Meta-SEE:Intelligent and Interactive Learning Framework for Software Engineering Education Based on Metaverse and Metacognition

With the rapid evolution of technology and the increasing complexity of software systems,there is a growing demand for effective educational approaches that empower learners to acquire and apply software engineering skills in practical contexts.This paper presents an intelligent and interactive learning(Meta-SEE)framework for software engineering education that combines the immersive capabilities of the metaverse with the cognitive processes of metacognition,to create an interactive and engaging learning environment.In the Meta-SEE framework,learners are immersed in a virtual world where they can collaboratively engage with concepts and practices of software engineering.Through the integration of metacognitive strategies,learners are empowered to monitor,regulate,and adapt their learning processes.By incorporating metacognition within the metaverse,learners gain a deeper understanding of their own thinking processes and become self-directed learners.In addition,MetaSEE has the potential to revolutionize software engineering education by offering a dynamic,immersive,and personalized learning experience.It allows learners to engage in realistic software development scenarios,explore complex systems,and collaborate with peers and instructors in virtual spaces.

How to Effectively Apply ChatGPT in Software Engineering Education?——A Perspective from Undergraduate Students

As a highly advanced conversational AI chatbot trained on extensive datasets,ChatGPT has garnered significant attention across various domains,including academia,industry,and education.In the field of education,existing studies primarily focus on 2 areas:Assessing the potential utility of ChatGPT in education by examining its capabilities and limitations;exploring the educational scenarios that could benefit from the integration of ChatGPT.In contrast to these studies,we conduct a user survey targeting undergraduate students specializing in Software Engineering,aiming to gain insights into their perceptions,challenges,and expectations regarding the utilization of ChatGPT.Based on the results of the survey,we provide valuable guidance on the effective incorporation of ChatGPT in the realm of software engineering education.

A New Model of Software Engineering Education and Exploration of Professional Curriculum Teaching

This paper focuses on the problems,opportunities,and challenges faced by software engineering education in the new era.We have studied the core ideas of the new model and reform,the specific measures implemented,and the challenges and solutions faced.The new model and reform must focus on cultivating practical abilities,introducing interdisciplinary knowledge,and strengthening innovation awareness and entrepreneurial spirit.The process of reform and innovation is carried out from the aspects of teaching methods,teaching means,and course performance evaluation in the teaching practice of software engineering courses.We adopt a method of“question guiding,simple and easy to understand,flexible and diverse,and emphasizing practical results”,optimizing the curriculum design,providing diverse learning opportunities,and establishing a platform for the industry-university-research cooperation.Our teaching philosophy is to adhere to the viewpoint of innovative teaching ideas,optimizing teaching methods and teaching means,and comprehensively improving the teaching quality and level of software engineering education.

The Practice and Method of Integrating Fine Traditional Culture into Data Structure Course Teaching

To capitalize on the primary role of major course teaching and to facilitate students’understanding of abstract concepts in the data structure course,it is essential to increase their interest in learning and develop case studies that highlight fine traditional culture.By incorporating these culture-rich case studies into classroom instruction,we employ a project-driven teaching approach.This not only allows students to master professional knowledge,but also enhances their abilities to solve specific engineering problems,ultimately fostering cultural confidence.Over the past few years,during which educational reforms have been conducted for trial runs,the feasibility and effectiveness of these reform schemes have been demonstrated.

Joint Monitoring of Ground and Sky for Cereal Crops Based on Scatterometer Measurement and ASAR Images

The joint monitoring of the ground and sky for cereal crops based on microwave data has become a popular method for researches on earth surface objects. Focused on the sensitivity of backscatter from the scatterometer measurement and advanced synthetic aperture radar (ASAR) images to cereal parameters of rice, nine acquisitions, including rice parameters related eco-physiological variables and scattering coefficients, have been carried over the paddy field corresponding to rice growth stages. This paper analyzes the relationship between the corresponding backscatter to the cereal parameters based on the measurement at the interesting bands, polarizations, and incidence angels. Further, a modified water cloud model is built based on the ground measurement and advanced integrated equation model (AIEM), and then cereal parameters from ASAR images are retrieved and verified. The research results show that the sensitivity of backscatter to cereals from the sensor of the radar scatterometer could be helpful to build the retrieve model for synthetic aperture radar (SAR) images, which can achieve the scientific goals of the joint monitoring of ground and sky for cereal crops.

Reform and Practice of Operating System Course

In recent years,with the changes in the international competitive environment,the development strategic focuses of the national software industry have also shifted.To adapt to these changes,we analyze and summarize the problems existing in the teaching content and methods of the traditional“Operating System”course and carry out the reform and practice of this core course for software engineering majors.First,we design and integrate domestic operating system examples into the course to meet the needs of national strategic development,thus cultivating operating system software talents in line with China’s national conditions and needs.Second,we reconstruct the teaching content of the course,strengthen the assessment of comprehensive ability,and establish a 3-level progressive teaching structure.Third,we carry out the deep integration of university and enterprise to realize the combination of theory and practice and establish a comprehensive and whole process university-enterprise course co-construction mode.Through the above reform measures,students show a strong interest in learning the operating system course.The operating system course has won the honor of the first-class course of Beijing Jiaotong University and has been approved for 4 industry-education cooperation projects of the Ministry of Education.

Self-Supervised Entity Alignment Based on Multi-Modal Contrastive Learning

Dear Editor,This letter proposes an unsupervised entity alignment method,which realizes integration of multiple multi-modal knowledge graphs adaptively.In recent years,Large-scale multi-modal knowledge graphs(LMKGs),containing text and image,have been widely applied in numerous knowledge-driven topics,such as question answering,entity linking,information extraction,reasoning and recommendation.

A New Talent Cultivation Model Under Open-source Environment:A Case Study at Zhejiang University

The open-source movement profoundly impacts the development of computer education.The current requirements for postgraduate cultivation in Chinese universities mainly include publishing papers,applying for patents,winning awards,and conducting research projects,which demonstrate the capabilities of students when they graduate from university.However,in today’s prevalent open-source culture,these types of assessments are still not comprehensive enough for postgraduate cultivation,especially for professional postgraduate degrees.For this reason,Zhejiang University takes the lead in proposing educational reforms for postgraduate cultivation based on the open-source ecosystem.It has implemented a new“trinity”mechanism(i.e.,open-source course,open-source training,and open-source capability evaluation)for graduate training centered on open source,serving as a novel supplement to the traditional methods of postgraduate cultivation.After a year of pilot operation,this new approach,deeply loved by teachers and students,has achieved good results and positive feedback.

A Multi-Objective Optimization Method of Initial Virtual Machine Fault-Tolerant Placement for Star Topological Data Centers of Cloud Systems

Virtualization is the most important technology in the unified resource layer of cloud computing systems.Static placement and dynamic management are two types of Virtual Machine(VM)management methods.VM dynamic management is based on the structure of the initial VM placement,and this initial structure will affect the efficiency of VM dynamic management.When a VM fails,cloud applications deployed on the faulty VM will crash if fault tolerance is not considered.In this study,a model of initial VM fault-tolerant placement for star topological data centers of cloud systems is built on the basis of multiple factors,including the service-level agreement violation rate,resource remaining rate,power consumption rate,failure rate,and fault tolerance cost.Then,a heuristic ant colony algorithm is proposed to solve the model.The service-providing VMs are placed by the ant colony algorithms,and the redundant VMs are placed by the conventional heuristic algorithms.The experimental results obtained from the simulation,real cluster,and fault injection experiments show that the proposed method can achieve better VM fault-tolerant placement solution than that of the traditional first fit or best fit descending method.

Automatic acquisition of pattern collocations in GO

The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of professsional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.

A survey on blockchain consensus mechanism: research overview, current advances and future directions

Purpose-As the core technology of blockchain,various consensus mechanisms have emerged to satisfy the demands of different application scenarios.Since determining the security,scalability and other related performance of the blockchain,how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.Design/methodology/approach-The paper opted for a research overview on the blockchain consensus mechanism,including the consensus mechanisms’consensus progress,classification and comparison,which are complemented by documentary analysis.Findings-This survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms.First,the authors outline the consensus processes,the advantages and disadvantages of the mainstream consensus mechanisms.Additionally,the consensus mechanisms are subdivided into four types according to their characteristics.Then,the consensus mechanisms are compared and analyzed based on four evaluation criteria.Finally,the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.Originality/value-This paper summarizes the future research development of the consensus mechanisms.

Survey on Lie Group Machine Learning

Lie group machine learning is recognized as the theoretical basis of brain intelligence,brain learning,higher machine learning,and higher artificial intelligence.Sample sets of Lie group matrices are widely available in practical applications.Lie group learning is a vibrant field of increasing importance and extraordinary potential and thus needs to be developed further.This study aims to provide a comprehensive survey on recent advances in Lie group machine learning.We introduce Lie group machine learning techniques in three major categories:supervised Lie group machine learning,semisupervised Lie group machine learning,and unsupervised Lie group machine learning.In addition,we introduce the special application of Lie group machine learning in image processing.This work covers the following techniques:Lie group machine learning model,Lie group subspace orbit generation learning,symplectic group learning,quantum group learning,Lie group fiber bundle learning,Lie group cover learning,Lie group deep structure learning,Lie group semisupervised learning,Lie group kernel learning,tensor learning,frame bundle connection learning,spectral estimation learning,Finsler geometric learning,homology boundary learning,category representation learning,and neuromorphic synergy learning.Overall,this survey aims to provide an insightful overview of state-of-the-art development in the field of Lie group machine learning.It will enable researchers to comprehensively understand the state of the field,identify the most appropriate tools for particular applications,and identify directions for future research.

Blockchain-enabled fog resource access and granting

Fog computing is a new computing paradigm for meeting ubiquitous massive access and latency-critical applications by moving the processing capability closer to end users.The geographical distribution/floating features with potential autonomy requirements introduce new challenges to the traditional methodology of network access control.In this paper,a blockchain-enabled fog resource access and granting solution is proposed to tackle the unique requirements brought by fog computing.The smart contract concept is introduced to enable dynamic,and automatic credential generation and delivery for an independent offer of fog resources.A per-transaction negotiation mechanism supports the fog resource provider to dynamically publish an offer and facilitates the choice of the preferred resource by the end user.Decentralized authentication and authorization relieve the processing pressure brought by massive access and single-point failure.Our solution can be extended and used in multi-access and especially multi-carrier scenarios in which centralized authorities are absent.