Teaching Strategy of Higher Vocational Interior Design Based on “Internet Plus” Thinking

“Internet Plus”thinking has been widely adopted in the teaching of interior design in colleges and universities,and its application has significant implications that cannot be disregarded.“Internet Plus”thinking not only realizes the innovation of interior design teaching but also significantly improves the level and quality of teaching.Through an analysis of the advantages of“Internet Plus”education platform and the current situation of higher vocational interior design teaching,effective strategies for higher vocational interior design teaching based on“Internet Plus”thinking are proposed in this paper in hope that this study will contribute to the efficient development of interior design teaching activities.

Study on Problems and Countermeasures of English Hidden Curriculum Construction in Higher Vocational Colleges in the Era of “Internet Plus”

As the extension and supplement of explicit curriculum,the English hidden curriculum in higher vocational colleges plays animportant role in cultivating students' behaviors,stimulate their interest and arouse their enthusiasm,initiative and creativity in learningEnglish.This paper analyzes the problems of English hidden curriculum construction in higher vocational colleges under the back-ground o"fInternet plus",and puts forward some corresponding countermeasures to bring the role of college English hidden curriculuminto full play.

On Construction of English Teaching Resources in Higher Vocational Colleges in the Era of “Internet Plus” from the Perspective of Ecopedagogy

In the era of"Internet Plus",emphasis has been placed on construction of teaching resources by utilizing internet platform andtechnologies.It is of great significance to discuss the construction of English teaching resources in higher vocational colleges from theperspective of ecopedagogy which is characterized by openness and diversity.We can achieve high efficiency and effectiveness in con-structing English teaching resources for higher vocational college students through abiding by following principles such as diversity,de-velopment,adaptation and openness.

How to Promote the New Energy Vehicles under China’s “Internet plus” Initiative: A Review

Under the background of the rapid development of the Internet, new energy vehicles (NEVs) have ushered in an excellent development opportunity. With the subsidy policy exiting, new energy vehicles are facing unprecedented challenges. One purpose of stimulating the NEVs through “Internet plus” initiative is to promote diversification of vehicle energy systems and advance industrial upgrading and transformation. On the premise of “Internet plus”, the paper analyses the obstacles and opportunities of new energy vehicles from four aspects, and proposes a promoting development model which includes management mode and profit mode, and constructs a promoting development framework which is about three stages of new energy vehicles. Finally, from the perspective of the new energy vehicle charging, the paper puts forward some policy advice to promote industrialization and popularization of new energy vehicles in China.

Price Discrimination of Film Products and Building of Hierarchical Market under the Background of “Internet Plus”

Price Discrimination of film products is theoretically feasible and logically inevitable, and it has been used for a long time in film industry as well. However, there are practical paradoxes in the new environment due to market factors like popularization of Internet environment and Online to Offline(O2O) retailers between hierarchical markets. Compared with high-level markets, low-level markets are lack of conditions for differentiated lower price like cinema infrastructure, and environment for film consumption market, so that the consumption potential for market has not been motivated yet. Therefore, it is quite important to pay close attention to how to expand the market by clearer gradient pricing structures and Internet platform.

The design of intelligent monitoring and control system of the mechanical equipment base on “Internet plus”

each heavy machinery equipment for the end of the system, each end of the installation of a GSM data collector, complete the collection of the operating parameters of the equipment, the establishment of basic conditions for the exchange of things. According to the data server address the preset timing, collector through the GPRS network or Internet wireless network data transmission, data transmission acquisition collection to the cloud, the cloud to complete the function of data identification, error correction, classification, management and analysis of the data management system based on the transmitted data, so as to realize the management of large data.

Reflections on the Dilemma and Solutions of College Students’ Innovation and Entrepreneurship Education under the Background of “Internet Plus”

Appropriate innovation and Entrepreneurship Education in the university can effectivelypromote the reform of teaching mode and improve the quality of personnel training. With the emergence of the “InternetPlus”, it is inevitable to integrate the Internet and innovation educationorganically. In this paper, on the basis of the existing literature and data review as well as the field researches in some universities, the author sorted out the plight of the present situation of College Students’ innovation and Entrepreneurship Education under the background of the “InternetPlus”, expounded the function and significance of innovation and entrepreneurship education, and puttedforward some suggestions to the construction of universities’ innovation and entrepreneurship education system, to promote students’ overall growh and social progress.

Research on the Current Situation and Strategy of“Internet Plus”Online Chinese Education

The era of Industry 4.0 brings about qualitative changes to the economy and society as well as poses new challenges to Chinese education,personnel training,and future development.It is the responsibility of Chinese educational institutions,researchers,government departments,and enterprises to adapt to the changes in science and technology,the market,and the society;to meet the needs of teachers,parents,and students;to understand the current situation of online Chinese education;to connect with the outside world;and ultimately to create a connection with a broader ecosystem of Chinese education to meet the learning needs of Chinese learners around the world.

The Education Reform of Business Students Under the“Internet Plus”Business Model Transformation Trend

The“Internet Plus”business model calls for the optimization of business education in higher education institutes.The fast pace of“Internet Plus”requires business students to have abundant interdisciplinary knowledge,comprehensive modern business skills,habits of lifelong self-learning,and the courage to innovate.This paper proposes that higher education institutes should improve their business education programs in the following ways:firstly,form teaching alliances to provide interdisciplinary learning opportunities for business students;secondly,establish a social practice tutor team from excellent alumni;thirdly,build an online education platform for alumni to develop lifelong autonomous learning habits;finally,explore the three-tutor training model for business students.

The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

A credibility-aware swarm-federated deep learning framework in internet of vehicles

Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead and data privacy risks.The recently proposed Swarm Learning(SL)provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination.A Swarm-Federated Deep Learning framework in the IoV system(IoV-SFDL)that integrates SL into the FDL framework is proposed in this paper.The IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL,then aggregates the global FDL model among different SL groups with a credibility weights prediction algorithm.Extensive experimental results show that compared with the baseline frameworks,the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%,while the model performance improves by about 5.02%for the same training iterations.

A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

Malicious attacks against data are unavoidable in the interconnected,open and shared Energy Internet(EI),Intrusion tolerant techniques are critical to the data security of EI.Existing intrusion tolerant techniques suffered from problems such as low adaptability,policy lag,and difficulty in determining the degree of tolerance.To address these issues,we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas:(1)it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights;and (2)it combines a tournament competition model with incentive weights to obtain optimal strategies for each stage of the game process.Extensive experiments are conducted in the IEEE 39-bus system,whose results demonstrate the feasibility of the incentive weights,confirm the proposed strategy strengthens the system’s ability to tolerate aggression,and improves the dynamic adaptability and response efficiency of the aggression-tolerant system in the case of limited resources.

Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

Analysis of the Current Situation of“Internet Plus Nursing Service”

In the era of“Internet Plus,”technologies like big data,the Internet of Things,and cloud computing have revitalized nursing services in China,leading to the emergence of the“Internet Plus Nursing Services”model.This model facilitates on-site nursing care for discharged patients and special groups with mobility challenges,further advancing the construction of a Healthy China and enabling more people to access high-quality and continuous nursing services.Governments at all levels should actively improve the systems related to“Internet Plus Nursing Services”and simplify the appointment and operation processes.It is also essential to standardize the medical waste disposal process to ensure the quality of on-site nursing services,protect the legitimate rights and interests of both caregivers and patients and safeguard patient privacy and security.Additionally,building a robust“Internet Plus”platform to promote“online appointment of nurses”services,integrate nursing resources,and foster the healthy development of“Internet Plus Nursing Services”is crucial.

ResNeSt-biGRU: An Intrusion Detection Model Based on Internet of Things

The rapid expansion of Internet of Things (IoT) devices across various sectors is driven by steadily increasingdemands for interconnected and smart technologies. Nevertheless, the surge in the number of IoT device hascaught the attention of cyber hackers, as it provides them with expanded avenues to access valuable data. Thishas resulted in a myriad of security challenges, including information leakage, malware propagation, and financialloss, among others. Consequently, developing an intrusion detection system to identify both active and potentialintrusion traffic in IoT networks is of paramount importance. In this paper, we propose ResNeSt-biGRU, a practicalintrusion detection model that combines the strengths of ResNeSt, a variant of Residual Neural Network, andbidirectionalGated RecurrentUnitNetwork (biGRU).Our ResNeSt-biGRUframework diverges fromconventionalintrusion detection systems (IDS) by employing this dual-layeredmechanism that exploits the temporal continuityand spatial feature within network data streams, a methodological innovation that enhances detection accuracy.In conjunction with this, we introduce the PreIoT dataset, a compilation of prevalent IoT network behaviors, totrain and evaluate IDSmodels with a focus on identifying potential intrusion traffics. The effectiveness of proposedscheme is demonstrated through testing, wherein it achieved an average accuracy of 99.90% on theN-BaIoT datasetas well as on the PreIoT dataset and 94.45% on UNSW-NB15 dataset. The outcomes of this research reveal thepotential of ResNeSt-biGRU to bolster security measures, diminish intrusion-related vulnerabilities, and preservethe overall security of IoT ecosystems.

Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)technology.The functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic regularity.Despite these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle immobilization.This paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly detection.IDS-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by cyber-attacks.These systems can autonomously create specific models based on network data to differentiate between regular traffic and cyber-attacks.Among these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational complexity.We evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and stability.This review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV systems.By examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

Securing the Internet of Health Things with Certificateless Anonymous Authentication Scheme

Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible to cybersecurity threats due to its reliance on low-power biomedical devices and the use of open wireless channels for communication.In this article,we intend to address this shortcoming,and as a result,we propose a new scheme called,the certificateless anonymous authentication(CAA)scheme.The proposed scheme is based on hyperelliptic curve cryptography(HECC),an enhanced variant of elliptic curve cryptography(ECC)that employs a smaller key size of 80 bits as compared to 160 bits.The proposed scheme is secure against various attacks in both formal and informal security analyses.The formal study makes use of the Real-or-Random(ROR)model.A thorough comparative study of the proposed scheme is conducted for the security and efficiency of the proposed scheme with the relevant existing schemes.The results demonstrate that the proposed scheme not only ensures high security for health-related data but also increases efficiency.The proposed scheme’s computation cost is 2.88 ms,and the communication cost is 1440 bits,which shows its better efficiency compared to its counterpart schemes.

Call for Papers——Feature Topic Vol.22,No.2,2025 Efficient Cooperative Transmission over Satellite Internet for 6G

Satellite Internet,as a strategic public information infrastructure,can effectively bridge the limitations of traditional terrestrial network coverage,support global coverage and deep space exploration,and greatly enhance the range of network information services accessible to humans.With the transition of terrestrial mobile communication networks from the 5G era,which provides access to information anywhere,to the 6G era,which seeks to connect everything,the construction of satellite Internet,which promises a"network reaching everywhere and service is ubiquitous",has become the consensus of the industry's development and the focus of global scientific and technological innovation.

Intelligent Internet of Things with Reliable Communication and Collaboration Technologies

The Internet of Things(IoT)connects objects to Internet through sensor devices,radio frequency identification devices and other information collection and processing devices to realize information interaction.IoT is widely used in many fields,including intelligent transportation,intelligent healthcare,intelligent home and industry.In these fields,IoT devices connected via high-speed internet for efficient and reliable communications and faster response times.

Assessing the effectiveness of internetbased interventions for mental health outcomes:an umbrella review

Internet-based interventions(IBIs)for behavioural health have been prevalent for over two decades,and a growing proportion of individuals with mental health concerns prefer these emerging digital alternatives.However,the effectiveness and acceptability of IBIs for various mental health disorders continue to be subject to scholarly debate.We performed an umbrella review of meta-analyses(MAs),conducting literature searches in PubMed,Web of Science,Embase,Cochrane and Ovid Medline from their inception to 17 January 2023.A total of 87MAs,reporting on 1683 randomised controlled trials and 295589 patients,were included.The results indicated that IBIs had a moderate effect on anxiety disorder(standardised mean difference(SMD)=0.53,95%CI 0.44 to 0.62)and post-traumatic stress disorder(PTSD)(SMD=0.63,95%CI 0.38 to 0.89).In contrast,the efficacy on depression(SMD=0.45,95%CI 0.39 to 0.52),addiction(SMD=0.23,95%CI 0.16 to 0.31),suicidal ideation(SMD=0.23,95%CI 0.16 to 0.30),stress(SMD=0.41,95%CI 0.33 to 0.48)and obsessive-compulsive disorder(SMD=0.47,95%CI 0.22 to 0.73)was relatively small.However,no significant effects were observed for personality disorders(SMD=0.07,95%CI-0.13 to 0.26).Our findings suggest a significant association between IBIs and improved mental health outcomes,with particular effectiveness noted in treating anxiety disorders and PTSD.However,it is noteworthy that the effectiveness of IBIs was impacted by high dropout rates during treatment.Furthermore,our results indicated that guided IBIs proved to be more effective than unguided ones,playing a positive role in reducing dropout rates and enhancing patient adherence rates.