,and fixed-weight schemes.Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.
文摘Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
基金The 2024 Guangdong University of Science and Technology Teaching,Science and Innovation Project(GKJXXZ2024028)。
文摘With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
基金2024 Anqing Normal University University-Level Key Project(ZK2024062D)。
文摘This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.
基金Shanghai Frontier Science Research Center for Modern Textiles,Donghua University,ChinaOpen Project of Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,China(No.IM202303)National Key Research and Development Program of China(No.2019YFB1706300)。
文摘A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.
基金Textile Light-Higher Education Teaching Reform Research Project of China Textile Industry Federation(2021BKJGLX362)China Higher Education Association 2023 Higher Education Scientific Research Planning Project“Vocational Education Service Regional Economic and Social Development Research”(23ZYJ0217)Liaoning Province Education Science“14th Five-Year Plan”Project“Research on the Correlation Between Higher Vocational Education and Intra-Regional Economy in Northeast China”(JGEB247)。
文摘The development of a new round of artificial intelligence(AI)science and technology provided good technical support and condition guarantee for college English teaching,but it also brought new challenges.It is necessary and inevitable for English teaching to experience reform and innovation.China’s AI digital teaching transformation is in the exploratory stage,and AI teaching mode has become the focus of future teaching development.Herein we propose a research method of integrating AI tools in college English teaching to adapt to the personalized learning of the new generation of college students,make the teaching process efficiently integrate the tide of the development of AI,promote the development of education evaluation system more accurately,and provide theoretical and data references for college English teaching reform.
基金A Study on the Teaching Reform of College English Audio-Visual Oral Course Oriented towards the Cultivation of Critical Thinking Ability(2501032339)。
文摘With the increasingly prominent trend of globalization,English,as the common language of international communication,plays an increasingly important role in university education.As a key link in English teaching,the college English audio-visual oral course not only imparts language knowledge and skills,but also shoulders the important task of cultivating students’critical thinking.As one of the essential core qualities of modern talents,critical thinking ability plays an irreplaceable role in students’in-depth understanding of English knowledge,improving intercultural communication ability and cultivating innovative thinking.This paper expounds the significance of cultivating students’critical thinking ability in college English audio-visual and oral teaching,and puts forward a series of innovative teaching strategies to cultivate students’critical thinking ability combined with practical teaching experience and cutting-edge education theory,in order to provide new ideas and practical guidance for the improvement of college English teaching quality and the development of students’comprehensive quality.
文摘This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.
文摘As new-generation intelligent technologies rapidly evolve,enhancing artificial intelligence(AI)education has become a global consensus,and improving AI literacy is a key focus in higher education.To address the lack of relevant knowledge among non-computer science students,the complexity of the material,which leads to low interest and high difficulty in learning,this paper proposes a three-pronged teaching design model:“BOPPPS model+large language models(LLMs)+mind maps with 3w2h”.This model aims to assist teachers in designing practical teaching cases and engaging,interactive activities,and provides examples of its application to help teachers better teach AI and improve the AI literacy of non-computer science students.
基金funded by Research Project,grant number BHQ090003000X03.
文摘Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or obtaining entity related external knowledge from knowledge bases or Large Language Models(LLMs).However,these approaches ignore the poor semantic correlation between visual and textual modalities in MNER datasets and do not explore different multi-modal fusion approaches.In this paper,we present MMAVK,a multi-modal named entity recognition model with auxiliary visual knowledge and word-level fusion,which aims to leverage the Multi-modal Large Language Model(MLLM)as an implicit knowledge base.It also extracts vision-based auxiliary knowledge from the image formore accurate and effective recognition.Specifically,we propose vision-based auxiliary knowledge generation,which guides the MLLM to extract external knowledge exclusively derived from images to aid entity recognition by designing target-specific prompts,thus avoiding redundant recognition and cognitive confusion caused by the simultaneous processing of image-text pairs.Furthermore,we employ a word-level multi-modal fusion mechanism to fuse the extracted external knowledge with each word-embedding embedded from the transformerbased encoder.Extensive experimental results demonstrate that MMAVK outperforms or equals the state-of-the-art methods on the two classical MNER datasets,even when the largemodels employed have significantly fewer parameters than other baselines.
基金funded by Research Project,grant number BHQ090003000X03。
文摘Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.
基金The 2023 Qingdao Institute of Technology Campus-Level Teaching and Research Project“Research on Project-Based Teaching Model for Engineering Majors in Colleges and Universities”(2023JY005)。
文摘Based on the study of the Mechanical Design and Automation major and its relevance to teaching reform in higher education engineering programs,a project-based teaching model was introduced.This approach integrates teaching design,scheme argumentation,and the implementation of teaching activities with the project serving as the central framework.Course knowledge points are derived from the project topics,forming the foundation for a structured knowledge framework.The course content is modularized in alignment with the project design,enabling students to engage with professional courses on a module-by-module basis,guided by the project.Each course utilizes the project topic as a practical case,facilitating project-led teaching.A teaching system tailored to the research project is proposed,establishing a professional course structure closely linked to the project objectives.
