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
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
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
Peer-to-peer(P2P)energy trading refers to a type of decentralized transaction,where the energy from distributed energy resources is directly traded between peers.A key challenge in peer-to-peer energy trading is desig...Peer-to-peer(P2P)energy trading refers to a type of decentralized transaction,where the energy from distributed energy resources is directly traded between peers.A key challenge in peer-to-peer energy trading is designing a safe,efficient,and transparent trading model and operating mechanism.In this study,we consider a P2P trading environment based on blockchain technology,where prosumers can submit bids or offers without knowing the reports of others.We propose an Arrow-d’Aspremont-Gerard-Varet(AGV)-based mechanism to encourage prosumers to submit their real reserve price and determine the P2P transaction price.We demonstrate that the AGV mechanism can achieve Bayesian incentive compatibility and budget balance.Kernel density estimation(KDE)is used to derive the prior distribution from the historical bid/offer information of the agents.Case studies are carried out to analyze and evaluate the proposed mechanism.Simulation results verify the effectiveness of the proposed mechanism in guiding agents to report the true reserve price while maximizing social welfare.Moreover,we discuss the advantages of budget balance for decentralized trading by comparing the Vickrey-Clarke-Groves(VCG)and AGV mechanisms.展开更多
As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of...As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.展开更多
Crowdsensing,as a data collection method that uses the mobile sensing ability of many users to help the public collect and extract useful information,has received extensive attention in data collection.Since crowdsens...Crowdsensing,as a data collection method that uses the mobile sensing ability of many users to help the public collect and extract useful information,has received extensive attention in data collection.Since crowdsensing relies on user equipment to consume resources to obtain information,and the quality and distribution of user equipment are uneven,crowdsensing has problems such as low participation enthusiasm of participants and low quality of collected data,which affects the widespread use of crowdsensing.This paper proposes to apply the blockchain to crowdsensing and solve the above challenges by utilizing the characteristics of the blockchain,such as immutability and openness.An architecture for constructing a crowdsensing incentive mechanism under distributed incentives is proposed.A multi-attribute auction algorithm and a k-nearest neighbor-based sensing data quality determination algorithm are proposed to support the architecture.Participating users upload data,determine data quality according to the algorithm,update user reputation,and realize the selection of perceived data.The process of screening data and updating reputation value is realized by smart contracts,which ensures that the information cannot be tampered with,thereby encouraging more users to participate.Results of the simulation show that using two algorithms can well reflect data quality and screen out malicious data.With the help of blockchain performance,the architecture and algorithm can achieve decentralized storage and tamper-proof information,which helps to motivate more users to participate in perception tasks and improve data quality.展开更多
Background:Researchers have a higher risk of anxiety and depression than the general population,so it is important to promote researchers’mental health.Method:Based on the data from 3210 global researchers surveyed b...Background:Researchers have a higher risk of anxiety and depression than the general population,so it is important to promote researchers’mental health.Method:Based on the data from 3210 global researchers surveyed by the journal Nature in 2021,confirmatory factor analysis,OLS regression and other regressions were used to explore the research incentive dimensions and their effects on researchers’mental health.Results:(1)Material incentive factors,work-family life balance factors,good organizational environment and spiritual motivation had significant positive effects on researchers’mental health.(2)The spiritual motivation could better promote researchers’mental health than the other factors.(3)Heterogeneity analysis showed that material incentive factors and spiritual motivation created more significant stimulating effects on the mental health of humanities and social sciences researchers.Work-family life balance factors were more effective in promoting the mental health of the mid-career group and the overtime group.Conclusion:Application of the four research incentives resulted in lower likelihood of anxiety or depression among researchers,and special attention should be paid to the role of the spiritual motivation.In order to promote researchers’mental health,different incentives should be applied to different researcher groups to better improve researchers’mental health.展开更多
Various Cardiovascular Diseases (CVDs) can be catastrophic and can lead to irreversible outcomes. Despite improved interventions for CVD prevention awareness, there continues to be discussion and research on diet-rela...Various Cardiovascular Diseases (CVDs) can be catastrophic and can lead to irreversible outcomes. Despite improved interventions for CVD prevention awareness, there continues to be discussion and research on diet-related CVD and mortality without addressing the problem. Instead of prioritizing public guidelines and policies, policymakers should understand CVD and address population barriers to adhering to a healthy diet that decreases CVD risk. Therefore, this project aims to analyze federal healthy food incentive policies to promote healthy diet behaviors that reduce CVD risk. The method used was existing data for a comparative policy analysis that included a policy proposal process: phases of progression, measures, and a policy model with data collection and requirements. This analysis compared a current federal food incentive program versus the proposed program. Results of the final analysis derived from the literature review and collected data stated consuming foods from the Mediterranean and other low-fat and low-salt diets reduced CVD risks that also reduced other risks secondary to CVD, such as obesity, diabetes, and Cerebrovascular Accident (CVA). Comparatively, combined healthy food incentives and disincentives were more effective for improving healthy behaviors than, in some cases, even after incentives were removed. Therefore, this policy analysis supports the indication for incentive policy change. However, the lack of federal stakeholders’ response to key policy changes upon proposal submission may require other methods of proposal dissemination. Nonetheless, focusing analysis on various Food Insecurity Nutrition Incentive (FINI) programs instead of one, multi-state program, which may have improved analysis outcomes, was the lesson learned.展开更多
To address the issue of information asymmetry between the two parties and moral hazard among service providers in the process of service outsourcing,this paper builds the Stackelberg game model based on the principal-...To address the issue of information asymmetry between the two parties and moral hazard among service providers in the process of service outsourcing,this paper builds the Stackelberg game model based on the principal-agent framework,examines the dynamic game situation before the contract being signed,and develops four information models.The analysis reveals a Pareto improvement in the game’s Nash equilibrium when comparing the four models from the standpoint of the supply chain.In the complete information scenario,the service level of the service provider,the customer company’s incentive effectiveness,and the supply chain system’s ultimate profit are all maximized.Furthermore,a coordinating mechanism for disposable profit is built in this study.The paper then suggests a blockchain-based architecture for the service outsourcing process supervision and a distributed incentive mechanism under the coordination mechanism in response to the inadequacy of the principal-agent theory to address the information asymmetry problem and the moral hazard problem.The experiment’s end findings demonstrate that both parties can benefit from the coordination mechanism,and the application of blockchain technology can resolve these issues and effectively encourage service providers.展开更多
Objective To provide reference for improving Chinese innovative drug research and development incentive policies.Methods Based on investigating the incentive policies for innovative drug research and development in cl...Objective To provide reference for improving Chinese innovative drug research and development incentive policies.Methods Based on investigating the incentive policies for innovative drug research and development in clinical research,evaluation and approval in China,anti-tumor drugs were taken as the research object to discuss relevant policies from the perspective of clinical trials and registration approval based on data statistics and current situation analysis.Results and Conclusion Driven by a series of incentive policies for innovative drug R&D,great achievements have been made on anti-tumor drugs.However,there are problems such as concentration of drug targets,homogenization of clinical trials,and gaps in some drugs with large clinical needs.To improve incentive policies for innovative drug R&D,China should adhere to the orientation of clinical value,focusing on basic research and translational research,improving evaluation and approval capabilities,and establishing a sound ecosystem for innovative drugs.展开更多
Based on the actual situation of the establishment of the incentive system for human resource management in universities,the constituent elements and relevant principles of the incentive system for human resources in ...Based on the actual situation of the establishment of the incentive system for human resource management in universities,the constituent elements and relevant principles of the incentive system for human resources in universities are expounded on,the current situation of the actual needs of the faculty and staff in universities is studied and analyzed,and practical plans for establishing the concept and implementing the incentive system in universities are proposed,with relevant incentive mechanisms for human resource management focusing on differentiated needs developed for reference.展开更多
With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterp...With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterprises need to optimize the incentive mechanism of R&D staff,to arouse the R&D staff's enthusiasm and creativity,to adapt to the new market competition and further improve market value.Whilst the incentive mechanism optimizing processing needs to consider not only the changing market environment but also the personal and working characteristics of R&D staff.This paper summarizes the characteristics of the current Chinese power enterprises' R&D staff:staff's theory quality is high,but insensitive to the market;they are confronted with heavy workload and diversified job choices;managers can observe their behavior choices or not;besides,the process of R&D is complex and the market reactions of R&D achievements are uncertain.Based on the premise of the above features,two incentive models are established in this paper from the point of view of enterprise managers.One is for the situation when staff's behavior choices can be observed;the other is for the situation when staff's behavior choices cannot be observed.Through solving the model,we analyze the optimization path of electric power enterprises R&D staff incentive mechanism under these conditions:(1) when staff's behavior choices can be observed,managers can pay more to the R&D staff who develop products with higher output value,in order to encourage them to work harder.(2) when staff's behavior choices cannot be observed,managers should take reasonable strategies according to the different situations:a.when R&D staff incentive totally depend on the market value of the R&D achievements,managers should allocate workload rationally according to their different technical levels;b.when the market reactions of R&D results become more precarious,managers need to reduce the incentive intensity which based on the market value and raise their fixed salary level;c.when R&D staff become more risk averse,managers should reduce the incentive intensity which based on the market value and raise their fixed salary level;on the contrary,managers should improve the incentive intensity and reduce the fixed salary level.展开更多
The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds ma...The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies(ESSs) for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.展开更多
Both conflict and asymmetric information exist betweenthe telecom operators and the service provider,and result in illegal behaviors of the service provider.The relationship between the telecom operators andthe servic...Both conflict and asymmetric information exist betweenthe telecom operators and the service provider,and result in illegal behaviors of the service provider.The relationship between the telecom operators andthe service provider is classical multi-task principalagentrelationship. The multi-task incentive for theservice provider is considered in the design of theprincipal-agent incentive contract, and it is necessaryto add the multi-task incentive to the serviceproviders through the analysis of the risk costs andthe agency costs of this problem.展开更多
In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage r...In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.展开更多
AIM:To study the acceptability of incentives for behavior changes in individuals with diabetes,comparing financial incentives to self-rewards and non-financial incentives.METHODS:A national online survey of United Sta...AIM:To study the acceptability of incentives for behavior changes in individuals with diabetes,comparing financial incentives to self-rewards and non-financial incentives.METHODS:A national online survey of United States adults with diabetes was conducted in March 2013(n = 153).This survey was designed for this study,with iterative testing and modifications in a pilot population.We measured the demographics of individuals,their interest in incentives,as well as the perceived challenge of diabetes self-management tasks,and expectations of incentives to improve diabetes self-management(financial,non-financial and self-rewards).Using an ordered logistic regression model,we assessed the association between a 32-point score of the perceived challenge of the self-management tasks and the three types of rewards.RESULTS:Ninety-six percent of individuals were interested in financial incentives,60% in non-financial incentives and 72% in self-rewards.Patients were less likely to use financial incentives when they perceived the behavior to be more challenging(odds ratio of using financial incentives of 0.82(95%CI:0.72-0.93) for each point of the behavior score).While the effectiveness of incentives may vary according to the perceived level of challenge of each behavior,participants did not expect to need large amounts to motivate them to modify their behavior.The expected average amounts needed to motivate a 5 lb weight loss in our population and to maintain this weight change for a year was $258(interquartile range of $10-100) and $713(interquartile range of $25-250) for a 15 lb weight loss.The difference in mean amount estimates for 5 lb and 15 lb weight loss was significant(P < 0.001).CONCLUSION:Individuals with diabetes are willing to consider financial incentives to improve diabetes selfmanagement.Future studies are needed to explore incentive programs and their effectiveness for diabetes.展开更多
The analysis of a supervision environment is the first step for a company to enter the new electricity market. Transmission and distribution assets are the main investment targets of a company. The overseas power mark...The analysis of a supervision environment is the first step for a company to enter the new electricity market. Transmission and distribution assets are the main investment targets of a company. The overseas power market belongs to the regulated industry;whether it is a stock M&A project or a green land bidding project, the regulatory environment determines the assets. The level of return and investment risk that guides the operation strategy of existing overseas assets, has a significant impact on the investment and operations of international companies. A comprehensive and rapid assessment of the regulatory environment can help the project teams of international companies understand the macroenvironment of the target electricity market within a short period, quickly identify investment risks, qualitatively analyze the return level of the underlying assets, shorten the decision time, capture investment opportunities, and enhance the team. Efficiency and quality of work are factors of great importance.展开更多
Distribution system will affect the labor incentive that has been heatedly discussed by recent literatures.Using a unique micro dataset, this paper dem on strates that the equalitaria n distributi on system is one of ...Distribution system will affect the labor incentive that has been heatedly discussed by recent literatures.Using a unique micro dataset, this paper dem on strates that the equalitaria n distributi on system is one of the reas ons for the in sufficie nt labor incentive during the Chinese Collective Agriculture period. Specifically speaking, in the distribution of basic rations, the proportion for children (aged 1-3 and 4-7 years) was often beyond their nutrition demand, resulting the dissatisfaction of other families with more laborers and less children, thus these households will reduce their labor supply gradually. At the same time, the existence of outstanding accounts makes it a failure to use work points to buy distributions, which is the mechanism of the distribution system and insufficient labor incentive. All the results have been accepted by the robustness tests. The study will help to understand the distribution system and labor incentive, as well as the failure of the Chinese collective agriculture.展开更多
Objectives: While the value of glycemic control to minimize adverse health outcomes among patients with diabetes is clear, achieving hemoglobin A1c (A1c) goals remain a challenge. We evaluated the use of financial inc...Objectives: While the value of glycemic control to minimize adverse health outcomes among patients with diabetes is clear, achieving hemoglobin A1c (A1c) goals remain a challenge. We evaluated the use of financial incentives to increase enrollment and improve glycemic control among patients invited to participate in a monthly diabetes group appointment (DGA) as part of their enrollment in DaVita HealthCare Partners, a large southern California managed care organization. Methods: Adult diabetes patients (≥18 years) with a currently uncontrolled hemoglobin A1c level (>8.0% if 9.0% if ≥ 65 years) were randomized to 1) no DGA, 2) DGA with no financial incentives (non-incentive DGA) or 3) DGA with financial incentives (incentive DGA). Results: Nine sites among four regions of the greater Los Angeles area participated. Each site offered one non-incentive DGA and one incentive DGA. Over 1500 patients were identified for recruitment and at the peak of enrollment, 299 patients were enrolled in 18 DGAs. On average, hemoglobin A1c values dropped more for patients participating in the incentive DGA (9.9% to 8.7%, -1.2%) versus non-incentive DGA (9.7% to 9.0%, -0.7%) versus no DGA group (9.1% to 8.7%, -0.4%). Several unexpected implementation challenges arose which complicated evaluation but provide important learning lessons. Conclusions: Management of chronic diseases like diabetes is challenging for patients and the primary care system alike. Continuing to implement and evaluate programs under “real-world” conditions can provide further insight into how best to support patients with diabetes and their primary care teams in order to achieve glycemic control and avoid preventable complications.展开更多
Nodes cooperation is a significant prerequisite for the realization of the relaying Ad Hoc.While with the development of multi-hop cellular networks, how to stimulate intermediate nodes to do the packet-forwarding des...Nodes cooperation is a significant prerequisite for the realization of the relaying Ad Hoc.While with the development of multi-hop cellular networks, how to stimulate intermediate nodes to do the packet-forwarding deserves more concerning.At present research,the incentive schemes in pure Ad Hoc and multi-hop cellular networks are analyzed and compared to classify the strengths and drawbacks of each scheme.We explain in particular what the key issues are to implement incentive schemes for cooperation. Finally,an incentive scheme based on integration of reputation and charging systems is proposed not only to block the existence of selfish nodes,but to satisfy the rational requirement of nodes.展开更多
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 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 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 National Natural Science Foundation of China(U2066211,52177124,52107134)the Institute of Electrical Engineering,CAS(E155610101)+1 种基金the DNL Cooperation Fund,CAS(DNL202023)the Youth Innovation Promotion Association of CAS(2019143).
文摘Peer-to-peer(P2P)energy trading refers to a type of decentralized transaction,where the energy from distributed energy resources is directly traded between peers.A key challenge in peer-to-peer energy trading is designing a safe,efficient,and transparent trading model and operating mechanism.In this study,we consider a P2P trading environment based on blockchain technology,where prosumers can submit bids or offers without knowing the reports of others.We propose an Arrow-d’Aspremont-Gerard-Varet(AGV)-based mechanism to encourage prosumers to submit their real reserve price and determine the P2P transaction price.We demonstrate that the AGV mechanism can achieve Bayesian incentive compatibility and budget balance.Kernel density estimation(KDE)is used to derive the prior distribution from the historical bid/offer information of the agents.Case studies are carried out to analyze and evaluate the proposed mechanism.Simulation results verify the effectiveness of the proposed mechanism in guiding agents to report the true reserve price while maximizing social welfare.Moreover,we discuss the advantages of budget balance for decentralized trading by comparing the Vickrey-Clarke-Groves(VCG)and AGV mechanisms.
文摘As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.
基金supported by National Key R&D Program of China(2020YFB1807800).
文摘Crowdsensing,as a data collection method that uses the mobile sensing ability of many users to help the public collect and extract useful information,has received extensive attention in data collection.Since crowdsensing relies on user equipment to consume resources to obtain information,and the quality and distribution of user equipment are uneven,crowdsensing has problems such as low participation enthusiasm of participants and low quality of collected data,which affects the widespread use of crowdsensing.This paper proposes to apply the blockchain to crowdsensing and solve the above challenges by utilizing the characteristics of the blockchain,such as immutability and openness.An architecture for constructing a crowdsensing incentive mechanism under distributed incentives is proposed.A multi-attribute auction algorithm and a k-nearest neighbor-based sensing data quality determination algorithm are proposed to support the architecture.Participating users upload data,determine data quality according to the algorithm,update user reputation,and realize the selection of perceived data.The process of screening data and updating reputation value is realized by smart contracts,which ensures that the information cannot be tampered with,thereby encouraging more users to participate.Results of the simulation show that using two algorithms can well reflect data quality and screen out malicious data.With the help of blockchain performance,the architecture and algorithm can achieve decentralized storage and tamper-proof information,which helps to motivate more users to participate in perception tasks and improve data quality.
文摘Background:Researchers have a higher risk of anxiety and depression than the general population,so it is important to promote researchers’mental health.Method:Based on the data from 3210 global researchers surveyed by the journal Nature in 2021,confirmatory factor analysis,OLS regression and other regressions were used to explore the research incentive dimensions and their effects on researchers’mental health.Results:(1)Material incentive factors,work-family life balance factors,good organizational environment and spiritual motivation had significant positive effects on researchers’mental health.(2)The spiritual motivation could better promote researchers’mental health than the other factors.(3)Heterogeneity analysis showed that material incentive factors and spiritual motivation created more significant stimulating effects on the mental health of humanities and social sciences researchers.Work-family life balance factors were more effective in promoting the mental health of the mid-career group and the overtime group.Conclusion:Application of the four research incentives resulted in lower likelihood of anxiety or depression among researchers,and special attention should be paid to the role of the spiritual motivation.In order to promote researchers’mental health,different incentives should be applied to different researcher groups to better improve researchers’mental health.
文摘Various Cardiovascular Diseases (CVDs) can be catastrophic and can lead to irreversible outcomes. Despite improved interventions for CVD prevention awareness, there continues to be discussion and research on diet-related CVD and mortality without addressing the problem. Instead of prioritizing public guidelines and policies, policymakers should understand CVD and address population barriers to adhering to a healthy diet that decreases CVD risk. Therefore, this project aims to analyze federal healthy food incentive policies to promote healthy diet behaviors that reduce CVD risk. The method used was existing data for a comparative policy analysis that included a policy proposal process: phases of progression, measures, and a policy model with data collection and requirements. This analysis compared a current federal food incentive program versus the proposed program. Results of the final analysis derived from the literature review and collected data stated consuming foods from the Mediterranean and other low-fat and low-salt diets reduced CVD risks that also reduced other risks secondary to CVD, such as obesity, diabetes, and Cerebrovascular Accident (CVA). Comparatively, combined healthy food incentives and disincentives were more effective for improving healthy behaviors than, in some cases, even after incentives were removed. Therefore, this policy analysis supports the indication for incentive policy change. However, the lack of federal stakeholders’ response to key policy changes upon proposal submission may require other methods of proposal dissemination. Nonetheless, focusing analysis on various Food Insecurity Nutrition Incentive (FINI) programs instead of one, multi-state program, which may have improved analysis outcomes, was the lesson learned.
基金Province Keys Research and Development Program of Shandong(Soft Science Projects)[No.2021RKY01007]Major Scientific and Technological Innovation Projects in Shandong Province[No.2018CXGC0703].
文摘To address the issue of information asymmetry between the two parties and moral hazard among service providers in the process of service outsourcing,this paper builds the Stackelberg game model based on the principal-agent framework,examines the dynamic game situation before the contract being signed,and develops four information models.The analysis reveals a Pareto improvement in the game’s Nash equilibrium when comparing the four models from the standpoint of the supply chain.In the complete information scenario,the service level of the service provider,the customer company’s incentive effectiveness,and the supply chain system’s ultimate profit are all maximized.Furthermore,a coordinating mechanism for disposable profit is built in this study.The paper then suggests a blockchain-based architecture for the service outsourcing process supervision and a distributed incentive mechanism under the coordination mechanism in response to the inadequacy of the principal-agent theory to address the information asymmetry problem and the moral hazard problem.The experiment’s end findings demonstrate that both parties can benefit from the coordination mechanism,and the application of blockchain technology can resolve these issues and effectively encourage service providers.
文摘Objective To provide reference for improving Chinese innovative drug research and development incentive policies.Methods Based on investigating the incentive policies for innovative drug research and development in clinical research,evaluation and approval in China,anti-tumor drugs were taken as the research object to discuss relevant policies from the perspective of clinical trials and registration approval based on data statistics and current situation analysis.Results and Conclusion Driven by a series of incentive policies for innovative drug R&D,great achievements have been made on anti-tumor drugs.However,there are problems such as concentration of drug targets,homogenization of clinical trials,and gaps in some drugs with large clinical needs.To improve incentive policies for innovative drug R&D,China should adhere to the orientation of clinical value,focusing on basic research and translational research,improving evaluation and approval capabilities,and establishing a sound ecosystem for innovative drugs.
文摘Based on the actual situation of the establishment of the incentive system for human resource management in universities,the constituent elements and relevant principles of the incentive system for human resources in universities are expounded on,the current situation of the actual needs of the faculty and staff in universities is studied and analyzed,and practical plans for establishing the concept and implementing the incentive system in universities are proposed,with relevant incentive mechanisms for human resource management focusing on differentiated needs developed for reference.
基金supported by 2016 annual North China Electric Power University undergraduate innovative training program research project(Grant No.20162183)
文摘With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterprises need to optimize the incentive mechanism of R&D staff,to arouse the R&D staff's enthusiasm and creativity,to adapt to the new market competition and further improve market value.Whilst the incentive mechanism optimizing processing needs to consider not only the changing market environment but also the personal and working characteristics of R&D staff.This paper summarizes the characteristics of the current Chinese power enterprises' R&D staff:staff's theory quality is high,but insensitive to the market;they are confronted with heavy workload and diversified job choices;managers can observe their behavior choices or not;besides,the process of R&D is complex and the market reactions of R&D achievements are uncertain.Based on the premise of the above features,two incentive models are established in this paper from the point of view of enterprise managers.One is for the situation when staff's behavior choices can be observed;the other is for the situation when staff's behavior choices cannot be observed.Through solving the model,we analyze the optimization path of electric power enterprises R&D staff incentive mechanism under these conditions:(1) when staff's behavior choices can be observed,managers can pay more to the R&D staff who develop products with higher output value,in order to encourage them to work harder.(2) when staff's behavior choices cannot be observed,managers should take reasonable strategies according to the different situations:a.when R&D staff incentive totally depend on the market value of the R&D achievements,managers should allocate workload rationally according to their different technical levels;b.when the market reactions of R&D results become more precarious,managers need to reduce the incentive intensity which based on the market value and raise their fixed salary level;c.when R&D staff become more risk averse,managers should reduce the incentive intensity which based on the market value and raise their fixed salary level;on the contrary,managers should improve the incentive intensity and reduce the fixed salary level.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61672408, U1405255, 61502368, 61602537, 61602357, 61672413, U1509214, U1135002)National High Technology Research and Development Program (863 Program) (Grant Nos. 2015AA016007, 2015AA017203)+5 种基金China Postdoctoral Science Foundation Funded Project (Grant No.2016M592762)Shaanxi Science & Technology Coordination & Innovation Project (Grant No.2016TZC-G-6-3)Shaanxi Provincial Natural Science Foundation (Grant Nos. 2015JQ6227, 2016JM6005)China 111 Project (Grant No. B16037)Beijing Municipal Social Science Foundation(Grant No. 16XCC023)Fundamental Research Funds for the Central Universities (Grant Nos. JB150308, JB150309, JB161501, JBG161511)
文摘The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies(ESSs) for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.
文摘Both conflict and asymmetric information exist betweenthe telecom operators and the service provider,and result in illegal behaviors of the service provider.The relationship between the telecom operators andthe service provider is classical multi-task principalagentrelationship. The multi-task incentive for theservice provider is considered in the design of theprincipal-agent incentive contract, and it is necessaryto add the multi-task incentive to the serviceproviders through the analysis of the risk costs andthe agency costs of this problem.
基金supported by Beijing Natural Science Foundation under Grant number L172049the National Science and CAS Engineering Laboratory for Intelligent Agricultural Machinery Equipment GC201907-02
文摘In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.
文摘AIM:To study the acceptability of incentives for behavior changes in individuals with diabetes,comparing financial incentives to self-rewards and non-financial incentives.METHODS:A national online survey of United States adults with diabetes was conducted in March 2013(n = 153).This survey was designed for this study,with iterative testing and modifications in a pilot population.We measured the demographics of individuals,their interest in incentives,as well as the perceived challenge of diabetes self-management tasks,and expectations of incentives to improve diabetes self-management(financial,non-financial and self-rewards).Using an ordered logistic regression model,we assessed the association between a 32-point score of the perceived challenge of the self-management tasks and the three types of rewards.RESULTS:Ninety-six percent of individuals were interested in financial incentives,60% in non-financial incentives and 72% in self-rewards.Patients were less likely to use financial incentives when they perceived the behavior to be more challenging(odds ratio of using financial incentives of 0.82(95%CI:0.72-0.93) for each point of the behavior score).While the effectiveness of incentives may vary according to the perceived level of challenge of each behavior,participants did not expect to need large amounts to motivate them to modify their behavior.The expected average amounts needed to motivate a 5 lb weight loss in our population and to maintain this weight change for a year was $258(interquartile range of $10-100) and $713(interquartile range of $25-250) for a 15 lb weight loss.The difference in mean amount estimates for 5 lb and 15 lb weight loss was significant(P < 0.001).CONCLUSION:Individuals with diabetes are willing to consider financial incentives to improve diabetes selfmanagement.Future studies are needed to explore incentive programs and their effectiveness for diabetes.
基金supported by National Key Research and Development Program of China (2018YFB0904000)。
文摘The analysis of a supervision environment is the first step for a company to enter the new electricity market. Transmission and distribution assets are the main investment targets of a company. The overseas power market belongs to the regulated industry;whether it is a stock M&A project or a green land bidding project, the regulatory environment determines the assets. The level of return and investment risk that guides the operation strategy of existing overseas assets, has a significant impact on the investment and operations of international companies. A comprehensive and rapid assessment of the regulatory environment can help the project teams of international companies understand the macroenvironment of the target electricity market within a short period, quickly identify investment risks, qualitatively analyze the return level of the underlying assets, shorten the decision time, capture investment opportunities, and enhance the team. Efficiency and quality of work are factors of great importance.
文摘Distribution system will affect the labor incentive that has been heatedly discussed by recent literatures.Using a unique micro dataset, this paper dem on strates that the equalitaria n distributi on system is one of the reas ons for the in sufficie nt labor incentive during the Chinese Collective Agriculture period. Specifically speaking, in the distribution of basic rations, the proportion for children (aged 1-3 and 4-7 years) was often beyond their nutrition demand, resulting the dissatisfaction of other families with more laborers and less children, thus these households will reduce their labor supply gradually. At the same time, the existence of outstanding accounts makes it a failure to use work points to buy distributions, which is the mechanism of the distribution system and insufficient labor incentive. All the results have been accepted by the robustness tests. The study will help to understand the distribution system and labor incentive, as well as the failure of the Chinese collective agriculture.
文摘Objectives: While the value of glycemic control to minimize adverse health outcomes among patients with diabetes is clear, achieving hemoglobin A1c (A1c) goals remain a challenge. We evaluated the use of financial incentives to increase enrollment and improve glycemic control among patients invited to participate in a monthly diabetes group appointment (DGA) as part of their enrollment in DaVita HealthCare Partners, a large southern California managed care organization. Methods: Adult diabetes patients (≥18 years) with a currently uncontrolled hemoglobin A1c level (>8.0% if 9.0% if ≥ 65 years) were randomized to 1) no DGA, 2) DGA with no financial incentives (non-incentive DGA) or 3) DGA with financial incentives (incentive DGA). Results: Nine sites among four regions of the greater Los Angeles area participated. Each site offered one non-incentive DGA and one incentive DGA. Over 1500 patients were identified for recruitment and at the peak of enrollment, 299 patients were enrolled in 18 DGAs. On average, hemoglobin A1c values dropped more for patients participating in the incentive DGA (9.9% to 8.7%, -1.2%) versus non-incentive DGA (9.7% to 9.0%, -0.7%) versus no DGA group (9.1% to 8.7%, -0.4%). Several unexpected implementation challenges arose which complicated evaluation but provide important learning lessons. Conclusions: Management of chronic diseases like diabetes is challenging for patients and the primary care system alike. Continuing to implement and evaluate programs under “real-world” conditions can provide further insight into how best to support patients with diabetes and their primary care teams in order to achieve glycemic control and avoid preventable complications.
基金supported by National "863" High Technology Research and Development Program Foundation(No.2006AA01Z208)Six Talented Eminence Foundation of Jiangsu Province+1 种基金Natural Science Foundation of Jiangsu Province(No. BK2004149)Green-Blue Academic Talented Project Foundation of Jiangsu Province
文摘Nodes cooperation is a significant prerequisite for the realization of the relaying Ad Hoc.While with the development of multi-hop cellular networks, how to stimulate intermediate nodes to do the packet-forwarding deserves more concerning.At present research,the incentive schemes in pure Ad Hoc and multi-hop cellular networks are analyzed and compared to classify the strengths and drawbacks of each scheme.We explain in particular what the key issues are to implement incentive schemes for cooperation. Finally,an incentive scheme based on integration of reputation and charging systems is proposed not only to block the existence of selfish nodes,but to satisfy the rational requirement of nodes.
