Exploration of the Construction and Path Selection of the Deep Integration Model of Industry-Education in Universities

Against the backdrop of continuous development in the field of education,universities are encouraged to innovate their talent cultivation systems and objectives.The deep integration of industry and education has emerged as an effective strategy,aligning with the basic requirements of the new engineering education initiative and exerting a positive impact on socioeconomic development.However,an analysis of the current state of industry-education integration in universities reveals several issues that require optimization,affecting the ultimate effectiveness of integration.To optimize this phenomenon and achieve high-quality development,universities need to further explore the construction of a deep integration model of industry and education,adhering to corresponding principles to form a comprehensive system.On this basis,pathways for deep industry-education integration can be summarized.

Exploration of Innovation Strategy in the Deep Integration of Information Technology and Education and Teaching

The rapid development of information technology provides a new opportunity and impetus for the reform of education and teaching.Deep integration of information technology and education and teaching is the only way to promote the modernization of education.Starting from the connotation of the deep integration of information technology and education and teaching,this paper analyzes the existing problems in the current integration process,and puts forward innovative strategies from the aspects of concept,resources,model,and evaluation.Through measures such as building a smart teaching environment,enriching high-quality teaching resources,innovating teaching organization models,and establishing multiple evaluation systems,we will realize the deep integration of information technology and teaching,promote the reform of teaching and learning methods,improve the quality of personnel training,and provide strong support for the modernization of education.

Research on the Deep Integration Mechanism of National Fitness Campaign and College Physical Education Teaching:Taking Guangdong University of Science and Technology as an Example

By using the methods of literature review,questionnaire survey,and expert interview,this paper discusses and analyzes the deep integration mechanism of national fitness campaign and college physical education teaching,in order to promote the development of college physical education teaching reform,expand ideas,explore new fields,and provide novel development directions.The purpose is to enhance the national physical quality,improve the public service system,enhance the health awareness of the citizens,and provide guidelines for promoting the development of sports.

Development Strategies for Z County E-sports Town in Chongqing:Integration of E-sports,Tourism,and Agriculture under New Policies

Chongqing Z County E-sports Town was once included in the“first batch of sports and leisure characteristic town pilot project list”issued by the General Administration of Sports of China.After several years of development,the e-sports industry in Z County e-sports town has struggled with issues such as a limited market,low popularity,poor business performance,and a lack of income generation capabilities.These challenges have severely hindered the town’s development,resulting in its exclusion from the recent“Chongqing characteristic town list.”Under the requirements of new policies,it can no longer promote itself,attract investment,or undertake project construction under the name of a“characteristic town”and must undergo redevelopment.This paper employs case analysis and comparative investigation methods to conduct an in-depth empirical study on the development of Z County E-sports Town.It is proposed that under the new policy environment,the town should foster the deep integration of its existing e-sports industry and culture with tourism and agriculture,transforming Z County E-sports Town into a new characteristic tourist destination.The findings of this paper offer a reference for the development of similar towns facing stagnation and provide case support for the construction of tourist destinations featuring e-sports.

Tasks-Oriented Joint Resource Allocation Scheme for the Internet of Vehicles with Sensing, Communication and Computing Integration

With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmission and the computing requirements of intelligent tasks lead to the complex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the scenario of Io V.First,this paper proposes a system model with sensing,communication,and computing integration for multiple intelligent tasks with different requirements in the Io V.Secondly,joint resource allocation problems for real-time tasks and delay-tolerant tasks in the Io V are constructed respectively,including communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization problems,and the convergence and complexity of the algorithm are discussed.Finally,the experimental results based on real data sets verify the performance advantages of the proposed resource allocation scheme,compared to the existing ones.The exploration efficiency of our proposed DDQN-based algorithm is improved by at least about 5%,and our proposed resource allocation scheme improves the m AP performance by about 0.15 under resource constraints.

Query Translation on the Fly in Deep Web Integration

To facilitate users to access the desired information, many researches have dedicated to the Deep Web （i.e. Web databases） integration. We focus on query translation which is an important part of the Deep Web integration. Our aim is to construct automatically a set of constraints mapping rules so that the system can translate the query from the integrated interface to the Web database interfaces based on them. We construct a concept hierarchy for the attributes of the query interfaces, especially, store the synonyms and the types （e.g. Number, Text, etc.） for every concept At the same time, we construct the data hierarchies for some concepts if necessary. Then we present an algorithm to generate the constraint mapping rules based on these hierarchies. The approach is suitable for the scalability of such application and can be extended easily from one domain to another for its domain independent feature. The results of experiment show its effectiveness and efficiency.

MUS Model:A Deep Learning-Based Architecture for IoT Intrusion Detection

In the face of the effective popularity of the Internet of Things(IoT),but the frequent occurrence of cybersecurity incidents,various cybersecurity protection means have been proposed and applied.Among them,Intrusion Detection System(IDS)has been proven to be stable and efficient.However,traditional intrusion detection methods have shortcomings such as lowdetection accuracy and inability to effectively identifymalicious attacks.To address the above problems,this paper fully considers the superiority of deep learning models in processing highdimensional data,and reasonable data type conversion methods can extract deep features and detect classification using advanced computer vision techniques to improve classification accuracy.TheMarkov TransformField(MTF)method is used to convert 1Dnetwork traffic data into 2D images,and then the converted 2D images are filtered by UnsharpMasking to enhance the image details by sharpening;to further improve the accuracy of data classification and detection,unlike using the existing high-performance baseline image classification models,a soft-voting integrated model,which integrates three deep learning models,MobileNet,VGGNet and ResNet,to finally obtain an effective IoT intrusion detection architecture:the MUS model.Four types of experiments are conducted on the publicly available intrusion detection dataset CICIDS2018 and the IoT network traffic dataset N_BaIoT,and the results demonstrate that the accuracy of attack traffic detection is greatly improved,which is not only applicable to the IoT intrusion detection environment,but also to different types of attacks and different network environments,which confirms the effectiveness of the work done.

Research on The Software Development Ability Training With Gradual and Whole Process Based on The Deep Integration Between Industry and Education

In view of the mechanism and quality problems in the software ability training of computer majors in colleges and universities,as well as the engineering ability and innovation ability training results can not effectively meet the needs of society,this paper discusses how to realize the deep integration of production and education through school enterprise cooperation under the existing training mode.Through the establishment of a progressive whole process training system,students’software ability can be improved in an all-round way.Taking Shenyang Aerospace University as an example,it expounds how to organically combine the theoretical teaching in class with the cultivation of extracurricular innovation ability,and gradually guide students to comprehensively improve their software development ability and innovation ability.The model has been running for many years,and plays a leading role in promoting the reform of education and teaching and improving the quality of education,and provides reference for the brotherly colleges and universities.

Xue Ling:Culture-Tourism Integration to Deepen China-UK People-to-People Ties

Xue Ling has been long engaged in international cultural and arts exchanges for decades.In February 2019,she assumed office as director of China National Tourist Office(CNTO),London,embarking on a new career to increase China-UK cultural exchanges and promote China's tourist resources.

Ontology-based schema matching method in web query interface integration

Deep web data integration needs to do schema matching on web query interfaces and obtain the mapping table.By introducing semantic conflicts into web query interface integration and discussing the origins and categories of the semantic conflicts,an ontology-based schema matching method is proposed.The process of the method is explained in detail using the example of web query interface integration in house domain.Conflicts can be detected automatically by checking semantic relevance degree,then the categories of the conflicts are identified and messages are sent to the conflict solver,which eliminates the conflicts and obtains the mapping table using conflict solving rules.The proposed method is simple,easy to implement and can be flexibly reused by extending the ontology to different domains.

Promoting the Deep Digital-Real Economy Integration:Theory and Practice

With the rapid development and widespread application of new-generation digital technologies,the digital economy is playing an increasingly important role in driving China's high-quality economic development.As economic growth drivers undergo transformation,studying how to promote the deep integration of the digital economy and the real economy(digital-real economy integration)holds significant strategic importance.In general,the digital-real economy integration of China has made impressive advancements,becoming an irreversible trend.Nonetheless,there persist challenges that necessitate attention,such as the imperative to strengthen underlying technology support and improve the quality of integration.By integrating specific application scenarios of digital technology with traditional enterprise theory,we can gain a comprehensive understanding of how the digital economy empowers innovation and development in traditional enterprises,thereby facilitating the exploration of practical paths for the deep digital-real economy integration.A thorough examination of the main forms and connotations of this deep integration allows us to analyze specific paths across three key dimensions:product layer,enterprise layer,and industry layer.By adopting this approach,a research framework that promotes the deep digital-real economy integration can be established.

Digital Twin for Integration of Design-Manufacturing-Maintenance:An Overview

Traditional design,manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost inefective manner.A unifed platform for efcient and intelligent designmanufacturing-maintenance of mechanical equipment and systems is highly needed in this rapidly digitized world.In this work,the defnition of digital twin and its research progress and associated challenges in the design,manufacturing and maintenance of engineering components and equipment were thoroughly reviewed.It is indicated that digital twin concept and associated technology provide a feasible solution for the integration of design-manufacturingmaintenance as it has behaved in the entire lifecycle of products.For this aim,a framework for information-physical combination,in which a more accurate design,a defect-free manufacturing,a more intelligent maintenance,and a more advanced sensing technology,is prospected.

Distributed optimization of electricity-Gas-Heat integrated energy system with multi-agent deep reinforcement learning

The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.

Research on the Deep Integration of Cultural and Tourism Development in the Construction of the Bashu Cultural and Tourism Corridor

The Bashu Cultural and Tourism Corridor is a region centered on Chongqing's main city and Chengdu,with the high-speed railways,expressways,and cities(counties)along the Yangtze River system connecting the two places as important components.Sichuan and Chongqing,guided by the"Bashu Cultural and Tourism Corridor Construction Plan,"have issued a series of policies and systems for the development of Bashu cultural tourism,vigorously promoting the construction of the Bashu Cultural and Tourism Corridor.However,in the process of promoting the construction of the Bashu Cultural and Tourism Corridor,there are also many challenges,such as insufficient integration of the cultural and tourism industry,outdated development models for cultural tourism,imperfect coordination mechanisms within the industry,a large gap in professional talents in the cultural and tourism industry,and inadequate exploration of characteristic cultural tourism resources.Among these,the insufficient integration of the cultural and tourism industry is particularly prominent,manifested in the disappearance of regional culture,a significant loss of talent,and low-quality development of the tourism industry.Cultural and tourism integration is a deep-level integration in the fields of concepts,functions,resources,industries,and technologies.This topic focuses on the issue of deep integration of cultural and tourism development in the construction of the Bashu Cultural and Tourism Corridor,which has important theoretical and practical significance.

Analysis of BIM application relationship with integration degree of construction environment

As the world pays more attention to low-earbon and sustainable development,there's a growing trend in architecture,engineering and construction fields to construct greener,more energy efficient and more sustainable buildings with the help of building information modeling(BIM).As BIM application becomes popular in industry,more and more scholars and engineers point out that an integrated construction environment is better for BIM's fully functional capability.This paper illustrates the relationship between BIM application and an integrated construction environment based on case survey data.It is found that even though an integration construction environment is not necessary in BIM application,the statistical results showed that DBB(design-bid-build)and CM(construction management)modes have great differences in BIM's application implementation scope and implementation deepness,while DB and CM modes do not.

Numerical Simulation of Installation Process and Uplift Resistance for An Integrated Suction Foundation in Deep Ocean

A concept design, named integrated suction foundation, is proposed for a tension leg platform（TLP） in deep ocean. The most important improvement in comparing with the traditional one is that a pressure-resistant storage module is designed. It utilizes the high hydrostatic pressure in deep ocean to drive water into the module to generate negative pressure for bucket suction. This work aims to further approve the feasibility of the concept design in the aspect of penetration installation and the uplift force in-place. Seepage is generated during suction penetration, and can have both positive and negative effects on penetration process. To study the effect of seepage on the penetration process of the integrated suction foundation, finite element analysis（FEA） is carried out in this work. In particular, an improved methodology to calculate the penetration resistance is proposed for the integrated suction foundation with respect to the reduction factor of penetration resistance. The maximum allowable negative pressure during suction penetration is calculated with the critical hydraulic gradient method through FEA. The simulation results of the penetration process show that the integrated suction foundation can be installed safely. Moreover, the uplift resistance of the integrated suction foundation is calculated and the feasibility of the integrated suction foundation working on-site is verified. In all, the analysis in this work further approves the feasibility of the integrated suction foundation for TLPs in deep ocean applications.

Device Physics Research for Submicron and Deep Submicron Space Microelectronics Devices and Integrated Circuits

Device physics research for submicron and deep submicron space microelectronics devices and integrated circuits will be described in three topics.1.Thin film submicron and deep submicron SOS / CMOS devices and integrated circuits.2.Deep submicron LDD CMOS devices and integrated circuits.3.C band and Ku band microwave GaAs MESFET and III-V compound hetrojunction HEM T and HBT devices and integrated circuits.

Intelligent Deep Learning Enabled Wild Forest Fire Detection System

The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfire detec-tion and alarming system using deep learning(IWFFDA-DL)model.The pro-posed IWFFDA-DL technique aims to identify forestfires at earlier stages through integrated sensors.The proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast thefire.Then,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of danger.For hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection performance.Finally,when thefire is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required actions.An extensive set of simulations were performed and the results are investigated interms of several aspects.The obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.

Towards Integrated Testing Approach: An Application of Cognitive Science and Deep Learning Principle

The use of multiple-choice(MC)question types has been one of the most contentious issues in language testing.Much has been said and written about the use of MC over the years.However,no attempt has ever been made to introduce any innovation in test item types.The researchers proposed a jumbled words test item(JW)based on cognitive science and deep learning principles,and addressed the feasibility of replacing the type of multiple-choice(MC)question with JW to meet the ongoing rapid development of language testing practice.Two research questions were proposed ad hoc,focusing on the co-relationship between JW and MC scores.RASCH-GZ was used to perform item analyses(Rasch,1960).The item difficulty parameters thus obtained were used to compare the two different test items.The sample data metric includes 40 Chinese participants.The findings revealed that correlation analysis revealed that the performance of the same group of subjects taking both JW and MC was not relevant(Pearson Corr=0).This is primarily due to the total elimination of guessing factors inherent in test-takers during JW test performance.Three factors were specified for the design of the JW test:compute program,test difficulty,and score acceptability.These all have three dimensions.Data collected through questionnaires were analyzed using EFA in SPSS V.24.0.KMOs(=0.867)were found to be approximately one and significance at 0.000(0.05),indicating that the construct of theuestionnaire thus designed has better validity for factor analysis.Three important conclusions were obtained,the implications of which could provide impetus for our testing counterparts to practice more precisely and correctly,potentially reshaping our overall language testing practice.Limitations and recommendations for future research were also discussed.

数字赋能文旅深度融合的理论逻辑与研究框架

数字赋能文旅深度融合既是数字经济时代文旅发展的重要方式,又是文旅研究的重要课题。文章在阐述文旅深度融合内涵的基础上,探究了数字赋能文旅深度融合的基本逻辑,认为数字技术嵌入支撑文旅数字化,促进文旅信息融合化,带来文旅产业新变革,形成文旅共生体和数字文旅新形态。从理论研究、数字赋能和融合实践3个维度,初步构建了数字赋能文旅深度融合的研究框架,强调要创新性地运用文旅IP理论、融合共生理论、文旅场景理论、产业演化理论、系统动力学等理论,阐释文旅融合学理及其内在逻辑、演化过程和动力机制,深化文旅深度融合主要科学问题研究。文章提出要把握数字赋能文旅融合的关键技术、文旅资源普查与评价、文旅融合场景建构、文旅产业融合创新生态体系、国家文化公园与文旅融合示范区建设、科技创新与数字文旅人才培养等关键问题,推动文旅融合应用实践和学术研究持续创新,更好地服务于新时代中国式现代化建设和文旅高质量发展。