Age-Driven Joint Sampling and Non-Slot Based Scheduling for Industrial Internet of Things

Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.

Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for Power Internet of Things

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

Blockchain-Based Message Authentication Scheme for Internet of Vehicles in an Edge Computing Environment

As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel efficiency.However,in the IoV system,there are always malicious vehicle nodes publishing false information.Therefore,it is essential to ensure the legitimacy of the source.In addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance bottlenecks.Most existing authentication schemes have the problem of low authentication efficiency in the scenario.To address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour Traffic.Here,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message authentication.In addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network attacks.In the simulation experiment,we compare our scheme with other existing works.Our scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Analysis of Mobile and Internet Network Coverage: Propagation of Electromagnetic Waves and Concept of Digital Divide in Burundi

Mobile and Internet network coverage plays an important role in digital transformation and the exploitation of new services. The evolution of mobile networks from the first generation (1G) to the 5th generation is still a long process. 2G networks have developed the messaging service, which complements the already operational voice service. 2G technology has rapidly progressed to the third generation (3G), incorporating multimedia data transmission techniques. It then progressed to fourth generation (4G) and LTE (Long Term Evolution), increasing the transmission speed to improve 3G. Currently, developed countries have already moved to 5G. In developing countries, including Burundi, a member of the East African Community (ECA) where more than 80% are connected to 2G technologies, 40% are connected to the 3G network and 25% to the 4G network and are not yet connected to the 5G network and then still a process. The objective of this article is to analyze the coverage of 2G, 3G and 4G networks in Burundi. This analysis will make it possible to identify possible deficits in order to reduce the digital divide between connected urban areas and remote rural areas. Furthermore, this analysis will draw the attention of decision-makers to the need to deploy networks and coverage to allow the population to access mobile and Internet services and thus enable the digitalization of the population. Finally, this article shows the level of coverage, the digital divide and an overview of the deployment of base stations (BTS) throughout the country to promote the transformation and digital inclusion of services.

Management and Construction of University Books and Materials Under the Background of the Internet

The rapid development and popularization of Internet technology has provided important support for the informatization reform of various industries.University books and materials have the characteristics of large quantities and difficult storage and management.Its digital storage and management platform construction can effectively realize the digital storage and real-time retrieval of books and materials,and help students and teachers to find and use books and materials more quickly.Especially in recent years,with the update of intelligent platforms and other technologies,the resource-sharing platform of university books and materials can realize more convenient book information retrieval without the limitation of time and space.This paper mainly explores the optimization path and platform construction scheme of university libraries and information management under the background of the Internet,hoping to provide some theoretical references for university library managers.

Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

The Internet of Vehicles(IoV)is a networking paradigm related to the intercommunication of vehicles using a network.In a dynamic network,one of the key challenges in IoV is traffic management under increasing vehicles to avoid congestion.Therefore,optimal path selection to route traffic between the origin and destination is vital.This research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network access.Firstly,this work proposed a novel use of the Ant Colony Optimization(ACO)algorithm and formulated the path planning optimization problem as an Integer Linear Program(ILP).This integrates the future estimation metric to predict the future arrivals of the vehicles,searching the optimal routes.Considering the mobile nature of IOV,fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal path.The model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective path.Thus,this work strongly supports its use in applications having stringent Quality of Service(QoS)requirements for the vehicles.

Are vulnerable farmers more easily influenced?Heterogeneous effects of Internet use on the adoption of integrated pest management

The Internet is believed to bring more technological dividends to vulnerable farmers during the green agriculture transformation.However,this is different from the theory of skill-biased technological change,which emphasizes that individuals with higher levels of human capital and more technological endowments benefit more.This study investigates the effects of Internet use on farmers'adoption of integrated pest management(IPM),theoretically and empirically,based on a dataset containing 1015 farmers in China's Shandong Province.By exploring the perspective of rational inattention,the reasons for the heterogeneity of the effects across farmers with different endowments,i.e.,education and land size,are analyzed.The potential endogeneity issues are addressed using the endogenous switching probit model.The results reveal that:(1)although Internet use significantly positively affects farmers'adoption of IPM,vulnerable farmers do not benefit more from it.Considerable selection bias leads to an overestimation of technological dividends for vulnerable farmers;(2)different sources of technology information lead to the difference in the degree of farmers'rational inattention toward Internet information,which plays a crucial role in the heterogeneous effect of Internet use;and(3)excessive dependence on strong-tie social network information sources entraps vulnerable farmers in information cocoons,hindering their ability to reap the benefits of Internet use fully.Therefore,it is essential to promote services geared towards elderly-oriented Internet agricultural technology information and encourage farmers with strong Internet utilization skills to share technology information with other farmers actively.

Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles

With the increasing popularity of artificial intelligence applications,machine learning is also playing an increasingly important role in the Internet of Things(IoT)and the Internet of Vehicles(IoV).As an essential part of the IoV,smart transportation relies heavily on information obtained from images.However,inclement weather,such as snowy weather,negatively impacts the process and can hinder the regular operation of imaging equipment and the acquisition of conventional image information.Not only that,but the snow also makes intelligent transportation systems make the wrong judgment of road conditions and the entire system of the Internet of Vehicles adverse.This paper describes the single image snowremoval task and the use of a vision transformer to generate adversarial networks.The residual structure is used in the algorithm,and the Transformer structure is used in the network structure of the generator in the generative adversarial networks,which improves the accuracy of the snow removal task.Moreover,the vision transformer has good scalability and versatility for larger models and has a more vital fitting ability than the previously popular convolutional neural networks.The Snow100K dataset is used for training,testing and comparison,and the peak signal-to-noise ratio and structural similarity are used as evaluation indicators.The experimental results show that the improved snow removal algorithm performs well and can obtain high-quality snow removal images.

Age-specific differences in the association between prediabetes and cardiovascular diseases in China:A national cross-sectional study

BACKGROUND Cardiovascular disease(CVD)is a leading cause of morbidity and mortality worldwide,the global burden of which is rising.It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults.To develop a focused screening plan and treatment for Chinese adults with prediabetes,it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008.A thorough evaluation was conducted.Individuals with prediabetes were categorized into two groups based on age.Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years.Random forest was established in both age groups.SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.RESULTS In total,6948 people were diagnosed with prediabetes in this study.In prediabetes,prevalences of CVD were 5(0.29%)in the younger group and 148(2.85%)in the older group.Overall,11.11%of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years.In the younger age group,the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle,whereas in the older age group,resident status was more closely linked.CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes.It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

Effect of internet multiple linkage mode-based extended care combined with in-hospital comfort care on colorectal cancer patients undergoing colostomy

BACKGROUND Patients with colorectal cancer may need postoperative nursing to improve prognosis,and conventional nursing is not effective.Clinical research is needed to explore nursing methods that can more effectively improve postoperative conditions on colorectal cancer patients undergoing colostomy.AIM To explore the effect of internet multiple linkage mode-based extended care combined with in-hospital comfort care on colorectal cancer patients undergoing colostomy.METHODS Data from 187 patients with colostomy treated in our hospital from May 2019 to March 2022 were collected and divided into three groups,A(n=62),B(n=62)and C(n=63),according to different intervention methods.Group A received internet multiple linkage mode-based extended care combined with in-hospital comfort care.Group B received internet multiple linkage mode-based extended care.Group C received usual care intervention.Complications were compared among the three groups.The stoma self-efficacy scale,Hamilton Anxiety Scale,RESULTS The complication rate of group A,B and C(16.13%,20.97%and 60.32%,respectively)was significantly different(all P<0.05).The incidence of complications in groups A and B was lower than that in group C,and there was no significant difference between groups A and B(P>0.05).After intervention,the scores of ostomy care,social contact,diet choice,confidence in maintaining vitality,confidence in self-care of ostomy,confidence in sexual life,confidence in sexual satisfaction and confidence in physical labor in the three groups were all higher than before intervention,and the scores of groups A and B were higher than those of group C,with statistical significance(P<0.05).The Hamilton Anxiety Scale and Hamilton Depression Scale scores of the three groups after intervention were lower than those before intervention.The scores of groups A and B were lower than those of group C,and the score of group A was lower than that of group B,all with statistical significance(all P<0.05).There was a statist-ically significant difference in cancer-induced fatigue among the three groups(P<0.05).After intervention,the scores of physical health,psychological health,social health and mental health of the three groups were lower than before the intervention.The scores of group A and B were lower than that of group C;and the score of group A was lower than that of group B,all with statistical significance(all P<0.05).CONCLUSION Internet multiple linkage mode-based extended care combined with in-hospital comfort care can effectively improve self-efficacy,bad mood,cancer-related fatigue and life quality of colorectal cancer patients undergoing colostomy.

The Relationship between Internet Addiction and Cyberbullying Perpetration: A Moderated Mediation Model of Moral Disengagement and Internet Literacy

Internet addiction and cyberbullying have emerged as significant global mental health concerns in recent years.Although previous studies have shown a close association between Internet addiction and cyberbullying,the underlying mechanisms connecting these two phenomena remain unclear.Therefore,this study aimed to reveal the mechanisms involved between Internet addiction and cyberbullying perpetration from the perspective of cognition function.This study recruited 976 Chinese youth through online survey,using the short version of Internet Addiction Test(s-IAT),Chinese Cyberbullying Intervention Project Questionnaire(C-CIPQ),Cyberbullying Moral Disengagement Scale(CMDS),and Internet Literacy Questionnaire(ILQ)to investigate the relationship between Internet addiction,moral disengagement,Internet literacy and cyberbullying perpetration.The keyfindings of this study were as follows:after controlling gender and age,(1)Internet addiction had a significant positive predictive effect on cyberbullying perpetration;(2)moral disengagement acted as a mediator between Internet addiction and cyberbullying perpetration;and(3)Internet literacy played a moderating role between moral disengagement and cyberbullying perpetration.In conclusion,there was a moderated mediating effect between Internet addiction and cyberbullying perpetration,contributing to a better understanding of the relationship between these two phenomena.

Non-linear relationship between age and subfoveal choroidal thickness in Chinese patients with proliferative diabetic retinopathy

BACKGROUND No study has investigated the change regularity between age and subfoveal choroidal thickness(SFCT)in proliferative diabetic retinopathy(PDR).AIM To investigate the relationship between the SFCT and age in Chinese patients with PDR.METHODS This was a cross-sectional retrospective study.The participants were hospitalized individuals with type 2 diabetes who underwent vitrectomy for PDR.Contralateral eyes that met the criteria were included in the study.All necessary laboratory tests were performed at the time of admission.Central macular thickness(CMT)and SFCT were two quantitative assessments made using enhanced depth imaging optical coherence tomography.CMT was measured automatically and SFCT was measured manually with digital calipers provided by the Heidelberg Eye Explorer software.RESULTS The final analysis included a total of 234 individuals with PDR.The average age was 55.60 years old±10.03 years old,and 57.69%of the population was male.Univariate analysis revealed a significant negative connection between age and SFCT in patients with PDR[β=-2.44,95%confidence interval(95%CI):-3.46 to-1.42;P<0.0001].In the fully adjusted model,the correlation between SFCT and age remained steady(β=-1.68,95%CI:-2.97 to-0.39;P=0.0117).Spline smoothing showed that the relationship between SFCT and age in patients with PDR was non-linear,with an inflection point at 54 years of age.CONCLUSION Our findings suggest that age is a key determinant of choroidal thickness.The non-linear link between SFCT and age in PDR patients should be taken into account.

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.

Communication-Efficient Decision-Making of Digital Twin Assisted Internet of Vehicles: A Hierarchical Multi-Agent Reinforcement Learning Approach

The connected autonomous vehicle is considered an effective way to improve transport safety and efficiency.To overcome the limited sensing and computing capabilities of individual vehicles,we design a digital twin assisted decision-making framework for Internet of Vehicles,by leveraging the integration of communication,sensing and computing.In this framework,the digital twin entities residing on edge can effectively communicate and cooperate with each other to plan sub-targets for their respective vehicles,while the vehicles only need to achieve the sub-targets by generating a sequence of atomic actions.Furthermore,we propose a hierarchical multiagent reinforcement learning approach to implement the framework,which can be trained in an end-to-end way.In the proposed approach,the communication interval of digital twin entities could adapt to timevarying environment.Extensive experiments on driving decision-making have been performed in traffic junction scenarios of different difficulties.The experimental results show that the proposed approach can largely improve collaboration efficiency while reducing communication overhead.

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.

Lightweight Storage Framework for Blockchain-Enabled Internet of Things Under Cloud Computing

Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the development of these applications,such as the issue with linearly growing storage capacity of blockchain systems.On the other hand,there is a lack of storage resources for sensor devices in IoT,and numerous sensor devices will generate massive data at ultra-high speed,which makes the storage problem of the IoT enabled by blockchain more prominent.There are various solutions to reduce the storage burden by modifying the blockchain’s storage policy,but most of them do not consider the willingness of peers.In attempt to make the blockchain more compatible with the IoT,this paper proposes a storage optimization scheme that revisits the system data storage problem from amore practically oriented standpoint.Peers will only store transactional data that they are directly involved in.In addition,a transaction verification model is developed to enable peers to undertake transaction verification with the aid of cloud computing,and an incentive mechanism is premised on the storage optimization scheme to assure data integrity.The results of the simulation experiments demonstrate the proposed scheme’s advantage in terms of storage and throughput.

Bowel preparation protocol for hospitalized patients ages 50 years or older:A randomized controlled trial

BACKGROUND The incidence and mortality rate of colorectal cancer progressively increase with age and become particularly prominent after the age of 50 years.Therefore,the population that is≥50 years in age requires long-term and regular colonoscopies.Uncomfortable bowel preparation is the main reason preventing patients from undergoing regular colonoscopies.The standard bowel preparation regimen of 4-L polyethylene glycol(PEG)is effective but poorly tolerated.AIM To investigate an effective and comfortable bowel preparation regimen for hospitalized patients≥50 years in age.METHODS Patients were randomly assigned to group 1(2-L PEG+30-mL lactulose+a lowresidue diet)or group 2(4-L PEG).Adequate bowel preparation was defined as a Boston bowel preparation scale(BBPS)score of≥6,with a score of≥2 for each segment.Non-inferiority was prespecified with a margin of 10%.Additionally,the degree of comfort was assessed based on the comfort questionnaire.RESULTS The proportion of patients with a BBPS score of≥6 in group 1 was not significantly different from that in group 2,as demonstrated by intention-to-treat(91.2%vs 91.0%,P=0.953)and per-protocol(91.8%vs 91.0%,P=0.802)analyses.Furthermore,in patients≥75 years in age,the proportion of BBPS scores of≥6 in group 1 was not significantly different from that in group 2(90.9%vs 97.0%,P=0.716).Group 1 had higher comfort scores(8.85±1.162 vs 7.59±1.735,P<0.001),longer sleep duration(6.86±1.204 h vs 5.80±1.730 h,P<0.001),and fewer awakenings(1.42±1.183 vs 2.04±1.835,P=0.026)than group 2.CONCLUSION For hospitalized patients≥50 years in age,the bowel preparation regimen comprising 2-L PEG+30-mL lactulose+a low-residue diet produced a cleanse that was as effective as the 4-L PEG regimen and even provided better comfort.