Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patient...Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patients with severe pneumonia and respiratory failure admitted from January 2024 to February 2025 were selected and randomly divided into two groups using a computer-based random drawing method.The control group(39 patients)received routine nursing,while the observation group(39 patients)received a time-sensitive incentive model combined with specialized rehabilitation nursing.Lung function and adverse emotional states were compared between the two groups.Results:After 2 weeks of nursing,the lung function of the observation group was higher than that of the control group(P<0.05),and the adverse emotional states of the observation group were lower than those of the control group(P<0.05).Conclusion:Implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure can improve lung function and emotional state.展开更多
As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artific...As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artificial Intelligence(AI)applications.However,most users are reluctant to disclose their data due to network bandwidth limitations,device energy consumption,and privacy requirements.To address this issue,this paper introduces an Edge-assisted Federated Learning(EFL)framework,along with an incentive mechanism for lightweight industrial data sharing.In order to reduce the information asymmetry between data owners and users,an EFL model-sharing incentive mechanism based on contract theory is designed.In addition,a weight dispersion evaluation scheme based on Wasserstein distance is proposed.This study models an optimization problem of node selection and sharing incentives to maximize the EFL model consumers'profit and ensure the quality of training services.An incentive-based EFL algorithm with individual rationality and incentive compatibility constraints is proposed.Finally,the experimental results verify the effectiveness of the proposed scheme in terms of positive incentives for contract design and performance analysis of EFL systems.展开更多
This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing pro...This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing problems.The incentive mechanism is constructed from multiple dimensions such as salary and career development,and optimized through the establishment of a scientific assessment and evaluation system,strengthening information construction,and creating a good cultural atmosphere.The aim is to improve the quality of higher education and cultivate outstanding talents.展开更多
With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-s...With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-sharing framework to ensure data security and encourage data owners to actively participate in sharing.We introduce a reliable attribute-based searchable encryption scheme that enables fine-grained access control of encrypted data and ensures secure and efficient data sharing.The revenue distribution model is constructed based on Shapley value to motivate participants.Additionally,by integrating the smart contract technology of blockchain,the search operation and incentive mechanism are automatically executed.Through revenue distribution analysis,the incentive effect and rationality of the proposed scheme are verified.Performance evaluation shows that,compared with traditional data-sharing models,our proposed framework not only meets data security requirements but also incentivizes more participants to actively participate in data sharing.展开更多
Overviewing the air pollution situation in Hong Kong,energy generation and transportation are part of the contribution to the carbon emissions.Electric vehicles do not have engines and no air pollutants emissions.The ...Overviewing the air pollution situation in Hong Kong,energy generation and transportation are part of the contribution to the carbon emissions.Electric vehicles do not have engines and no air pollutants emissions.The promotion of electric vehicles serves as an important strategy to Hong Kong's goal to achieve carbon neutrality by 2050.This paper illustrated the financial incentives the Hong Kong Government has launched,including First Registration Tax concessions,profits tax deduction,One-for-One Scheme,lower license fee,subsidy support for e-buses and e-taxis,free charging services at government car parks,EV-charging at home Subsidy Scheme,etc.By comparing the cost of purchasing and owning vehicles with the cost of purchasing and owning electric vehicles as well as the market performance of electric vehicles to examine whether the financial incentives in Hong Kong can promote electric vehicles and serve as a prerequisite to low carbon transition.The results show that under government support and promotion associated with preferential policy,electric vehicles will become the future trend in Hong Kong with the advantage of lower emissions,energy saving,and environmental protection.展开更多
The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in...The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.展开更多
This essay evaluates the behavioural dynamics generated by profit incentives and compares them with those in government-owned and charitable enterprises.Drawing on neoclassical microeconomics,agency theory,and institu...This essay evaluates the behavioural dynamics generated by profit incentives and compares them with those in government-owned and charitable enterprises.Drawing on neoclassical microeconomics,agency theory,and institutional economics,it shows how the profit motive drives cost minimization,allocative efficiency,innovation,and consumer responsiveness.Profit expectations,formalized in endogenous growth models,act as catalysts for technological progress and dynamic efficiency,while agency-theoretic governance mechanisms align managerial incentives with shareholder interests.In contrast,government-owned enterprises operate under multi-objective welfare functions,often constrained by soft budget expectations,political interference,and X-inefficiencies that dilute efficiency.Charitable organizations,structured by the non-distribution constraint,emphasize social trust,equity,and mission fulfilment,supported by warm-glow altruism but constrained by free-rider problems and underfunding.A comparative evaluation suggests that profit-driven firms outperform in competitive markets producing private goods,whereas government and charitable forms play essential roles in addressing market failures and providing public or credence goods.The analysis affirms the institutionalist principle that ownership and governance structures must be aligned with the nature of the goods or services delivered.展开更多
BACKGROUND Patients undergoing rectal cancer surgery frequently encounter challenges in their self-care abilities,disease knowledge,and emotional well-being postoperatively.Effective nursing interventions are critical...BACKGROUND Patients undergoing rectal cancer surgery frequently encounter challenges in their self-care abilities,disease knowledge,and emotional well-being postoperatively.Effective nursing interventions are critical for improving the quality of life and minimizing complications.This study explored the clinical implications of integrating health education guided by problem management with positive incentive nursing to address these challenges.AIM To evaluate the effect of this combined nursing model on postoperative self-care ability,disease knowledge,mood state,and complication rates in patients undergoing rectal cancer surgery.METHODS Eighty patients who underwent rectal cancer surgery between October 2021 and August 2024 were allocated into reference(routine care)and experimental(problem management-guided health education combined with positive incentive nursing)groups.The outcomes included exercise of self-care agency scale,disease knowledge(hospital-specific questionnaire),mood state(profile of mood states),and complication rates.RESULTS The experimental group demonstrated significant improvements in self-care ability(P<0.05),with higher scores for health knowledge,self-concept,self-care skills,and self-care responsibility than the reference group.Disease knowledge scores also improved markedly in the experimental group(P<0.05).Mood state scores showed a significant decrease in the negative dimensions(e.g.,anxiety and depression)and an increase in energy vitality(P<0.05).Additionally,the experimental group exhibited a lower complication rate than the reference group(7.5%vs 27.5%,P<0.05).CONCLUSION The integration of problem management-guided health education with positive incentive nursing significantly enhanced postoperative self-care abilities,disease knowledge,and emotional well-being while reducing complication rates.This model demonstrated potential for widespread adoption in clinical practice by offering a structured approach to improve patient outcomes and quality of life.展开更多
Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade...Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.展开更多
As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems rema...As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.展开更多
The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildi...The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.展开更多
Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various ...Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.展开更多
Time-Sensitive Network(TSN)with deterministic transmission capability is increasingly used in many emerging fields.It mainly guarantees the Quality of Service(QoS)of applications with strict requirements on time and s...Time-Sensitive Network(TSN)with deterministic transmission capability is increasingly used in many emerging fields.It mainly guarantees the Quality of Service(QoS)of applications with strict requirements on time and security.One of the core features of TSN is traffic scheduling with bounded low delay in the network.However,traffic scheduling schemes in TSN are usually synthesized offline and lack dynamism.To implement incremental scheduling of newly arrived traffic in TSN,we propose a Dynamic Response Incremental Scheduling(DR-IS)method for time-sensitive traffic and deploy it on a software-defined time-sensitive network architecture.Under the premise of meeting the traffic scheduling requirements,we adopt two modes,traffic shift and traffic exchange,to dynamically adjust the time slot injection position of the traffic in the original scheme,and determine the sending offset time of the new timesensitive traffic to minimize the global traffic transmission jitter.The evaluation results show that DRIS method can effectively control the large increase of traffic transmission jitter in incremental scheduling without affecting the transmission delay,thus realizing the dynamic incremental scheduling of time-sensitive traffic in TSN.展开更多
Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients m...Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.展开更多
The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promot...The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.展开更多
Background: While global efforts have led to a decline in maternal and neonatal mortality, Sub-Saharan Africa continues to face disproportionately high rates, remaining far above the Sustainable Development Goal (SDG)...Background: While global efforts have led to a decline in maternal and neonatal mortality, Sub-Saharan Africa continues to face disproportionately high rates, remaining far above the Sustainable Development Goal (SDG) targets. In Kenya, as the 2030 SDG deadline approaches, the gap in maternal, neonatal, and child health services remains significant. Addressing these challenges is critical to improving Maternal, Neonatal, and Child Health (MNCH) outcomes. Objective: This study explores how integration of digital health innovations into the MNCH chain of service delivery affects the quality of MNCH care within the selected PHC settings in Kajiado, Kisii and Migori Counties in Kenya. Methodology: This Quasi-experimental study was conducted 1-year post-intervention targeting a total of 482 pregnant women from intervention and control sites in Kisii, Kajiado and Migori Counties, Kenya. Data was analysed using Chi-Square test comparing frequencies between intervention and control groups when both variables are categorical. Results: Pre-intervention data revealed an increase in first ANC coverage within first trimester, from 167 to 278 post-intervention (p Linda mama social health insurance registrations increased from 1008 to 1135. At the intervention sites, 938 pregnant women got screened by midwives using portable mobile Obstetric Point-of-Care Ultrasound (OPOCUS) technology compared to the 27 cases that accessed ultrasound services in the noncontiguous control sites. The pilot sites midwives earned themselves an incentive income totaling Ksh 400,000 while the Community Health Promoters (CHPs) who created demand for OPOCUS earned an incentive income totaling Ksh 327,195 from their IGAs that were project supported. There was a significant increase in mobile health application usage and e-resources access for health information in the intervention group (p services and improved adherence to referrals. Conclusion: The success of digital health interventions in improving health-seeking behaviour, knowledge, and service uptake highlights the potential of such innovations to strengthen health systems and achieve universal health coverage. We recommend the intervention for a scale-up in other PHC settings in Kenya.展开更多
Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensa...Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.展开更多
With the increasing severity of urban traffic congestion and environmental pollution issues,Mobility-as-a-Service(MaaS)has garnered increasing attention as an emerging mode of transportation.Thus,how to motivate users...With the increasing severity of urban traffic congestion and environmental pollution issues,Mobility-as-a-Service(MaaS)has garnered increasing attention as an emerging mode of transportation.Thus,how to motivate users to participate in MaaS has become an important research issue.This study first classified the incentive policies into four aspects:financial incentive policy,non-financial incentive policy,information policy,and convenience policy.Then,through online questionnaires and field interviews,456 sets of data were collected in Beijing,and the data were analyzed by the structural equation model and latent class model.The results show that the four incentive policies are positively correlated with users'participation in MaaS,among which financial incentive policy and information policy have the greatest impact,that is,they can better encourage users by increasing direct financial subsidies and broadening the information about MaaS.In addition,Latent Class Analysis was performed to class different users and it was found that the personal characteristics of users had some influence on willingness to participate in MaaS.Therefore,incentive policies should be designed to consider the needs and characteristics of different user groups to improve their willingness to participate in MaaS.The results can provide theoretical suggestions for the government to promote the widespread application of MaaS in urban transportation.展开更多
With the rapid development of financial technology,middle managers in banks face both new challenges and opportunities.This paper conducts an in-depth analysis of the current state and issues surrounding the career de...With the rapid development of financial technology,middle managers in banks face both new challenges and opportunities.This paper conducts an in-depth analysis of the current state and issues surrounding the career development of middle managers in banks and explores effective incentive model designs and implementation strategies.Employing both quantitative and qualitative evaluation methods,the study assesses the practical impact of various incentive models.Through case analysis,targeted improvement suggestions are proposed.The findings reveal that a well-designed incentive mechanism significantly enhances middle managers’job satisfaction and loyalty,which is essential for the sustained growth of banks.展开更多
文摘Objective:To explore the effect of implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure.Methods:Seventy-eight patients with severe pneumonia and respiratory failure admitted from January 2024 to February 2025 were selected and randomly divided into two groups using a computer-based random drawing method.The control group(39 patients)received routine nursing,while the observation group(39 patients)received a time-sensitive incentive model combined with specialized rehabilitation nursing.Lung function and adverse emotional states were compared between the two groups.Results:After 2 weeks of nursing,the lung function of the observation group was higher than that of the control group(P<0.05),and the adverse emotional states of the observation group were lower than those of the control group(P<0.05).Conclusion:Implementing a time-sensitive incentive model combined with specialized rehabilitation nursing in patients with severe pneumonia and respiratory failure can improve lung function and emotional state.
基金supported by the National Natural Science Foundation of China (No.62071070)Major science and technology special project of Science and Technology Department of Yunnan Province (202002AB080001-8)BUPT innovation&entrepreneurship support program (2023-YC-T031)。
文摘As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artificial Intelligence(AI)applications.However,most users are reluctant to disclose their data due to network bandwidth limitations,device energy consumption,and privacy requirements.To address this issue,this paper introduces an Edge-assisted Federated Learning(EFL)framework,along with an incentive mechanism for lightweight industrial data sharing.In order to reduce the information asymmetry between data owners and users,an EFL model-sharing incentive mechanism based on contract theory is designed.In addition,a weight dispersion evaluation scheme based on Wasserstein distance is proposed.This study models an optimization problem of node selection and sharing incentives to maximize the EFL model consumers'profit and ensure the quality of training services.An incentive-based EFL algorithm with individual rationality and incentive compatibility constraints is proposed.Finally,the experimental results verify the effectiveness of the proposed scheme in terms of positive incentives for contract design and performance analysis of EFL systems.
文摘This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing problems.The incentive mechanism is constructed from multiple dimensions such as salary and career development,and optimized through the establishment of a scientific assessment and evaluation system,strengthening information construction,and creating a good cultural atmosphere.The aim is to improve the quality of higher education and cultivate outstanding talents.
基金supported by the Natural Science Foundation of Hebei Province of China(F2021201052).
文摘With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-sharing framework to ensure data security and encourage data owners to actively participate in sharing.We introduce a reliable attribute-based searchable encryption scheme that enables fine-grained access control of encrypted data and ensures secure and efficient data sharing.The revenue distribution model is constructed based on Shapley value to motivate participants.Additionally,by integrating the smart contract technology of blockchain,the search operation and incentive mechanism are automatically executed.Through revenue distribution analysis,the incentive effect and rationality of the proposed scheme are verified.Performance evaluation shows that,compared with traditional data-sharing models,our proposed framework not only meets data security requirements but also incentivizes more participants to actively participate in data sharing.
文摘Overviewing the air pollution situation in Hong Kong,energy generation and transportation are part of the contribution to the carbon emissions.Electric vehicles do not have engines and no air pollutants emissions.The promotion of electric vehicles serves as an important strategy to Hong Kong's goal to achieve carbon neutrality by 2050.This paper illustrated the financial incentives the Hong Kong Government has launched,including First Registration Tax concessions,profits tax deduction,One-for-One Scheme,lower license fee,subsidy support for e-buses and e-taxis,free charging services at government car parks,EV-charging at home Subsidy Scheme,etc.By comparing the cost of purchasing and owning vehicles with the cost of purchasing and owning electric vehicles as well as the market performance of electric vehicles to examine whether the financial incentives in Hong Kong can promote electric vehicles and serve as a prerequisite to low carbon transition.The results show that under government support and promotion associated with preferential policy,electric vehicles will become the future trend in Hong Kong with the advantage of lower emissions,energy saving,and environmental protection.
基金supported in part by National Key R&D Program of China(Grant No.2022YFC3803700)in part by the National Natural Science Foundation of China(Grant No.92067102)in part by the project of Beijing Laboratory of Advanced Information Networks.
文摘The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.
文摘This essay evaluates the behavioural dynamics generated by profit incentives and compares them with those in government-owned and charitable enterprises.Drawing on neoclassical microeconomics,agency theory,and institutional economics,it shows how the profit motive drives cost minimization,allocative efficiency,innovation,and consumer responsiveness.Profit expectations,formalized in endogenous growth models,act as catalysts for technological progress and dynamic efficiency,while agency-theoretic governance mechanisms align managerial incentives with shareholder interests.In contrast,government-owned enterprises operate under multi-objective welfare functions,often constrained by soft budget expectations,political interference,and X-inefficiencies that dilute efficiency.Charitable organizations,structured by the non-distribution constraint,emphasize social trust,equity,and mission fulfilment,supported by warm-glow altruism but constrained by free-rider problems and underfunding.A comparative evaluation suggests that profit-driven firms outperform in competitive markets producing private goods,whereas government and charitable forms play essential roles in addressing market failures and providing public or credence goods.The analysis affirms the institutionalist principle that ownership and governance structures must be aligned with the nature of the goods or services delivered.
文摘BACKGROUND Patients undergoing rectal cancer surgery frequently encounter challenges in their self-care abilities,disease knowledge,and emotional well-being postoperatively.Effective nursing interventions are critical for improving the quality of life and minimizing complications.This study explored the clinical implications of integrating health education guided by problem management with positive incentive nursing to address these challenges.AIM To evaluate the effect of this combined nursing model on postoperative self-care ability,disease knowledge,mood state,and complication rates in patients undergoing rectal cancer surgery.METHODS Eighty patients who underwent rectal cancer surgery between October 2021 and August 2024 were allocated into reference(routine care)and experimental(problem management-guided health education combined with positive incentive nursing)groups.The outcomes included exercise of self-care agency scale,disease knowledge(hospital-specific questionnaire),mood state(profile of mood states),and complication rates.RESULTS The experimental group demonstrated significant improvements in self-care ability(P<0.05),with higher scores for health knowledge,self-concept,self-care skills,and self-care responsibility than the reference group.Disease knowledge scores also improved markedly in the experimental group(P<0.05).Mood state scores showed a significant decrease in the negative dimensions(e.g.,anxiety and depression)and an increase in energy vitality(P<0.05).Additionally,the experimental group exhibited a lower complication rate than the reference group(7.5%vs 27.5%,P<0.05).CONCLUSION The integration of problem management-guided health education with positive incentive nursing significantly enhanced postoperative self-care abilities,disease knowledge,and emotional well-being while reducing complication rates.This model demonstrated potential for widespread adoption in clinical practice by offering a structured approach to improve patient outcomes and quality of life.
基金this project under Geran Putra Inisiatif(GPI)with reference of GP-GPI/2023/976210。
文摘Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.
基金partially supported by the National Natural Science Foundation of China (62173308)the Natural Science Foundation of Zhejiang Province of China (LR20F030001)the Jinhua Science and Technology Project (2022-1-042)。
文摘As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.
基金supported by Guangxi Power Grid Science and Technology Project(GXKJXM20222069).
文摘The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.
基金supported in part by Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China,under Grant J2022011.
文摘Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.
基金supported by the Innovation Scientists and Technicians Troop Construction Projects of Henan Province(224000510002)。
文摘Time-Sensitive Network(TSN)with deterministic transmission capability is increasingly used in many emerging fields.It mainly guarantees the Quality of Service(QoS)of applications with strict requirements on time and security.One of the core features of TSN is traffic scheduling with bounded low delay in the network.However,traffic scheduling schemes in TSN are usually synthesized offline and lack dynamism.To implement incremental scheduling of newly arrived traffic in TSN,we propose a Dynamic Response Incremental Scheduling(DR-IS)method for time-sensitive traffic and deploy it on a software-defined time-sensitive network architecture.Under the premise of meeting the traffic scheduling requirements,we adopt two modes,traffic shift and traffic exchange,to dynamically adjust the time slot injection position of the traffic in the original scheme,and determine the sending offset time of the new timesensitive traffic to minimize the global traffic transmission jitter.The evaluation results show that DRIS method can effectively control the large increase of traffic transmission jitter in incremental scheduling without affecting the transmission delay,thus realizing the dynamic incremental scheduling of time-sensitive traffic in TSN.
基金supported by Key Research and Development Program of China (No.2022YFC3005401)Key Research and Development Program of Yunnan Province,China (Nos.202203AA080009,202202AF080003)+1 种基金Science and Technology Achievement Transformation Program of Jiangsu Province,China (BA2021002)Fundamental Research Funds for the Central Universities (Nos.B220203006,B210203024).
文摘Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.
基金supported by the Project of Philosophy and Social Science Foundation of Shanghai,China(Grant No.2020BGL011).
文摘The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.
文摘Background: While global efforts have led to a decline in maternal and neonatal mortality, Sub-Saharan Africa continues to face disproportionately high rates, remaining far above the Sustainable Development Goal (SDG) targets. In Kenya, as the 2030 SDG deadline approaches, the gap in maternal, neonatal, and child health services remains significant. Addressing these challenges is critical to improving Maternal, Neonatal, and Child Health (MNCH) outcomes. Objective: This study explores how integration of digital health innovations into the MNCH chain of service delivery affects the quality of MNCH care within the selected PHC settings in Kajiado, Kisii and Migori Counties in Kenya. Methodology: This Quasi-experimental study was conducted 1-year post-intervention targeting a total of 482 pregnant women from intervention and control sites in Kisii, Kajiado and Migori Counties, Kenya. Data was analysed using Chi-Square test comparing frequencies between intervention and control groups when both variables are categorical. Results: Pre-intervention data revealed an increase in first ANC coverage within first trimester, from 167 to 278 post-intervention (p Linda mama social health insurance registrations increased from 1008 to 1135. At the intervention sites, 938 pregnant women got screened by midwives using portable mobile Obstetric Point-of-Care Ultrasound (OPOCUS) technology compared to the 27 cases that accessed ultrasound services in the noncontiguous control sites. The pilot sites midwives earned themselves an incentive income totaling Ksh 400,000 while the Community Health Promoters (CHPs) who created demand for OPOCUS earned an incentive income totaling Ksh 327,195 from their IGAs that were project supported. There was a significant increase in mobile health application usage and e-resources access for health information in the intervention group (p services and improved adherence to referrals. Conclusion: The success of digital health interventions in improving health-seeking behaviour, knowledge, and service uptake highlights the potential of such innovations to strengthen health systems and achieve universal health coverage. We recommend the intervention for a scale-up in other PHC settings in Kenya.
文摘Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.
基金sponsored by The National Natural Science Foundation of China(Grant No.71971020).
文摘With the increasing severity of urban traffic congestion and environmental pollution issues,Mobility-as-a-Service(MaaS)has garnered increasing attention as an emerging mode of transportation.Thus,how to motivate users to participate in MaaS has become an important research issue.This study first classified the incentive policies into four aspects:financial incentive policy,non-financial incentive policy,information policy,and convenience policy.Then,through online questionnaires and field interviews,456 sets of data were collected in Beijing,and the data were analyzed by the structural equation model and latent class model.The results show that the four incentive policies are positively correlated with users'participation in MaaS,among which financial incentive policy and information policy have the greatest impact,that is,they can better encourage users by increasing direct financial subsidies and broadening the information about MaaS.In addition,Latent Class Analysis was performed to class different users and it was found that the personal characteristics of users had some influence on willingness to participate in MaaS.Therefore,incentive policies should be designed to consider the needs and characteristics of different user groups to improve their willingness to participate in MaaS.The results can provide theoretical suggestions for the government to promote the widespread application of MaaS in urban transportation.
文摘With the rapid development of financial technology,middle managers in banks face both new challenges and opportunities.This paper conducts an in-depth analysis of the current state and issues surrounding the career development of middle managers in banks and explores effective incentive model designs and implementation strategies.Employing both quantitative and qualitative evaluation methods,the study assesses the practical impact of various incentive models.Through case analysis,targeted improvement suggestions are proposed.The findings reveal that a well-designed incentive mechanism significantly enhances middle managers’job satisfaction and loyalty,which is essential for the sustained growth of banks.
