In a wide range of engineering applications,complex constrained multi-objective optimization problems(CMOPs)present significant challenges,as the complexity of constraints often hampers algorithmic convergence and red...In a wide range of engineering applications,complex constrained multi-objective optimization problems(CMOPs)present significant challenges,as the complexity of constraints often hampers algorithmic convergence and reduces population diversity.To address these challenges,we propose a novel algorithm named Constraint IntensityDriven Evolutionary Multitasking(CIDEMT),which employs a two-stage,tri-task framework to dynamically integrates problem structure and knowledge transfer.In the first stage,three cooperative tasks are designed to explore the Constrained Pareto Front(CPF),the Unconstrained Pareto Front(UPF),and theε-relaxed constraint boundary,respectively.A CPF-UPF relationship classifier is employed to construct a problem-type-aware evolutionary strategy pool.At the end of the first stage,each task selects strategies from this strategy pool based on the specific type of problem,thereby guiding the subsequent evolutionary process.In the second stage,while each task continues to evolve,aτ-driven knowledge transfer mechanism is introduced to selectively incorporate effective solutions across tasks.enhancing the convergence and feasibility of the main task.Extensive experiments conducted on 32 benchmark problems from three test suites(LIRCMOP,DASCMOP,and DOC)demonstrate that CIDEMT achieves the best Inverted Generational Distance(IGD)values on 24 problems and the best Hypervolume values(HV)on 22 problems.Furthermore,CIDEMT significantly outperforms six state-of-the-art constrained multi-objective evolutionary algorithms(CMOEAs).These results confirm CIDEMT’s superiority in promoting convergence,diversity,and robustness in solving complex CMOPs.展开更多
Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by ...Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.展开更多
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with...The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.展开更多
With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the pres...With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the present study explores the implications of integrating image-generative AI into Landscape Architecture courses from three perspectives: stimulating students creative design potential, expanding approaches to form and concept generation, and enhancing the visualization of spatial scenes. Furthermore, it discusses application strategies from three dimensions: AI-assisted conceptual generation, human-machine collaboration for design refinement, and optimization of scheme presentation and evaluation. This paper aims to provide relevant educators with insights and references.展开更多
With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instru...With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.展开更多
With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent ...With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.展开更多
Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specia...In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.展开更多
Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning sc...Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.展开更多
Tuberculosis(TB)remains one of the most persistent and formidable public health challenges globally.Despite the ambitious targets set by the World Health Organization End TB Strategy,the path to elimination is fraught...Tuberculosis(TB)remains one of the most persistent and formidable public health challenges globally.Despite the ambitious targets set by the World Health Organization End TB Strategy,the path to elimination is fraught with obstacles.According to the Global Tuberculosis Report 2025,while global incidence has been stabilization,the burden of multidrug-resistant tuberculosis(MDR-TB)and the long-term sequelae facing survivors continue to hinder progress[1].展开更多
Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This pap...Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.展开更多
The Guidelines for the Construction of Ideological and Political Education in Courses at Institutions of Higher Learning emphasizes that“the construction of ideological and political education in courses is an import...The Guidelines for the Construction of Ideological and Political Education in Courses at Institutions of Higher Learning emphasizes that“the construction of ideological and political education in courses is an important task for comprehensively improving the quality of talent cultivation”and“clarifying the target requirements and key content of the construction of ideological and political education in courses.”In vocational colleges,as an important discipline in the field of information technology,the construction of ideological and political education in software technology courses is of great significance for cultivating students’comprehensive qualities and establishing correct values.Based on sorting out the core literacy of the construction of ideological and political education in software technology courses,this article actively explores its construction path,hoping to provide references for relevant educators.展开更多
University courses should have both breadth and depth.However,most courses in universities only focus on the breadth construction,while neglecting the depth construction,resulting in students being unable to apply the...University courses should have both breadth and depth.However,most courses in universities only focus on the breadth construction,while neglecting the depth construction,resulting in students being unable to apply the knowledge they have learned to conduct research or solve real-world application problems.The students’high-level abilities are insufficient and not well-trained.Therefore,in this paper,we propose a T-structured course design method to ensure both breadth and depth of a course.The proposed T-structured course design method includes four aspects:T-structured course contents,T-structured teaching activities,T-structured examination formats,and T-structured homework difficulty.By applying our proposed T-structured course design strategy to the course Optimization Algorithms and Intelligent Computing,good results are achieved,demonstrating the applicability of our proposed strategy.展开更多
Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer a...Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer and inefficient evolutionary strategies become more severe as the number of iterations increases.Motivated by this,a novel self-adjusting dualmode evolutionary framework,which integrates variable classification evolution and knowledge dynamic transfer strategies,is designed to compensate for this deficiency.First,a dual-mode evolutionary framework is designed to meet the needs of evolution in different states.Then,a self-adjusting strategy based on spatial-temporal information is adopted to guide the selection of evolutionary modes.Second,a classification mechanism for decision variables is proposed to achieve the grouping of variables with different attributes.Then,the evolutionary algorithm with a multi-operator mechanism is employed to conduct classified evolution of decision variables.Third,an evolutionary strategy based on multi-source knowledge sharing is presented to realize the cross-domain transfer of knowledge.Then,a dynamic weighting strategy is developed for efficient utilization of knowledge.Finally,by conducting experiments and comparing the designed method with several existing algorithms,the empirical results confirm that it significantly outperforms its peers in tackling benchmark instances.展开更多
A“smart course”denotes a learner-centered curriculum model that deeply integrates advanced technologies,including generative artificial intelligence(AI)and big data analytics,with ongoing optimization and iterative ...A“smart course”denotes a learner-centered curriculum model that deeply integrates advanced technologies,including generative artificial intelligence(AI)and big data analytics,with ongoing optimization and iterative refinement.This paper examines the pathways of smart course development in higher vocational education by using the Study Tour Course Design course as a practical case study.The analysis is conducted from four perspectives:innovation in educational concepts,innovation in teaching models,transformation in learning paradigms,and enhancement in evaluation systems.By developing a threedimensional framework encompassing“knowledge,skills,and problems”,the focus of education shifts from“knowledge imparting”to“competency development”.This approach fosters a transformation in teaching interactions,moving beyond the traditional“teacher and student interaction”to a more integrated trinity collaboration of“teachers,students,and machines”,and promotes the transformation of students’learning from“passive receptive learning”to“autonomous inquiry-based learning”.Simultaneously,it facilitates the transition of evaluation methods from“outcome-based evaluation”to“multi-dimensional evaluation”.展开更多
This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessme...This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessment methods of core courses of the traffic engineering specialty.By introducing diversified assessment methods,focusing on process assessment,and strengthening the assessment of practical abilities,the aim is to improve students’learning enthusiasm and initiative,and cultivate students’innovation ability and practical ability to meet the needs of traffic engineering professionals in the new era.展开更多
In this paper,the necessity of constructing a golden course for Advanced Mathematics is presented.For teachers,golden courses enhance their teaching ability and job satisfaction.For students,golden courses improve the...In this paper,the necessity of constructing a golden course for Advanced Mathematics is presented.For teachers,golden courses enhance their teaching ability and job satisfaction.For students,golden courses improve their sense of learning value and significance and encourage them to actively learn and participate deeply.Next,the relevant content of course ideological and political construction is provided.Finally,a specific approach was proposed to create a golden course for Advanced Mathematics by integrating ideological and political education into the curriculum.展开更多
In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for...In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for ideological and political elements,and deeply explores ideological and political cases such as the Beidahuang spirit,Daqing spirit,model worker spirit,and role models around them.It explores the integration practice of“curriculum ideological and political”in extracurricular tutoring teaching of engineering graphics,aiming to guide students to establish patriotism,love for schools,knowledge of agriculture,and love for agriculture,and effectively enhance the coordinated development of students’graphic skills and ideological and political literacy.Practice has shown that integrating ideological and political resources,incorporating ideological and political elements into curriculum content and practical activities,can effectively enhance the collaborative development of students’graphic skills and ideological and political literacy.At the same time,it provides new ideas and references for expanding ideological and political education to extracurricular tutoring courses.展开更多
Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by ...Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61972040the Science and Technology Research and Development Project funded by China Railway Material Trade Group Luban Company.
文摘In a wide range of engineering applications,complex constrained multi-objective optimization problems(CMOPs)present significant challenges,as the complexity of constraints often hampers algorithmic convergence and reduces population diversity.To address these challenges,we propose a novel algorithm named Constraint IntensityDriven Evolutionary Multitasking(CIDEMT),which employs a two-stage,tri-task framework to dynamically integrates problem structure and knowledge transfer.In the first stage,three cooperative tasks are designed to explore the Constrained Pareto Front(CPF),the Unconstrained Pareto Front(UPF),and theε-relaxed constraint boundary,respectively.A CPF-UPF relationship classifier is employed to construct a problem-type-aware evolutionary strategy pool.At the end of the first stage,each task selects strategies from this strategy pool based on the specific type of problem,thereby guiding the subsequent evolutionary process.In the second stage,while each task continues to evolve,aτ-driven knowledge transfer mechanism is introduced to selectively incorporate effective solutions across tasks.enhancing the convergence and feasibility of the main task.Extensive experiments conducted on 32 benchmark problems from three test suites(LIRCMOP,DASCMOP,and DOC)demonstrate that CIDEMT achieves the best Inverted Generational Distance(IGD)values on 24 problems and the best Hypervolume values(HV)on 22 problems.Furthermore,CIDEMT significantly outperforms six state-of-the-art constrained multi-objective evolutionary algorithms(CMOEAs).These results confirm CIDEMT’s superiority in promoting convergence,diversity,and robustness in solving complex CMOPs.
文摘Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.
基金supported by the Chinese National Natural Science Foundation under Grant Nos.(41975181,42325503,42375197,42575207,42205090)Y.LIU is supported by the U.S.Department of Energy’s Atmospheric System Research(ASR)program.
文摘The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
基金Supported by Applied Brand Course of Mianyang Teacher's College(Investigation and Monitoring of Natural Resources).
文摘With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the present study explores the implications of integrating image-generative AI into Landscape Architecture courses from three perspectives: stimulating students creative design potential, expanding approaches to form and concept generation, and enhancing the visualization of spatial scenes. Furthermore, it discusses application strategies from three dimensions: AI-assisted conceptual generation, human-machine collaboration for design refinement, and optimization of scheme presentation and evaluation. This paper aims to provide relevant educators with insights and references.
基金supported by the Zhejiang Province Leading Geese Plan(Grant No.2025C02025)the Guangdong Province Primary and Secondary School Teachers’Digital Literacy Enhancement Project 2025(Grant No.GDSZSYKT2025244).
文摘With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.
基金Computer Basic Education Teaching Research Project of Association of Fundamental Computing Education in Chinese Universities(Nos.2025-AFCEC-527 and 2024-AFCEC-088)Research on the Reform of Public Course Teaching at Nantong College of Science and Technology(No.2024JGG015).
文摘With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
文摘In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant number:82171965.
文摘Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.
文摘Tuberculosis(TB)remains one of the most persistent and formidable public health challenges globally.Despite the ambitious targets set by the World Health Organization End TB Strategy,the path to elimination is fraught with obstacles.According to the Global Tuberculosis Report 2025,while global incidence has been stabilization,the burden of multidrug-resistant tuberculosis(MDR-TB)and the long-term sequelae facing survivors continue to hinder progress[1].
基金Supported by Scientific Research Fund Project of Yunnan Provincial Department of Education(2025J1950).
文摘Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.
文摘The Guidelines for the Construction of Ideological and Political Education in Courses at Institutions of Higher Learning emphasizes that“the construction of ideological and political education in courses is an important task for comprehensively improving the quality of talent cultivation”and“clarifying the target requirements and key content of the construction of ideological and political education in courses.”In vocational colleges,as an important discipline in the field of information technology,the construction of ideological and political education in software technology courses is of great significance for cultivating students’comprehensive qualities and establishing correct values.Based on sorting out the core literacy of the construction of ideological and political education in software technology courses,this article actively explores its construction path,hoping to provide references for relevant educators.
基金supported in part by the fund of 2023 Guangdong Province Science and Technology Innovation Strategy Special Project“Construction of Industrial Data and Intelligent Application Innovation Platform”(2023A011),2024 Shanwei New Generation Electronic Information Industry Talent Revitalization Plan,and the project“Research on the Impact and Countermeasures of Large Scale Charging Facility Access on Guangdong Power Grid Planning and Construction.”。
文摘University courses should have both breadth and depth.However,most courses in universities only focus on the breadth construction,while neglecting the depth construction,resulting in students being unable to apply the knowledge they have learned to conduct research or solve real-world application problems.The students’high-level abilities are insufficient and not well-trained.Therefore,in this paper,we propose a T-structured course design method to ensure both breadth and depth of a course.The proposed T-structured course design method includes four aspects:T-structured course contents,T-structured teaching activities,T-structured examination formats,and T-structured homework difficulty.By applying our proposed T-structured course design strategy to the course Optimization Algorithms and Intelligent Computing,good results are achieved,demonstrating the applicability of our proposed strategy.
基金supported in part by the Plan of Key Scientific Research Projects of Colleges and Universities in Henan Province(25A413005,24A120005)the National Science and Technology Major Project(2021ZD0112302)the National Natural Science Foundation of China(62222301,61890930-5,62021003).
文摘Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer and inefficient evolutionary strategies become more severe as the number of iterations increases.Motivated by this,a novel self-adjusting dualmode evolutionary framework,which integrates variable classification evolution and knowledge dynamic transfer strategies,is designed to compensate for this deficiency.First,a dual-mode evolutionary framework is designed to meet the needs of evolution in different states.Then,a self-adjusting strategy based on spatial-temporal information is adopted to guide the selection of evolutionary modes.Second,a classification mechanism for decision variables is proposed to achieve the grouping of variables with different attributes.Then,the evolutionary algorithm with a multi-operator mechanism is employed to conduct classified evolution of decision variables.Third,an evolutionary strategy based on multi-source knowledge sharing is presented to realize the cross-domain transfer of knowledge.Then,a dynamic weighting strategy is developed for efficient utilization of knowledge.Finally,by conducting experiments and comparing the designed method with several existing algorithms,the empirical results confirm that it significantly outperforms its peers in tackling benchmark instances.
基金Sponsored by Vocational Education Teaching Reform Research Project of Shandong Province“Research on Digital New-Form Curriculum Development Based on AI Knowledge Maps in the Context of Industry-Education Integration”(2023352)Vocational Education Teaching Reform Research Project of Shandong Province“Innovation and Practice in the Development Model of Vocational College Master Craftsman Studios under the Perspective of Industry-Education Integration”(2024375).
文摘A“smart course”denotes a learner-centered curriculum model that deeply integrates advanced technologies,including generative artificial intelligence(AI)and big data analytics,with ongoing optimization and iterative refinement.This paper examines the pathways of smart course development in higher vocational education by using the Study Tour Course Design course as a practical case study.The analysis is conducted from four perspectives:innovation in educational concepts,innovation in teaching models,transformation in learning paradigms,and enhancement in evaluation systems.By developing a threedimensional framework encompassing“knowledge,skills,and problems”,the focus of education shifts from“knowledge imparting”to“competency development”.This approach fosters a transformation in teaching interactions,moving beyond the traditional“teacher and student interaction”to a more integrated trinity collaboration of“teachers,students,and machines”,and promotes the transformation of students’learning from“passive receptive learning”to“autonomous inquiry-based learning”.Simultaneously,it facilitates the transition of evaluation methods from“outcome-based evaluation”to“multi-dimensional evaluation”.
基金Key Project of Educational Science of China Association for Transportation Education and Research(Class B)(JT2024ZD077)。
文摘This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessment methods of core courses of the traffic engineering specialty.By introducing diversified assessment methods,focusing on process assessment,and strengthening the assessment of practical abilities,the aim is to improve students’learning enthusiasm and initiative,and cultivate students’innovation ability and practical ability to meet the needs of traffic engineering professionals in the new era.
基金Project of Heilongjiang University of Finance and Economics(XJYB2024056)Project of Heilongjiang University of Finance and Economics(XJYB2024057)。
文摘In this paper,the necessity of constructing a golden course for Advanced Mathematics is presented.For teachers,golden courses enhance their teaching ability and job satisfaction.For students,golden courses improve their sense of learning value and significance and encourage them to actively learn and participate deeply.Next,the relevant content of course ideological and political construction is provided.Finally,a specific approach was proposed to create a golden course for Advanced Mathematics by integrating ideological and political education into the curriculum.
基金financed by Project of Heilongjiang Higher Education Society“Research on Graphics Curriculum Based on Innovation and Entrepreneurship Education under the Background of Digital Education”(23GJYB035)the 2024 Annual Planning Project of the“14th Five Year Plan”of Educational Science in Heilongjiang Province“Research and Exploration on Ideological and Political Teaching of‘Computer Graphics’Course under the Concept of OBE in New Engineering”(GJB1424113).
文摘In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for ideological and political elements,and deeply explores ideological and political cases such as the Beidahuang spirit,Daqing spirit,model worker spirit,and role models around them.It explores the integration practice of“curriculum ideological and political”in extracurricular tutoring teaching of engineering graphics,aiming to guide students to establish patriotism,love for schools,knowledge of agriculture,and love for agriculture,and effectively enhance the coordinated development of students’graphic skills and ideological and political literacy.Practice has shown that integrating ideological and political resources,incorporating ideological and political elements into curriculum content and practical activities,can effectively enhance the collaborative development of students’graphic skills and ideological and political literacy.At the same time,it provides new ideas and references for expanding ideological and political education to extracurricular tutoring courses.
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